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Merge branch 'noetic' into mycobot_280pi

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wangWking 2022-06-13 09:29:44 +08:00 • committed by GitHub
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94
mycobot_320/new_mycobot_320_pi/CMakeLists.txt Normal file
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cmake_minimum_required(VERSION 3.0.2)
project(new_mycobot_320_pi)
add_compile_options(-std=c++11)
## Find catkin and any catkin packagess
find_package(catkin REQUIRED COMPONENTS
roscpp
rospy
std_msgs
actionlib
image_transport
cv_bridge
mycobot_communication
mycobot_description
)
## Generate messages in the 'msg' folder
# add_message_files(
# FILES
# Message1.msg
# Message2.msg
# )
## Generate services in the 'srv' folder
# add_service_files(
# FILES
# Service1.srv
# Service2.srv
# )
## Generate actions in the 'action' folder
# add_action_files(
# FILES
# Action1.action
# Action2.action
# )
## Generate added messages and services with any dependencies listed here
# generate_messages(
# DEPENDENCIES
# std_msgs
# )
## Generate dynamic reconfigure parameters in the 'cfg' folder
# generate_dynamic_reconfigure_options(
# cfg/DynReconf1.cfg
# cfg/DynReconf2.cfg
# )
## Declare a catkin package
catkin_package(
CATKIN_DEPENDS std_msgs actionlib
# INCLUDE_DIRS include
# LIBRARIES new_mycobot_320
# CATKIN_DEPENDS roscpp rospy std_msgs
# DEPENDS system_lib
)
## Specify additional locations of header files
## Your package locations should be listed before other locations
include_directories(include${catkin_INCLUDE_DIRS} ${OpenCV_INCLUDE_DIRS})
catkin_install_python(PROGRAMS
scripts/mycobot_320_follow_display.py
scripts/mycobot_320_slider.py
scripts/mycobot_320_teleop_keyboard.py
scripts/mycobot_320_listen_real.py
scripts/mycobot_320_listen_real_of_topic.py
scripts/mycobot_320_detect_marker.py
scripts/mycobot_320_following_marker.py
scripts/mycobot_320_follow_and_pump.py
scripts/mycobot_320_simple_gui.py
DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
)
install(DIRECTORY launch DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
PATTERN "setup_assistant.launch" EXCLUDE)
install(DIRECTORY config DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION})
# find_package(OpenCV REQUIRED)
# add_executable(opencv_camera src/opencv_camera.cpp)
# Declare a C++ library
# add_library(${PROJECT_NAME}
# src/opencv_camera.cpp
# )
# target_link_libraries(opencv_camera ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})
# add_executable(camera_display src/camera_display)
# target_link_libraries(camera_display ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})

25
mycobot_320/new_mycobot_320_pi/LICENSE Normal file
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BSD 2-Clause License
Copyright (c) 2020, Elephant Robotics
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

216
mycobot_320/new_mycobot_320_pi/config/mycobot_320_with_marker.rviz Normal file
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Panels:
- Class: rviz/Displays
Help Height: 78
Name: Displays
Property Tree Widget:
Expanded:
- /Global Options1
- /Status1
- /RobotModel1
- /TF1
- /Marker1
- /Marker1/Namespaces1
Splitter Ratio: 0.5
Tree Height: 662
- Class: rviz/Selection
Name: Selection
- Class: rviz/Tool Properties
Expanded:
- /2D Pose Estimate1
- /2D Nav Goal1
- /Publish Point1
Name: Tool Properties
Splitter Ratio: 0.588679016
- Class: rviz/Views
Expanded:
- /Current View1
Name: Views
Splitter Ratio: 0.5
- Class: rviz/Time
Experimental: false
Name: Time
SyncMode: 0
SyncSource: ""
Toolbars:
toolButtonStyle: 2
Visualization Manager:
Class: ""
Displays:
- Alpha: 0.5
Cell Size: 1
Class: rviz/Grid
Color: 160; 160; 164
Enabled: true
Line Style:
Line Width: 0.0299999993
Value: Lines
Name: Grid
Normal Cell Count: 0
Offset:
X: 0
Y: 0
Z: 0
Plane: XY
Plane Cell Count: 10
Reference Frame: <Fixed Frame>
Value: true
- Alpha: 1
Class: rviz/RobotModel
Collision Enabled: false
Enabled: true
Links:
All Links Enabled: true
Expand Joint Details: false
Expand Link Details: false
Expand Tree: false
Link Tree Style: Links in Alphabetic Order
joint1:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
joint2:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
joint3:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
joint4:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
joint5:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
joint6:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
joint6_flange:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
Name: RobotModel
Robot Description: robot_description
TF Prefix: ""
Update Interval: 0
Value: true
Visual Enabled: true
- Class: rviz/TF
Enabled: true
Frame Timeout: 15
Frames:
All Enabled: true
basic_shapes:
Value: true
joint1:
Value: true
joint2:
Value: true
joint3:
Value: true
joint4:
Value: true
joint5:
Value: true
joint6:
Value: true
joint6_flange:
Value: true
Marker Scale: 0.300000012
Name: TF
Show Arrows: true
Show Axes: true
Show Names: true
Tree:
joint1:
joint2:
joint3:
joint4:
joint5:
joint6:
joint6_flange:
basic_shapes:
{}
Update Interval: 0
Value: true
- Class: rviz/Marker
Enabled: true
Marker Topic: /visualization_marker
Name: Marker
Namespaces:
basic_cube: true
Queue Size: 100
Value: true
Enabled: true
Global Options:
Background Color: 48; 48; 48
Default Light: true
Fixed Frame: base
Frame Rate: 30
Name: root
Tools:
- Class: rviz/Interact
Hide Inactive Objects: true
- Class: rviz/MoveCamera
- Class: rviz/Select
- Class: rviz/FocusCamera
- Class: rviz/Measure
- Class: rviz/SetInitialPose
Topic: /initialpose
- Class: rviz/SetGoal
Topic: /move_base_simple/goal
- Class: rviz/PublishPoint
Single click: true
Topic: /clicked_point
Value: true
Views:
Current:
Class: rviz/Orbit
Distance: 1.20289087
Enable Stereo Rendering:
Stereo Eye Separation: 0.0599999987
Stereo Focal Distance: 1
Swap Stereo Eyes: false
Value: false
Focal Point:
X: -0.0706475973
Y: -0.0814988762
Z: 0.107583851
Focal Shape Fixed Size: true
Focal Shape Size: 0.0500000007
Invert Z Axis: false
Name: Current View
Near Clip Distance: 0.00999999978
Pitch: 0.440398335
Target Frame: <Fixed Frame>
Value: Orbit (rviz)
Yaw: 0.430389732
Saved: ~
Window Geometry:
Displays:
collapsed: false
Height: 903
Hide Left Dock: false
Hide Right Dock: false
QMainWindow State: 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
Selection:
collapsed: false
Time:
collapsed: false
Tool Properties:
collapsed: false
Views:
collapsed: false
Width: 1853
X: 65
Y: 24

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mycobot_320/new_mycobot_320_pi/config/new_mycobot_320_pi.rviz Normal file
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Panels:
- Class: rviz/Displays
Help Height: 78
Name: Displays
Property Tree Widget:
Expanded:
- /Global Options1
- /Status1
- /TF1
- /TF1/Tree1
Splitter Ratio: 0.5
Tree Height: 617
- Class: rviz/Selection
Name: Selection
- Class: rviz/Tool Properties
Expanded:
- /2D Pose Estimate1
- /2D Nav Goal1
- /Publish Point1
Name: Tool Properties
Splitter Ratio: 0.588679016
- Class: rviz/Views
Expanded:
- /Current View1
Name: Views
Splitter Ratio: 0.5
- Class: rviz/Time
Experimental: false
Name: Time
SyncMode: 0
SyncSource: ""
Toolbars:
toolButtonStyle: 2
Visualization Manager:
Class: ""
Displays:
- Alpha: 0.5
Cell Size: 1
Class: rviz/Grid
Color: 160; 160; 164
Enabled: true
Line Style:
Line Width: 0.0299999993
Value: Lines
Name: Grid
Normal Cell Count: 0
Offset:
X: 0
Y: 0
Z: 0
Plane: XY
Plane Cell Count: 10
Reference Frame: <Fixed Frame>
Value: true
- Alpha: 1
Class: rviz/RobotModel
Collision Enabled: false
Enabled: true
Links:
All Links Enabled: true
Expand Joint Details: false
Expand Link Details: false
Expand Tree: false
Link Tree Style: Links in Alphabetic Order
base:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link1:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link2:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link3:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link4:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link5:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link6:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
Name: RobotModel
Robot Description: robot_description
TF Prefix: ""
Update Interval: 0
Value: true
Visual Enabled: true
- Class: rviz/TF
Enabled: true
Frame Timeout: 15
Frames:
All Enabled: true
base:
Value: true
link1:
Value: true
link2:
Value: true
link3:
Value: true
link4:
Value: true
link5:
Value: true
link6:
Value: true
Marker Scale: 0.300000012
Name: TF
Show Arrows: true
Show Axes: true
Show Names: true
Tree:
base:
link1:
link2:
link3:
link4:
link5:
link6:
{}
Update Interval: 0
Value: true
Enabled: true
Global Options:
Background Color: 48; 48; 48
Default Light: true
Fixed Frame: base
Frame Rate: 30
Name: root
Tools:
- Class: rviz/Interact
Hide Inactive Objects: true
- Class: rviz/MoveCamera
- Class: rviz/Select
- Class: rviz/FocusCamera
- Class: rviz/Measure
- Class: rviz/SetInitialPose
Topic: /initialpose
- Class: rviz/SetGoal
Topic: /move_base_simple/goal
- Class: rviz/PublishPoint
Single click: true
Topic: /clicked_point
Value: true
Views:
Current:
Class: rviz/Orbit
Distance: 1.44857454
Enable Stereo Rendering:
Stereo Eye Separation: 0.0599999987
Stereo Focal Distance: 1
Swap Stereo Eyes: false
Value: false
Focal Point:
X: 0
Y: 0
Z: 0
Focal Shape Fixed Size: true
Focal Shape Size: 0.0500000007
Invert Z Axis: false
Name: Current View
Near Clip Distance: 0.00999999978
Pitch: 0.584796429
Target Frame: <Fixed Frame>
Value: Orbit (rviz)
Yaw: 3.21858907
Saved: ~
Window Geometry:
Displays:
collapsed: false
Height: 898
Hide Left Dock: false
Hide Right Dock: false
QMainWindow State: 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
Selection:
collapsed: false
Time:
collapsed: false
Tool Properties:
collapsed: false
Views:
collapsed: false
Width: 1855
X: 65
Y: 24

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mycobot_320/new_mycobot_320_pi/launch/mycobot_320_detect_marker.launch Normal file
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<launch>
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/mycobot_320_with_marker.rviz" />
<arg name="gui" default="true" />
<arg name="num" default="0" />
<include file="$(find new_mycobot_320_pi)/launch/mycobot_320_slider.launch">
<arg name="model" value="$(arg model)" />
<arg name="rvizconfig" value="$(arg rvizconfig)" />
<arg name="gui" value="$(arg gui)" />
</include>
<node name="opencv_camera" pkg="new_mycobot_320_pi" type="opencv_camera" args="$(arg num)"/>
<node name="detect_marker" pkg="new_mycobot_320_pi" type="mycobot_320_detect_marker.py" />
<node name="following_marker" pkg="new_mycobot_320_pi" type="mycobot_320_following_marker.py" />
</launch>

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mycobot_320/new_mycobot_320_pi/launch/mycobot_320_detect_marker_with_topic.launch Normal file
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<launch>
<arg name="port" default="/dev/ttyAMA0" />
<arg name="baud" default="1000000" />
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/mycobot_320_with_marker.rviz" />
<arg name="gui" default="false" />
<arg name="num" default="0" />
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />
<!-- Show in Rviz -->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
<!-- mycobot-topics -->
<include file="$(find mycobot_communication)/launch/communication_topic.launch">
<arg name="port" value="$(arg port)" />
<arg name="baud" value="$(arg baud)" />
</include>
<!-- listen and pub the real angles -->
<node name="real_listener" pkg="new_mycobot_320_pi" type="mycobot_320_listen_real_of_topic.py" />
<!-- vision node -->
<node name="opencv_camera" pkg="new_mycobot_320_pi" type="opencv_camera" args="$(arg num)"/>
<node name="detect_marker" pkg="new_mycobot_320_pi" type="mycobot_320_detect_marker.py" />
<node name="following_marker" pkg="new_mycobot_320_pi" type="mycobot_320_following_marker.py" />
</launch>

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mycobot_320/new_mycobot_320_pi/launch/mycobot_320_follow_display.launch Normal file
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<launch>
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/new_mycobot_320_pi.rviz" />
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" >
<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
</node>
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
</launch>

22
mycobot_320/new_mycobot_320_pi/launch/mycobot_320_simple_gui.launch Normal file
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<launch>
<arg name="port" default="/dev/ttyAMA0" />
<arg name="baud" default="115200" />
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/new_mycobot_320_pi.rviz" />
<arg name="gui" default="false" />
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />
<!-- Show in Rviz -->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
<include file="$(find mycobot_communication)/launch/communication_service.launch">
<arg name="port" value="$(arg port)" />
<arg name="baud" value="$(arg baud)" />
</include>
<node name="real_listener" pkg="new_mycobot_320_pi" type="mycobot_320_listen_real.py" />
<node name="simple_gui" pkg="new_mycobot_320_pi" type="mycobot_320_simple_gui.py" />
</launch>

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mycobot_320/new_mycobot_320_pi/launch/mycobot_320_slider.launch Normal file
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<launch>
<arg name="port" default="/dev/ttyAMA0" />
<arg name="baud" default="115200" />
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/new_mycobot_320_pi.rviz" />
<arg name="gui" default="true" />
<!-- <include file="$(find mycobot_280)/launch/slider_control.launch">
<arg name="model" value="$(arg model)" />
<arg name="rvizconfig" value="$(arg rvizconfig)" />
<arg name="gui" value="$(arg gui)" />
</include> -->
<!-- new -->
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />
<node name="joint_state_publisher_gui" pkg="joint_state_publisher_gui" type="joint_state_publisher_gui">
<!-- <param name="use_gui" value="$(arg gui)" /> -->
<!-- <rosparam param="source_list" subst_value="true">["joint_states"]</rosparam> -->
</node>
<!-- Open control script -->
<!-- <node name="control_slider" pkg="mycobot_280" type="slider_control.py">
<param name="port" type="string" value="$(arg port)" />
<param name="baud" type="int" value="$(arg baud)" />
</node> -->
<!-- Show in Rviz -->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
</launch>

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mycobot_320/new_mycobot_320_pi/launch/mycobot_320_teleop_keyboard.launch Normal file
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<launch>
<arg name="port" default="/dev/ttyAMA0" />
<arg name="baud" default="115200" />
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/new_mycobot_320_pi.rviz" />
<arg name="gui" default="false" />
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />
<!-- Show in Rviz -->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
<include file="$(find mycobot_communication)/launch/communication_service.launch">
<arg name="port" value="$(arg port)" />
<arg name="baud" value="$(arg baud)" />
</include>
<node name="real_listener" pkg="new_mycobot_320_pi" type="mycobot_320_listen_real.py" />
</launch>

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mycobot_320/new_mycobot_320_pi/launch/mycobot_320_test.launch Normal file
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<launch>
<arg name="model" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi.urdf"/>
<arg name="rvizconfig" default="$(find new_mycobot_320_pi)/config/new_mycobot_320_pi.rviz" />
<arg name="gui" default="true" />
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />
<node name="joint_state_publisher" pkg="joint_state_publisher" type="joint_state_publisher">
<param name="use_gui" value="$(arg gui)" />
<!-- <rosparam param="source_list" subst_value="true">["joint_states"]</rosparam> -->
</node>
<!-- Show in Rviz ，显示在Rviz-->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
</launch>

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<?xml version="1.0"?>
<package format="2">
<name>new_mycobot_320_pi</name>
<version>0.0.0</version>
<description>The new_mycobot_320_pi package</description>
<!-- One maintainer tag required, multiple allowed, one person per tag -->
<!-- Example: -->
<!-- <maintainer email="jane.doe@example.com">Jane Doe</maintainer> -->
<maintainer email="h@todo.todo">h</maintainer>
<!-- One license tag required, multiple allowed, one license per tag -->
<!-- Commonly used license strings: -->
<!-- BSD, MIT, Boost Software License, GPLv2, GPLv3, LGPLv2.1, LGPLv3 -->
<license>TODO</license>
<!-- Url tags are optional, but multiple are allowed, one per tag -->
<!-- Optional attribute type can be: website, bugtracker, or repository -->
<!-- Example: -->
<!-- <url type="website">http://wiki.ros.org/new_mycobot_320</url> -->
<!-- Author tags are optional, multiple are allowed, one per tag -->
<!-- Authors do not have to be maintainers, but could be -->
<!-- Example: -->
<!-- <author email="jane.doe@example.com">Jane Doe</author> -->
<!-- The *depend tags are used to specify dependencies -->
<!-- Dependencies can be catkin packages or system dependencies -->
<!-- Examples: -->
<!-- Use depend as a shortcut for packages that are both build and exec dependencies -->
<!-- <depend>roscpp</depend> -->
<!-- Note that this is equivalent to the following: -->
<!-- <build_depend>roscpp</build_depend> -->
<!-- <exec_depend>roscpp</exec_depend> -->
<!-- Use build_depend for packages you need at compile time: -->
<!-- <build_depend>message_generation</build_depend> -->
<!-- Use build_export_depend for packages you need in order to build against this package: -->
<!-- <build_export_depend>message_generation</build_export_depend> -->
<!-- Use buildtool_depend for build tool packages: -->
<!-- <buildtool_depend>catkin</buildtool_depend> -->
<!-- Use exec_depend for packages you need at runtime: -->
<!-- <exec_depend>message_runtime</exec_depend> -->
<!-- Use test_depend for packages you need only for testing: -->
<!-- <test_depend>gtest</test_depend> -->
<!-- Use doc_depend for packages you need only for building documentation: -->
<!-- <doc_depend>doxygen</doc_depend> -->
<buildtool_depend>catkin</buildtool_depend>
<!-- <build_depend>roscpp</build_depend>
<build_depend>rospy</build_depend> -->
<build_depend>std_msgs</build_depend>
<!-- <build_export_depend>roscpp</build_export_depend>
<build_export_depend>rospy</build_export_depend>
<build_export_depend>std_msgs</build_export_depend>
<exec_depend>roscpp</exec_depend>
<exec_depend>rospy</exec_depend> -->
<exec_depend>std_msgs</exec_depend>
<build_depend>mycobot_communication</build_depend>
<build_depend>mycobot_description</build_depend>
<build_export_depend>mycobot_communication</build_export_depend>
<build_export_depend>mycobot_description</build_export_depend>
<exec_depend>mycobot_communication</exec_depend>
<exec_depend>mycobot_description</exec_depend>
<exec_depend>actionlib</exec_depend>
<build_depend>actionlib</build_depend>
<!-- The export tag contains other, unspecified, tags -->
<export>
<!-- Other tools can request additional information be placed here -->
</export>
</package>

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mycobot_320/new_mycobot_320_pi/scripts/.gitkeep Normal file
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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_detect_marker.py Executable file
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import rospy
import cv2 as cv
import numpy as np
from cv_bridge import CvBridge, CvBridgeError
from sensor_msgs.msg import Image
import tf
from tf.broadcaster import TransformBroadcaster
import tf_conversions
from mycobot_communication.srv import (
GetCoords,
SetCoords,
GetAngles,
SetAngles,
GripperStatus,
)
class ImageConverter:
def __init__(self):
self.br = TransformBroadcaster()
self.bridge = CvBridge()
self.aruco_dict = cv.aruco.Dictionary_get(cv.aruco.DICT_6X6_250)
self.aruo_params = cv.aruco.DetectorParameters_create()
calibrationParams = cv.FileStorage(
"calibrationFileName.xml", cv.FILE_STORAGE_READ
)
self.dist_coeffs = calibrationParams.getNode("distCoeffs").mat()
self.camera_matrix = None
# subscriber, listen wether has img come in.
self.image_sub = rospy.Subscriber("/camera/image", Image, self.callback)
def callback(self, data):
"""Callback function.
Process image with OpenCV, detect Mark to get the pose. Then acccording the
pose to transforming.
"""
try:
# trans `rgb` to `gbr` for opencv.
cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print(e)
size = cv_image.shape
focal_length = size[1]
center = [size[1] / 2, size[0] / 2]
if self.camera_matrix is None:
# calc the camera matrix, if don't have.
self.camera_matrix = np.array(
[
[focal_length, 0, center[0]],
[0, focal_length, center[1]],
[0, 0, 1],
],
dtype=np.float32,
)
gray = cv.cvtColor(cv_image, cv.COLOR_BGR2GRAY)
# detect aruco marker.
ret = cv.aruco.detectMarkers(gray, self.aruco_dict, parameters=self.aruo_params)
corners, ids = ret[0], ret[1]
# process marker data.
if len(corners) > 0:
if ids is not None:
# print('corners:', corners, 'ids:', ids)
# detect marker pose.
# argument:
# marker corners
# marker size (meter)
ret = cv.aruco.estimatePoseSingleMarkers(
corners, 0.05, self.camera_matrix, self.dist_coeffs
)
(rvec, tvec) = (ret[0], ret[1])
(rvec - tvec).any()
print("rvec:", rvec, "tvec:", tvec)
# just select first one detected marker.
for i in range(rvec.shape[0]):
cv.aruco.drawDetectedMarkers(cv_image, corners)
cv.aruco.drawAxis(
cv_image,
self.camera_matrix,
self.dist_coeffs,
rvec[i, :, :],
tvec[i, :, :],
0.03,
)
xyz = tvec[0, 0, :]
xyz = [xyz[0] - 0.045, xyz[1], xyz[2] - 0.03]
# get quaternion for ros.
euler = rvec[0, 0, :]
tf_change = tf.transformations.quaternion_from_euler(
euler[0], euler[1], euler[2]
)
print("tf_change:", tf_change)
# trans pose according [joint1]
self.br.sendTransform(
xyz, tf_change, rospy.Time.now(), "basic_shapes", "joint6_flange"
)
# [x, y, z, -172, 3, -46.8]
cv.imshow("Image", cv_image)
cv.waitKey(3)
try:
pass
except CvBridgeError as e:
print(e)
if __name__ == "__main__":
try:
rospy.init_node("detect_marker")
rospy.loginfo("Starting cv_bridge_test node")
ImageConverter()
rospy.spin()
except KeyboardInterrupt:
print("Shutting down cv_bridge_test node.")
cv.destroyAllWindows()

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_follow_and_pump.py Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import rospy
from visualization_msgs.msg import Marker
import time
import os
# 与 mycobot 通信的消息类型
from mycobot_communication.msg import MycobotSetAngles, MycobotSetCoords, MycobotPumpStatus
rospy.init_node("gipper_subscriber", anonymous=True)
# 控制 mycobot 的 topic，依次是角度、坐标、夹爪
angle_pub = rospy.Publisher("mycobot/angles_goal",
MycobotSetAngles, queue_size=5)
coord_pub = rospy.Publisher("mycobot/coords_goal",
MycobotSetCoords, queue_size=5)
# Judging equipment: ttyUSB* is M5；ttyACM* is wio
robot = os.popen("ls /dev/ttyUSB*").readline()
if "dev" in robot:
Pin = [2, 5]
else:
Pin = [20, 21]
pump_pub = rospy.Publisher("mycobot/pump_status",
MycobotPumpStatus, queue_size=5)
# 实例化消息对象
angles = MycobotSetAngles()
coords = MycobotSetCoords()
pump = MycobotPumpStatus()
# 与 mycobot 真实位置的偏差值
x_offset = -20
y_offset = 20
z_offset = 110
# 通过该变量限制，抓取行为只做一次
flag = False
# 为了后面比较二维码是否移动
temp_x = temp_y = temp_z = 0.0
temp_time = time.time()
def pub_coords(x, y, z, rx=-150, ry=10, rz=-90, sp=70, m=2):
"""发布坐标"""
coords.x = x
coords.y = y
coords.z = z
coords.rx = rx
coords.ry = ry
coords.rz = rz
coords.speed = 70
coords.model = m
# print(coords)
coord_pub.publish(coords)
def pub_angles(a, b, c, d, e, f, sp):
"""发布角度"""
angles.joint_1 = float(a)
angles.joint_2 = float(b)
angles.joint_3 = float(c)
angles.joint_4 = float(d)
angles.joint_5 = float(e)
angles.joint_6 = float(f)
angles.speed = sp
angle_pub.publish(angles)
def pub_pump(flag, Pin):
"""发布夹爪状态"""
pump.Status = flag
pump.Pin1 = Pin[0]
pump.Pin2 = Pin[1]
pump_pub.publish(pump)
def target_is_moving(x, y, z):
"""判断目标是否移动"""
count = 0
for o, n in zip((x, y, z), (temp_x, temp_y, temp_z)):
print(o, n)
if abs(o - n) < 2:
count += 1
print(count)
if count == 3:
return False
return True
def grippercallback(data):
"""回调函数"""
global flag, temp_x, temp_y, temp_z
# rospy.loginfo('gripper_subscriber get date :%s', data)
if flag:
return
# 解析出坐标值
# pump length: 88mm
x = float(format(data.pose.position.x * 1000, ".2f"))
y = float(format(data.pose.position.y * 1000, ".2f"))
z = float(format(data.pose.position.z * 1000, ".2f"))
# 当运行时间小于 30s，或目标位置还在改变时，进行追踪行为
if (
time.time() - temp_time < 30
or (temp_x == temp_y == temp_z == 0.0)
or target_is_moving(x - x_offset, y - y_offset, z)
):
x -= x_offset
y -= y_offset
pub_coords(x - 20, y, 280)
time.sleep(0.1)
temp_x, temp_y, temp_z = x, y, z
return
else: # 表示目标处于静止状态，可以尝试抓取
print(x, y, z)
# detect heigth + pump height + limit height + offset
x += x_offset
y += y_offset
z = z + 88 + z_offset
pub_coords(x, y, z)
time.sleep(2.5)
# down
for i in range(1, 17):
pub_coords(x, y, z - i * 5, rx=-160, sp=10)
time.sleep(0.1)
time.sleep(2)
pub_pump(True, Pin)
# pump on
pub_coords(x, y, z + 20, -165)
time.sleep(1.5)
pub_angles(0, 30, -50, -40, 0, 0, 50)
time.sleep(1.5)
put_z = 140
pub_coords(39.4, -174.7, put_z, -177.13, -4.13, -152.59, 70, 2)
time.sleep(1.5)
for i in range(1, 8):
pub_coords(39.4, -174.7, put_z - i * 5, -
177.13, -4.13, -152.59, 15, 2)
time.sleep(0.1)
pub_pump(False, Pin)
time.sleep(0.5)
pub_angles(0, 30, -50, -40, 0, 0, 50)
time.sleep(1.5)
# finally
flag = True
def main():
for _ in range(10):
# pub_coords(150, 20, 220, -175, 0, -90, 70, 2)
pub_angles(0, 30, -50, -40, 0, 0, 50)
# pub_angles(random.randint(-30, 30), random.randint(-30, 30), random.randint(-30, 30), random.randint(-30, 30), random.randint(-30, 30), random.randint(-30, 30), 70)
time.sleep(0.5)
pub_pump(False, Pin)
# time.sleep(2.5)
# mark 信息的订阅者
rospy.Subscriber("visualization_marker", Marker,
grippercallback, queue_size=1)
print("gripper test")
rospy.spin()
if __name__ == "__main__":
main()

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_follow_display.py Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
from cgi import print_environ
import time
import rospy
from sensor_msgs.msg import JointState
from std_msgs.msg import Header
from visualization_msgs.msg import Marker
from pymycobot.mycobot import MyCobot
def talker():
rospy.init_node("display", anonymous=True)
print("Try connect real mycobot...")
port = rospy.get_param("~port", "/dev/ttyAMA0")
baud = rospy.get_param("~baud", 115200)
print("port: {}, baud: {}\n".format(port, baud))
try:
mycobot = MyCobot(port, baud)
except Exception as e:
print(e)
print(
"""\
\rTry connect mycobot failed!
\rPlease check wether connected with mycobot.
\rPlease chckt wether the port or baud is right.
"""
)
exit(1)
mycobot.release_all_servos()
time.sleep(0.1)
print("Rlease all servos over.\n")
pub = rospy.Publisher("joint_states", JointState, queue_size=10)
pub_marker = rospy.Publisher("visualization_marker", Marker, queue_size=10)
rate = rospy.Rate(30) # 30hz
# pub joint state
joint_state_send = JointState()
joint_state_send.header = Header()
joint_state_send.name = [
"joint2_to_joint1",
"joint3_to_joint2",
"joint4_to_joint3",
"joint5_to_joint4",
"joint6_to_joint5",
"joint6output_to_joint6",
]
joint_state_send.velocity = [0]
joint_state_send.effort = []
marker_ = Marker()
marker_.header.frame_id = "/joint1"
marker_.ns = "my_namespace"
print("publishing ...")
while not rospy.is_shutdown():
joint_state_send.header.stamp = rospy.Time.now()
angles = mycobot.get_radians()
data_list = []
for index, value in enumerate(angles):
data_list.append(value)
# rospy.loginfo('{}'.format(data_list))
joint_state_send.position = data_list
pub.publish(joint_state_send)
coords = mycobot.get_coords()
# marker
marker_.header.stamp = rospy.Time.now()
marker_.type = marker_.SPHERE
marker_.action = marker_.ADD
marker_.scale.x = 0.04
marker_.scale.y = 0.04
marker_.scale.z = 0.04
# marker position initial
if not coords:
coords = [0, 0, 0, 0, 0, 0]
rospy.loginfo("error [101]: can not get coord values")
marker_.pose.position.x = coords[1] / 1000 * -1
marker_.pose.position.y = coords[0] / 1000
marker_.pose.position.z = coords[2] / 1000
marker_.color.a = 1.0
marker_.color.g = 1.0
pub_marker.publish(marker_)
rate.sleep()
if __name__ == "__main__":
try:
talker()
except rospy.ROSInterruptException:
pass

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_following_marker.py Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import time
import rospy
from sensor_msgs.msg import JointState
from std_msgs.msg import Header
from visualization_msgs.msg import Marker
import tf
def talker():
rospy.init_node("following_marker", anonymous=True)
pub_marker = rospy.Publisher("visualization_marker", Marker, queue_size=10)
rate = rospy.Rate(20)
listener = tf.TransformListener()
marker_ = Marker()
marker_.header.frame_id = "/joint1"
marker_.ns = "basic_cube"
print("publishing ...")
while not rospy.is_shutdown():
now = rospy.Time.now() - rospy.Duration(0.1)
try:
trans, rot = listener.lookupTransform("joint1", "basic_shapes", now)
except Exception as e:
print(e)
continue
print(type(trans), trans)
print(type(rot), rot)
# marker
marker_.header.stamp = now
marker_.type = marker_.CUBE
marker_.action = marker_.ADD
marker_.scale.x = 0.04
marker_.scale.y = 0.04
marker_.scale.z = 0.04
# marker position initial
marker_.pose.position.x = trans[0]
marker_.pose.position.y = trans[1]
marker_.pose.position.z = trans[2]
marker_.pose.orientation.x = rot[0]
marker_.pose.orientation.y = rot[1]
marker_.pose.orientation.z = rot[2]
marker_.pose.orientation.w = rot[3]
marker_.color.a = 1.0
marker_.color.g = 1.0
pub_marker.publish(marker_)
rate.sleep()
if __name__ == "__main__":
try:
talker()
except rospy.ROSInterruptException:
pass

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_listen_real.py Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
# license removed for brevity
import time
import math
import rospy
from sensor_msgs.msg import JointState
from std_msgs.msg import Header
from mycobot_communication.srv import GetAngles
def talker():
rospy.loginfo("start ...")
rospy.init_node("real_listener", anonymous=True)
pub = rospy.Publisher("joint_states", JointState, queue_size=10)
rate = rospy.Rate(30) # 30hz
# pub joint state
joint_state_send = JointState()
joint_state_send.header = Header()
joint_state_send.name = [
"joint2_to_joint1",
"joint3_to_joint2",
"joint4_to_joint3",
"joint5_to_joint4",
"joint6_to_joint5",
"joint6output_to_joint6",
]
joint_state_send.velocity = [0]
joint_state_send.effort = []
# waiting util server `get_joint_angles` enable.
rospy.loginfo("wait service")
rospy.wait_for_service("get_joint_angles")
func = rospy.ServiceProxy("get_joint_angles", GetAngles)
rospy.loginfo("start loop ...")
while not rospy.is_shutdown():
# get real angles from server.
res = func()
if res.joint_1 == res.joint_2 == res.joint_3 == 0.0:
continue
radians_list = [
res.joint_1 * (math.pi / 180),
res.joint_2 * (math.pi / 180),
res.joint_3 * (math.pi / 180),
res.joint_4 * (math.pi / 180),
res.joint_5 * (math.pi / 180),
res.joint_6 * (math.pi / 180),
]
rospy.loginfo("res: {}".format(radians_list))
# publish angles.
joint_state_send.header.stamp = rospy.Time.now()
joint_state_send.position = radians_list
pub.publish(joint_state_send)
rate.sleep()
if __name__ == "__main__":
try:
talker()
except rospy.ROSInterruptException:
pass

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_listen_real_of_topic.py Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import math
import rospy
from sensor_msgs.msg import JointState
from std_msgs.msg import Header
from mycobot_communication.msg import MycobotAngles
class Listener(object):
def __init__(self):
super(Listener, self).__init__()
rospy.loginfo("start ...")
rospy.init_node("real_listener_1", anonymous=True)
# init publisher.
self.pub = rospy.Publisher("joint_states", JointState, queue_size=10)
# init subscriber.
self.sub = rospy.Subscriber("mycobot/angles_real", MycobotAngles, self.callback)
rospy.spin()
def callback(self, data):
"""`mycobot/angles_real` subscriber callback method.
Args:
data (MycobotAngles): callback argument.
"""
# ini publisher object.
joint_state_send = JointState()
joint_state_send.header = Header()
joint_state_send.name = [
"joint2_to_joint1",
"joint3_to_joint2",
"joint4_to_joint3",
"joint5_to_joint4",
"joint6_to_joint5",
"joint6output_to_joint6",
]
joint_state_send.velocity = [0]
joint_state_send.effort = []
joint_state_send.header.stamp = rospy.Time.now()
# process callback data.
radians_list = [
data.joint_1 * (math.pi / 180),
data.joint_2 * (math.pi / 180),
data.joint_3 * (math.pi / 180),
data.joint_4 * (math.pi / 180),
data.joint_5 * (math.pi / 180),
data.joint_6 * (math.pi / 180),
]
rospy.loginfo("res: {}".format(radians_list))
joint_state_send.position = radians_list
self.pub.publish(joint_state_send)
if __name__ == "__main__":
try:
Listener()
except rospy.ROSInterruptException:
pass

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_simple_gui.py Executable file
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import Tkinter as tk
from mycobot_communication.srv import GetCoords, SetCoords, GetAngles, SetAngles, GripperStatus
import rospy
import time
from rospy import ServiceException
class Window:
def __init__(self, handle):
self.win = handle
self.win.resizable(0, 0) # 固定窗口大小
self.model = 0
self.speed = rospy.get_param("~speed", 50)
# 设置默认速度
self.speed_d = tk.StringVar()
self.speed_d.set(str(self.speed))
# print(self.speed)
self.connect_ser()
# 获取机械臂数据
self.record_coords = [0, 0, 0, 0, 0, 0, self.speed, self.model]
self.res_angles = [0, 0, 0, 0, 0, 0, self.speed, self.model]
self.get_date()
# get screen width and height
self.ws = self.win.winfo_screenwidth() # width of the screen
self.hs = self.win.winfo_screenheight() # height of the screen
# calculate x and y coordinates for the Tk root window
x = (self.ws / 2) - 190
y = (self.hs / 2) - 250
self.win.geometry("430x370+{}+{}".format(x, y))
# 布局
self.set_layout()
# 输入部分
self.need_input()
# 展示部分
self.show_init()
# joint 设置按钮
tk.Button(self.frmLT, text="设置", width=5, command=self.get_joint_input).grid(
row=6, column=1, sticky="w", padx=3, pady=2
)
# coordination 设置按钮
tk.Button(self.frmRT, text="设置", width=5, command=self.get_coord_input).grid(
row=6, column=1, sticky="w", padx=3, pady=2
)
# 夹爪开关按钮
tk.Button(self.frmLB, text="夹爪(开)", command=self.gripper_open, width=5).grid(
row=1, column=0, sticky="w", padx=3, pady=50
)
tk.Button(self.frmLB, text="夹爪(关)", command=self.gripper_close, width=5).grid(
row=1, column=1, sticky="w", padx=3, pady=2
)
def connect_ser(self):
rospy.init_node("simple_gui", anonymous=True, disable_signals=True)
rospy.wait_for_service("get_joint_angles")
rospy.wait_for_service("set_joint_angles")
rospy.wait_for_service("get_joint_coords")
rospy.wait_for_service("set_joint_coords")
rospy.wait_for_service("switch_gripper_status")
try:
self.get_coords = rospy.ServiceProxy("get_joint_coords", GetCoords)
self.set_coords = rospy.ServiceProxy("set_joint_coords", SetCoords)
self.get_angles = rospy.ServiceProxy("get_joint_angles", GetAngles)
self.set_angles = rospy.ServiceProxy("set_joint_angles", SetAngles)
self.switch_gripper = rospy.ServiceProxy(
"switch_gripper_status", GripperStatus
)
except:
print("start error ...")
exit(1)
print("Connect service success.")
def set_layout(self):
self.frmLT = tk.Frame(width=200, height=200)
self.frmLC = tk.Frame(width=200, height=200)
self.frmLB = tk.Frame(width=200, height=200)
self.frmRT = tk.Frame(width=200, height=200)
self.frmLT.grid(row=0, column=0, padx=1, pady=3)
self.frmLC.grid(row=1, column=0, padx=1, pady=3)
self.frmLB.grid(row=1, column=1, padx=2, pady=3)
self.frmRT.grid(row=0, column=1, padx=2, pady=3)
def need_input(self):
# 输入提示
tk.Label(self.frmLT, text="Joint 1 ").grid(row=0)
tk.Label(self.frmLT, text="Joint 2 ").grid(row=1) # 第二行
tk.Label(self.frmLT, text="Joint 3 ").grid(row=2)
tk.Label(self.frmLT, text="Joint 4 ").grid(row=3)
tk.Label(self.frmLT, text="Joint 5 ").grid(row=4)
tk.Label(self.frmLT, text="Joint 6 ").grid(row=5)
tk.Label(self.frmRT, text=" x ").grid(row=0)
tk.Label(self.frmRT, text=" y ").grid(row=1) # 第二行
tk.Label(self.frmRT, text=" z ").grid(row=2)
tk.Label(self.frmRT, text=" rx ").grid(row=3)
tk.Label(self.frmRT, text=" ry ").grid(row=4)
tk.Label(self.frmRT, text=" rz ").grid(row=5)
# 设置输入框的默认值
self.j1_default = tk.StringVar()
self.j1_default.set(self.res_angles[0])
self.j2_default = tk.StringVar()
self.j2_default.set(self.res_angles[1])
self.j3_default = tk.StringVar()
self.j3_default.set(self.res_angles[2])
self.j4_default = tk.StringVar()
self.j4_default.set(self.res_angles[3])
self.j5_default = tk.StringVar()
self.j5_default.set(self.res_angles[4])
self.j6_default = tk.StringVar()
self.j6_default.set(self.res_angles[5])
self.x_default = tk.StringVar()
self.x_default.set(self.record_coords[0])
self.y_default = tk.StringVar()
self.y_default.set(self.record_coords[1])
self.z_default = tk.StringVar()
self.z_default.set(self.record_coords[2])
self.rx_default = tk.StringVar()
self.rx_default.set(self.record_coords[3])
self.ry_default = tk.StringVar()
self.ry_default.set(self.record_coords[4])
self.rz_default = tk.StringVar()
self.rz_default.set(self.record_coords[5])
# joint 输入框
self.J_1 = tk.Entry(self.frmLT, textvariable=self.j1_default)
self.J_1.grid(row=0, column=1, pady=3)
self.J_2 = tk.Entry(self.frmLT, textvariable=self.j2_default)
self.J_2.grid(row=1, column=1, pady=3)
self.J_3 = tk.Entry(self.frmLT, textvariable=self.j3_default)
self.J_3.grid(row=2, column=1, pady=3)
self.J_4 = tk.Entry(self.frmLT, textvariable=self.j4_default)
self.J_4.grid(row=3, column=1, pady=3)
self.J_5 = tk.Entry(self.frmLT, textvariable=self.j5_default)
self.J_5.grid(row=4, column=1, pady=3)
self.J_6 = tk.Entry(self.frmLT, textvariable=self.j6_default)
self.J_6.grid(row=5, column=1, pady=3)
# coord 输入框
self.x = tk.Entry(self.frmRT, textvariable=self.x_default)
self.x.grid(row=0, column=1, pady=3, padx=0)
self.y = tk.Entry(self.frmRT, textvariable=self.y_default)
self.y.grid(row=1, column=1, pady=3)
self.z = tk.Entry(self.frmRT, textvariable=self.z_default)
self.z.grid(row=2, column=1, pady=3)
self.rx = tk.Entry(self.frmRT, textvariable=self.rx_default)
self.rx.grid(row=3, column=1, pady=3)
self.ry = tk.Entry(self.frmRT, textvariable=self.ry_default)
self.ry.grid(row=4, column=1, pady=3)
self.rz = tk.Entry(self.frmRT, textvariable=self.rz_default)
self.rz.grid(row=5, column=1, pady=3)
# 所有输入框，用于拿输入的数据
self.all_j = [self.J_1, self.J_2, self.J_3, self.J_4, self.J_5, self.J_6]
self.all_c = [self.x, self.y, self.z, self.rx, self.ry, self.rz]
# 速度输入框
tk.Label(
self.frmLB,
text="speed",
).grid(row=0, column=0)
self.get_speed = tk.Entry(self.frmLB, textvariable=self.speed_d, width=10)
self.get_speed.grid(row=0, column=1)
def show_init(self):
# 显示
tk.Label(self.frmLC, text="Joint 1 ").grid(row=0)
tk.Label(self.frmLC, text="Joint 2 ").grid(row=1) # 第二行
tk.Label(self.frmLC, text="Joint 3 ").grid(row=2)
tk.Label(self.frmLC, text="Joint 4 ").grid(row=3)
tk.Label(self.frmLC, text="Joint 5 ").grid(row=4)
tk.Label(self.frmLC, text="Joint 6 ").grid(row=5)
# get数据
# ，展示出来
self.cont_1 = tk.StringVar(self.frmLC)
self.cont_1.set(str(self.res_angles[0]) + "°")
self.cont_2 = tk.StringVar(self.frmLC)
self.cont_2.set(str(self.res_angles[1]) + "°")
self.cont_3 = tk.StringVar(self.frmLC)
self.cont_3.set(str(self.res_angles[2]) + "°")
self.cont_4 = tk.StringVar(self.frmLC)
self.cont_4.set(str(self.res_angles[3]) + "°")
self.cont_5 = tk.StringVar(self.frmLC)
self.cont_5.set(str(self.res_angles[4]) + "°")
self.cont_6 = tk.StringVar(self.frmLC)
self.cont_6.set(str(self.res_angles[5]) + "°")
self.cont_all = [
self.cont_1,
self.cont_2,
self.cont_3,
self.cont_4,
self.cont_5,
self.cont_6,
self.speed,
self.model,
]
self.show_j1 = tk.Label(
self.frmLC,
textvariable=self.cont_1,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=0, column=1, padx=0, pady=5)
self.show_j2 = tk.Label(
self.frmLC,
textvariable=self.cont_2,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=1, column=1, padx=0, pady=5)
self.show_j3 = tk.Label(
self.frmLC,
textvariable=self.cont_3,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=2, column=1, padx=0, pady=5)
self.show_j4 = tk.Label(
self.frmLC,
textvariable=self.cont_4,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=3, column=1, padx=0, pady=5)
self.show_j5 = tk.Label(
self.frmLC,
textvariable=self.cont_5,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=4, column=1, padx=0, pady=5)
self.show_j6 = tk.Label(
self.frmLC,
textvariable=self.cont_6,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=5, column=1, padx=5, pady=5)
self.all_jo = [
self.show_j1,
self.show_j2,
self.show_j3,
self.show_j4,
self.show_j5,
self.show_j6,
]
# 显示
tk.Label(self.frmLC, text=" x ").grid(row=0, column=3)
tk.Label(self.frmLC, text=" y ").grid(row=1, column=3) # 第二行
tk.Label(self.frmLC, text=" z ").grid(row=2, column=3)
tk.Label(self.frmLC, text=" rx ").grid(row=3, column=3)
tk.Label(self.frmLC, text=" ry ").grid(row=4, column=3)
tk.Label(self.frmLC, text=" rz ").grid(row=5, column=3)
self.coord_x = tk.StringVar()
self.coord_x.set(str(self.record_coords[0]))
self.coord_y = tk.StringVar()
self.coord_y.set(str(self.record_coords[1]))
self.coord_z = tk.StringVar()
self.coord_z.set(str(self.record_coords[2]))
self.coord_rx = tk.StringVar()
self.coord_rx.set(str(self.record_coords[3]))
self.coord_ry = tk.StringVar()
self.coord_ry.set(str(self.record_coords[4]))
self.coord_rz = tk.StringVar()
self.coord_rz.set(str(self.record_coords[5]))
self.coord_all = [
self.coord_x,
self.coord_y,
self.coord_z,
self.coord_rx,
self.coord_ry,
self.coord_rz,
self.speed,
self.model,
]
self.show_x = tk.Label(
self.frmLC,
textvariable=self.coord_x,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=0, column=4, padx=5, pady=5)
self.show_y = tk.Label(
self.frmLC,
textvariable=self.coord_y,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=1, column=4, padx=5, pady=5)
self.show_z = tk.Label(
self.frmLC,
textvariable=self.coord_z,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=2, column=4, padx=5, pady=5)
self.show_rx = tk.Label(
self.frmLC,
textvariable=self.coord_rx,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=3, column=4, padx=5, pady=5)
self.show_ry = tk.Label(
self.frmLC,
textvariable=self.coord_ry,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=4, column=4, padx=5, pady=5)
self.show_rz = tk.Label(
self.frmLC,
textvariable=self.coord_rz,
font=("Arial", 9),
width=7,
height=1,
bg="white",
).grid(row=5, column=4, padx=5, pady=5)
# mm 单位展示
self.unit = tk.StringVar()
self.unit.set("mm")
for i in range(6):
tk.Label(self.frmLC, textvariable=self.unit, font=("Arial", 9)).grid(
row=i, column=5
)
def gripper_open(self):
try:
self.switch_gripper(True)
except ServiceException:
# 可能由于该方法没有返回值，服务抛出无法处理的错误
pass
def gripper_close(self):
try:
self.switch_gripper(False)
except ServiceException:
pass
def get_coord_input(self):
# 获取 coord 输入的数据，发送给机械臂
c_value = []
for i in self.all_c:
# print(type(i.get()))
c_value.append(float(i.get()))
self.speed = (
int(float(self.get_speed.get())) if self.get_speed.get() else self.speed
)
c_value.append(self.speed)
c_value.append(self.model)
# print(c_value)
try:
self.set_coords(*c_value)
except ServiceException:
pass
self.show_j_date(c_value[:-2], "coord")
def get_joint_input(self):
# 获取joint输入的数据，发送给机械臂
j_value = []
for i in self.all_j:
# print(type(i.get()))
j_value.append(float(i.get()))
self.speed = (
int(float(self.get_speed.get())) if self.get_speed.get() else self.speed
)
j_value.append(self.speed)
try:
self.set_angles(*j_value)
except ServiceException:
pass
self.show_j_date(j_value[:-1])
# return j_value,c_value,speed
def get_date(self):
# 拿机械臂的数据，用于展示
t = time.time()
while time.time() - t < 2:
self.res = self.get_coords()
if self.res.x > 1:
break
time.sleep(0.1)
t = time.time()
while time.time() - t < 2:
self.angles = self.get_angles()
if self.angles.joint_1 > 1:
break
time.sleep(0.1)
# print(self.angles.joint_1)
self.record_coords = [
round(self.res.x, 2),
round(self.res.y, 2),
round(self.res.z, 2),
round(self.res.rx, 2),
round(self.res.ry, 2),
round(self.res.rz, 2),
self.speed,
self.model,
]
self.res_angles = [
round(self.angles.joint_1, 2),
round(self.angles.joint_2, 2),
round(self.angles.joint_3, 2),
round(self.angles.joint_4, 2),
round(self.angles.joint_5, 2),
round(self.angles.joint_6, 2),
]
# print('coord:',self.record_coords)
# print('angles:',self.res_angles)
# def send_input(self,dates):
def show_j_date(self, date, way=""):
# 展示数据
if way == "coord":
for i, j in zip(date, self.coord_all):
# print(i)
j.set(str(i))
else:
for i, j in zip(date, self.cont_all):
j.set(str(i) + "°")
def run(self):
while True:
try:
self.win.update()
time.sleep(0.001)
except tk.TclError as e:
if "application has been destroyed" in str(e):
break
else:
raise
def main():
window = tk.Tk()
window.title("mycobot ros GUI")
Window(window).run()
if __name__ == "__main__":
main()

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mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_slider.py Executable file
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""[summary]
This file obtains the joint angle of the manipulator in ROS,
and then sends it directly to the real manipulator using `pymycobot` API.
This file is [slider_control.launch] related script.
Passable parameters:
port: serial prot string. Defaults is '/dev/ttyAMA0'
baud: serial prot baudrate. Defaults is 1000000.
"""
import rospy
from sensor_msgs.msg import JointState
from pymycobot.mycobot import MyCobot
mc = None
def callback(data):
# rospy.loginfo(rospy.get_caller_id() + "%s", data.position)
print(data.position)
data_list = []
for index, value in enumerate(data.position):
data_list.append(value)
mc.send_radians(data_list, 80)
# time.sleep(0.5)
def listener():
global mc
rospy.init_node("control_slider", anonymous=True)
rospy.Subscriber("joint_states", JointState, callback)
port = rospy.get_param("~port", "/dev/ttyAMA0")
baud = rospy.get_param("~baud", 115200)
print(port, baud)
mc = MyCobot(port, baud)
# spin() simply keeps python from exiting until this node is stopped
print("spin ...")
rospy.spin()
if __name__ == "__main__":
listener()

175
mycobot_320/new_mycobot_320_pi/scripts/mycobot_320_teleop_keyboard.py Executable file
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
from mycobot_communication.srv import GetCoords, SetCoords, GetAngles, SetAngles, GripperStatus
import rospy
import sys
import select
import termios
import tty
import time
import roslib
msg = """\
Mycobot Teleop Keyboard Controller
---------------------------
Movimg options(control coordinations [x,y,z,rx,ry,rz]):
w(x+)
a(y-) s(x-) d(y+)
z(z-) x(z+)
u(rx+) i(ry+) o(rz+)
j(rx-) k(ry-) l(rz-)
Gripper control:
g - open
h - close
Other:
1 - Go to init pose
2 - Go to home pose
3 - Resave home pose
q - Quit
"""
def vels(speed, turn):
return "currently:\tspeed: %s\tchange percent: %s " % (speed, turn)
class Raw(object):
def __init__(self, stream):
self.stream = stream
self.fd = self.stream.fileno()
def __enter__(self):
self.original_stty = termios.tcgetattr(self.stream)
tty.setcbreak(self.stream)
def __exit__(self, type, value, traceback):
termios.tcsetattr(self.stream, termios.TCSANOW, self.original_stty)
def teleop_keyboard():
rospy.init_node("teleop_keyboard")
model = 0
speed = rospy.get_param("~speed", 50)
change_percent = rospy.get_param("~change_percent", 5)
change_angle = 180 * change_percent / 100
change_len = 250 * change_percent / 100
rospy.wait_for_service("get_joint_angles")
rospy.wait_for_service("set_joint_angles")
rospy.wait_for_service("get_joint_coords")
rospy.wait_for_service("set_joint_coords")
rospy.wait_for_service("switch_gripper_status")
print("service ready.")
try:
get_coords = rospy.ServiceProxy("get_joint_coords", GetCoords)
set_coords = rospy.ServiceProxy("set_joint_coords", SetCoords)
get_angles = rospy.ServiceProxy("get_joint_angles", GetAngles)
set_angles = rospy.ServiceProxy("set_joint_angles", SetAngles)
switch_gripper = rospy.ServiceProxy(
"switch_gripper_status", GripperStatus)
except:
print("start error ...")
exit(1)
init_pose = [0, 0, 0, 0, 0, 0, speed]
home_pose = [0, 8, -127, 40, 0, 0, speed]
# rsp = set_angles(*init_pose)
while True:
res = get_coords()
if res.x > 1:
print("joint1's angle : "+str(res.x)+"is not > 1,please calibrate the joint1's angle")
break
time.sleep(0.1)
record_coords = [res.x, res.y, res.z, res.rx, res.ry, res.rz, speed, model]
print(record_coords)
try:
print(msg)
print(vels(speed, change_percent))
while 1:
try:
# print("\r current coords: %s" % record_coords, end="")
with Raw(sys.stdin):
key = sys.stdin.read(1)
if key == "q":
break
elif key in ["w", "W"]:
record_coords[0] += change_len
set_coords(*record_coords)
elif key in ["s", "S"]:
record_coords[0] -= change_len
set_coords(*record_coords)
elif key in ["a", "A"]:
record_coords[1] -= change_len
set_coords(*record_coords)
elif key in ["d", "D"]:
record_coords[1] += change_len
set_coords(*record_coords)
elif key in ["z", "Z"]:
record_coords[2] -= change_len
set_coords(*record_coords)
elif key in ["x", "X"]:
record_coords[2] += change_len
set_coords(*record_coords)
elif key in ["u", "U"]:
record_coords[3] += change_angle
set_coords(*record_coords)
elif key in ["j", "J"]:
record_coords[3] -= change_angle
set_coords(*record_coords)
elif key in ["i", "I"]:
record_coords[4] += change_angle
set_coords(*record_coords)
elif key in ["k", "K"]:
record_coords[4] -= change_angle
set_coords(*record_coords)
elif key in ["o", "O"]:
record_coords[5] += change_angle
set_coords(*record_coords)
elif key in ["l", "L"]:
record_coords[5] -= change_angle
set_coords(*record_coords)
elif key in ["g", "G"]:
switch_gripper(True)
elif key in ["h", "H"]:
switch_gripper(False)
elif key == "1":
rsp = set_angles(*init_pose)
elif key in "2":
rsp = set_angles(*home_pose)
elif key in "3":
rep = get_angles()
home_pose[0] = rep.joint_1
home_pose[1] = rep.joint_2
home_pose[2] = rep.joint_3
home_pose[3] = rep.joint_4
home_pose[5] = rep.joint_5
else:
continue
except Exception as e:
# print(e)
continue
except Exception as e:
print(e)
if __name__ == "__main__":
try:
teleop_keyboard()
except rospy.ROSInterruptException:
pass

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mycobot_320/new_mycobot_320_pi/scripts/test.py Executable file
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# -*- coding: utf-8 -*-
from pymycobot.mycobot import MyCobot
from pymycobot.genre import Angle
from pymycobot import PI_PORT, PI_BAUD # 当使用树莓派版本的mycobot时，可以引用这两个变量进行MyCobot初始化
import time
mc = MyCobot("/dev/ttyUSB0", 115200)
# 通过传递角度参数，让机械臂每个关节移动到对应[0, 0, 0, 0, 0, 0]的位置
mc.send_angles([0, 0, 0, 0, 0, 0], 50)
# 设置等待时间，确保机械臂已经到达指定位置
time.sleep(2.5)
# 让关节1移动到90这个位置
# mc.send_angle(Angle.J1.value, 90, 50)

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mycobot_320/new_mycobot_320_pi/src/camera_display.cpp Normal file
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#include <ros/ros.h>
#include <image_transport/image_transport.h>
#include <opencv2/highgui/highgui.hpp>
#include <cv_bridge/cv_bridge.h>
void imageCallback(const sensor_msgs::ImageConstPtr &msg)
{
try
{
cv::imshow("view", cv_bridge::toCvShare(msg, "bgr8")->image);
cv::waitKey(30);
}
catch (cv_bridge::Exception &e)
{
ROS_ERROR("Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str());
}
}
int main(int argc, char **argv)
{
ros::init(argc, argv, "image_listener");
ros::NodeHandle nh;
cv::namedWindow("view");
cv::startWindowThread();
image_transport::ImageTransport it(nh);
image_transport::Subscriber sub = it.subscribe("camera/image", 1, imageCallback);
ros::spin();
cv::destroyWindow("view");
}

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mycobot_320/new_mycobot_320_pi/src/opencv_camera.cpp Normal file
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#include <ros/ros.h>
#include <image_transport/image_transport.h>
#include <opencv2/highgui/highgui.hpp>
#include <cv_bridge/cv_bridge.h>
#include <sstream> // for converting the command line parameter to integer
int main(int argc, char **argv)
{
// Check if video source has been passed as a parameter
if (argv[1] == NULL)
{
ROS_INFO("argv[1]=NULL\n");
return 1;
}
ros::init(argc, argv, "image_publisher"); // Initialize node
ros::NodeHandle nh;
image_transport::ImageTransport it(nh);
image_transport::Publisher pub = it.advertise("camera/image", 1); // Publish topic
ros::Rate loop_rate(200); // refresh Hz.
// Convert the passed as command line parameter index for the video device to an integer
std::istringstream video_sourceCmd(argv[1]);
int video_source;
// Check if it is indeed a number
if (!(video_sourceCmd >> video_source))
{
ROS_INFO("video_sourceCmd is %d\n", video_source);
return 1;
}
cv::VideoCapture cap(video_source);
// Check if video device can be opened with the given index
if (!cap.isOpened())
{
ROS_INFO("can not opencv video device\n");
return 1;
}
cv::Mat frame;
sensor_msgs::ImagePtr msg;
while (nh.ok())
{
cap >> frame;
// cv::imshow("veiwer", frame);
// Check if grabbed frame is actually full with some content
if (!frame.empty())
{
msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", frame).toImageMsg();
pub.publish(msg);
//cv::Wait(1);
}
ros::spinOnce();
loop_rate.sleep();
// if(cv::waitKey(2) >= 0)
// break;
}
}

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mycobot_320/new_mycobot_320_pi_moveit/CMakeLists.txt Normal file
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cmake_minimum_required(VERSION 3.0.2)
project(new_mycobot_320_pi_moveit)
## Compile as C++11, supported in ROS Kinetic and newer
# add_compile_options(-std=c++11)
find_package(catkin REQUIRED)
catkin_package()
install(DIRECTORY launch DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
PATTERN "setup_assistant.launch" EXCLUDE)
install(DIRECTORY config DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION})

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mycobot_320/new_mycobot_320_pi_moveit/LICENSE Normal file
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BSD 2-Clause License
Copyright (c) 2020, Elephant Robotics
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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mycobot_320/new_mycobot_320_pi_moveit/config/chomp_planning.yaml Normal file
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planning_time_limit: 10.0
max_iterations: 200
max_iterations_after_collision_free: 5
smoothness_cost_weight: 0.1
obstacle_cost_weight: 1.0
learning_rate: 0.01
smoothness_cost_velocity: 0.0
smoothness_cost_acceleration: 1.0
smoothness_cost_jerk: 0.0
ridge_factor: 0.01
use_pseudo_inverse: false
pseudo_inverse_ridge_factor: 1e-4
joint_update_limit: 0.1
collision_clearence: 0.2
collision_threshold: 0.07
use_stochastic_descent: true
enable_failure_recovery: true
max_recovery_attempts: 5

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mycobot_320/new_mycobot_320_pi_moveit/config/fake_controllers.yaml Normal file
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controller_list:
- name: fake_arm_group_controller
joints:
- joint2_to_joint1
- joint3_to_joint2
- joint4_to_joint3
- joint5_to_joint4
- joint6_to_joint5
- joint6output_to_joint6

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mycobot_320/new_mycobot_320_pi_moveit/config/firefighter.srdf Normal file
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<?xml version="1.0" ?>
<!--This does not replace URDF, and is not an extension of URDF.
This is a format for representing semantic information about the robot structure.
A URDF file must exist for this robot as well, where the joints and the links that are referenced are defined
-->
<robot name="firefighter">
<!--GROUPS: Representation of a set of joints and links. This can be useful for specifying DOF to plan for, defining arms, end effectors, etc-->
<!--LINKS: When a link is specified, the parent joint of that link (if it exists) is automatically included-->
<!--JOINTS: When a joint is specified, the child link of that joint (which will always exist) is automatically included-->
<!--CHAINS: When a chain is specified, all the links along the chain (including endpoints) are included in the group. Additionally, all the joints that are parents to included links are also included. This means that joints along the chain and the parent joint of the base link are included in the group-->
<!--SUBGROUPS: Groups can also be formed by referencing to already defined group names-->
<group name="arm_group">
<joint name="joint2_to_joint1" />
<joint name="joint3_to_joint2" />
<joint name="joint4_to_joint3" />
<joint name="joint5_to_joint4" />
<joint name="joint6_to_joint5" />
<joint name="joint6output_to_joint6" />
</group>
<!--GROUP STATES: Purpose: Define a named state for a particular group, in terms of joint values. This is useful to define states like 'folded arms'-->
<group_state name="init_pose" group="arm_group">
<joint name="joint2_to_joint1" value="0" />
<joint name="joint3_to_joint2" value="0" />
<joint name="joint4_to_joint3" value="0" />
<joint name="joint5_to_joint4" value="0" />
<joint name="joint6_to_joint5" value="0" />
<joint name="joint6output_to_joint6" value="0" />
</group_state>
<!--DISABLE COLLISIONS: By default it is assumed that any link of the robot could potentially come into collision with any other link in the robot. This tag disables collision checking between a specified pair of links. -->
<disable_collisions link1="base" link2="link1" reason="Adjacent" />
<disable_collisions link1="link1" link2="link2" reason="Adjacent" />
<disable_collisions link1="link1" link2="link4" reason="Never" />
<disable_collisions link1="link2" link2="link3" reason="Adjacent" />
<disable_collisions link1="link3" link2="link4" reason="Adjacent" />
<disable_collisions link1="link4" link2="link5" reason="Adjacent" />
<disable_collisions link1="link4" link2="link6" reason="Never" />
<disable_collisions link1="link5" link2="link6" reason="Adjacent" />
</robot>

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mycobot_320/new_mycobot_320_pi_moveit/config/joint_limits.yaml Normal file
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# joint_limits.yaml allows the dynamics properties specified in the URDF to be overwritten or augmented as needed
# Specific joint properties can be changed with the keys [max_position, min_position, max_velocity, max_acceleration]
# Joint limits can be turned off with [has_velocity_limits, has_acceleration_limits]
joint_limits:
joint2_to_joint1:
has_velocity_limits: false
max_velocity: 0
has_acceleration_limits: false
max_acceleration: 0
joint3_to_joint2:
has_velocity_limits: false
max_velocity: 0
has_acceleration_limits: false
max_acceleration: 0
joint4_to_joint3:
has_velocity_limits: false
max_velocity: 0
has_acceleration_limits: false
max_acceleration: 0
joint5_to_joint4:
has_velocity_limits: false
max_velocity: 0
has_acceleration_limits: false
max_acceleration: 0
joint6_to_joint5:
has_velocity_limits: false
max_velocity: 0
has_acceleration_limits: false
max_acceleration: 0
joint6output_to_joint6:
has_velocity_limits: false
max_velocity: 0
has_acceleration_limits: false
max_acceleration: 0

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mycobot_320/new_mycobot_320_pi_moveit/config/kinematics.yaml Normal file
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arm_group:
kinematics_solver: kdl_kinematics_plugin/KDLKinematicsPlugin
kinematics_solver_search_resolution: 0.005
kinematics_solver_timeout: 0.005
kinematics_solver_attempts: 3

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mycobot_320/new_mycobot_320_pi_moveit/config/ompl_planning.yaml Normal file
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planner_configs:
SBL:
type: geometric::SBL
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
EST:
type: geometric::EST
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0 setup()
goal_bias: 0.05 # When close to goal select goal, with this probability. default: 0.05
LBKPIECE:
type: geometric::LBKPIECE
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
border_fraction: 0.9 # Fraction of time focused on boarder default: 0.9
min_valid_path_fraction: 0.5 # Accept partially valid moves above fraction. default: 0.5
BKPIECE:
type: geometric::BKPIECE
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
border_fraction: 0.9 # Fraction of time focused on boarder default: 0.9
failed_expansion_score_factor: 0.5 # When extending motion fails, scale score by factor. default: 0.5
min_valid_path_fraction: 0.5 # Accept partially valid moves above fraction. default: 0.5
KPIECE:
type: geometric::KPIECE
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability. default: 0.05
border_fraction: 0.9 # Fraction of time focused on boarder default: 0.9 (0.0,1.]
failed_expansion_score_factor: 0.5 # When extending motion fails, scale score by factor. default: 0.5
min_valid_path_fraction: 0.5 # Accept partially valid moves above fraction. default: 0.5
RRT:
type: geometric::RRT
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability? default: 0.05
RRTConnect:
type: geometric::RRTConnect
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
RRTstar:
type: geometric::RRTstar
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability? default: 0.05
delay_collision_checking: 1 # Stop collision checking as soon as C-free parent found. default 1
TRRT:
type: geometric::TRRT
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability? default: 0.05
max_states_failed: 10 # when to start increasing temp. default: 10
temp_change_factor: 2.0 # how much to increase or decrease temp. default: 2.0
min_temperature: 10e-10 # lower limit of temp change. default: 10e-10
init_temperature: 10e-6 # initial temperature. default: 10e-6
frountier_threshold: 0.0 # dist new state to nearest neighbor to disqualify as frontier. default: 0.0 set in setup()
frountierNodeRatio: 0.1 # 1/10, or 1 nonfrontier for every 10 frontier. default: 0.1
k_constant: 0.0 # value used to normalize expresssion. default: 0.0 set in setup()
PRM:
type: geometric::PRM
max_nearest_neighbors: 10 # use k nearest neighbors. default: 10
PRMstar:
type: geometric::PRMstar
FMT:
type: geometric::FMT
num_samples: 1000 # number of states that the planner should sample. default: 1000
radius_multiplier: 1.1 # multiplier used for the nearest neighbors search radius. default: 1.1
nearest_k: 1 # use Knearest strategy. default: 1
cache_cc: 1 # use collision checking cache. default: 1
heuristics: 0 # activate cost to go heuristics. default: 0
extended_fmt: 1 # activate the extended FMT*: adding new samples if planner does not finish successfully. default: 1
BFMT:
type: geometric::BFMT
num_samples: 1000 # number of states that the planner should sample. default: 1000
radius_multiplier: 1.0 # multiplier used for the nearest neighbors search radius. default: 1.0
nearest_k: 1 # use the Knearest strategy. default: 1
balanced: 0 # exploration strategy: balanced true expands one tree every iteration. False will select the tree with lowest maximum cost to go. default: 1
optimality: 1 # termination strategy: optimality true finishes when the best possible path is found. Otherwise, the algorithm will finish when the first feasible path is found. default: 1
heuristics: 1 # activates cost to go heuristics. default: 1
cache_cc: 1 # use the collision checking cache. default: 1
extended_fmt: 1 # Activates the extended FMT*: adding new samples if planner does not finish successfully. default: 1
PDST:
type: geometric::PDST
STRIDE:
type: geometric::STRIDE
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability. default: 0.05
use_projected_distance: 0 # whether nearest neighbors are computed based on distances in a projection of the state rather distances in the state space itself. default: 0
degree: 16 # desired degree of a node in the Geometric Near-neightbor Access Tree (GNAT). default: 16
max_degree: 18 # max degree of a node in the GNAT. default: 12
min_degree: 12 # min degree of a node in the GNAT. default: 12
max_pts_per_leaf: 6 # max points per leaf in the GNAT. default: 6
estimated_dimension: 0.0 # estimated dimension of the free space. default: 0.0
min_valid_path_fraction: 0.2 # Accept partially valid moves above fraction. default: 0.2
BiTRRT:
type: geometric::BiTRRT
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
temp_change_factor: 0.1 # how much to increase or decrease temp. default: 0.1
init_temperature: 100 # initial temperature. default: 100
frountier_threshold: 0.0 # dist new state to nearest neighbor to disqualify as frontier. default: 0.0 set in setup()
frountier_node_ratio: 0.1 # 1/10, or 1 nonfrontier for every 10 frontier. default: 0.1
cost_threshold: 1e300 # the cost threshold. Any motion cost that is not better will not be expanded. default: inf
LBTRRT:
type: geometric::LBTRRT
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability. default: 0.05
epsilon: 0.4 # optimality approximation factor. default: 0.4
BiEST:
type: geometric::BiEST
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
ProjEST:
type: geometric::ProjEST
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
goal_bias: 0.05 # When close to goal select goal, with this probability. default: 0.05
LazyPRM:
type: geometric::LazyPRM
range: 0.0 # Max motion added to tree. ==> maxDistance_ default: 0.0, if 0.0, set on setup()
LazyPRMstar:
type: geometric::LazyPRMstar
SPARS:
type: geometric::SPARS
stretch_factor: 3.0 # roadmap spanner stretch factor. multiplicative upper bound on path quality. It does not make sense to make this parameter more than 3. default: 3.0
sparse_delta_fraction: 0.25 # delta fraction for connection distance. This value represents the visibility range of sparse samples. default: 0.25
dense_delta_fraction: 0.001 # delta fraction for interface detection. default: 0.001
max_failures: 1000 # maximum consecutive failure limit. default: 1000
SPARStwo:
type: geometric::SPARStwo
stretch_factor: 3.0 # roadmap spanner stretch factor. multiplicative upper bound on path quality. It does not make sense to make this parameter more than 3. default: 3.0
sparse_delta_fraction: 0.25 # delta fraction for connection distance. This value represents the visibility range of sparse samples. default: 0.25
dense_delta_fraction: 0.001 # delta fraction for interface detection. default: 0.001
max_failures: 5000 # maximum consecutive failure limit. default: 5000
arm_group:
default_planner_config: None
planner_configs:
- SBL
- EST
- LBKPIECE
- BKPIECE
- KPIECE
- RRT
- RRTConnect
- RRTstar
- TRRT
- PRM
- PRMstar
- FMT
- BFMT
- PDST
- STRIDE
- BiTRRT
- LBTRRT
- BiEST
- ProjEST
- LazyPRM
- LazyPRMstar
- SPARS
- SPARStwo
projection_evaluator: joints(joint2_to_joint1,joint3_to_joint2)
longest_valid_segment_fraction: 0.005

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mycobot_320/new_mycobot_320_pi_moveit/config/ros_controllers.yaml Normal file
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# Simulation settings for using moveit_sim_controllers
moveit_sim_hw_interface:
joint_model_group: arm_group
joint_model_group_pose: init_pose
# Settings for ros_control_boilerplate control loop
generic_hw_control_loop:
loop_hz: 300
cycle_time_error_threshold: 0.01
# Settings for ros_control hardware interface
hardware_interface:
joints:
- joint2_to_joint1
- joint3_to_joint2
- joint4_to_joint3
- joint5_to_joint4
- joint6_to_joint5
- joint6output_to_joint6
sim_control_mode: 1 # 0: position, 1: velocity
# Publish all joint states
# Creates the /joint_states topic necessary in ROS
joint_state_controller:
type: joint_state_controller/JointStateController
publish_rate: 50
controller_list:
[]

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mycobot_320/new_mycobot_320_pi_moveit/config/sensors_3d.yaml Normal file
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# The name of this file shouldn't be changed, or else the Setup Assistant won't detect it
sensors:
- filtered_cloud_topic: filtered_cloud
max_range: 5.0
max_update_rate: 1.0
padding_offset: 0.1
padding_scale: 1.0
point_cloud_topic: /head_mount_kinect/depth_registered/points
point_subsample: 1
sensor_plugin: occupancy_map_monitor/PointCloudOctomapUpdater

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mycobot_320/new_mycobot_320_pi_moveit/launch/chomp_planning_pipeline.launch.xml Normal file
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<launch>
<!-- CHOMP Plugin for MoveIt! -->
<arg name="planning_plugin" value="chomp_interface/CHOMPPlanner" />
<arg name="start_state_max_bounds_error" value="0.1" />
<param name="planning_plugin" value="$(arg planning_plugin)" />
<param name="start_state_max_bounds_error" value="$(arg start_state_max_bounds_error)" />
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/chomp_planning.yaml" />
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/default_warehouse_db.launch Executable file
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<launch>
<arg name="reset" default="false"/>
<!-- If not specified, we'll use a default database location -->
<arg name="moveit_warehouse_database_path" default="$(find new_mycobot_320_pi_moveit)/default_warehouse_mongo_db" />
<!-- Launch the warehouse with the configured database location -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/warehouse.launch">
<arg name="moveit_warehouse_database_path" value="$(arg moveit_warehouse_database_path)" />
</include>
<!-- If we want to reset the database, run this node -->
<node if="$(arg reset)" name="$(anon moveit_default_db_reset)" type="moveit_init_demo_warehouse" pkg="moveit_ros_warehouse" respawn="false" output="screen" />
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/demo.launch Executable file
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<launch>
<!-- By default, we do not start a database (it can be large) -->
<arg name="db" default="false" />
<!-- Allow user to specify database location -->
<arg name="db_path" default="$(find new_mycobot_320_pi_moveit)/default_warehouse_mongo_db" />
<!-- By default, we are not in debug mode -->
<arg name="debug" default="false" />
<!--
By default, hide joint_state_publisher's GUI
MoveIt!'s "demo" mode replaces the real robot driver with the joint_state_publisher.
The latter one maintains and publishes the current joint configuration of the simulated robot.
It also provides a GUI to move the simulated robot around "manually".
This corresponds to moving around the real robot without the use of MoveIt.
-->
<arg name="use_gui" default="false" />
<!-- Load the URDF, SRDF and other .yaml configuration files on the param server -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/planning_context.launch">
<arg name="load_robot_description" value="true"/>
</include>
<!-- If needed, broadcast static tf for robot root -->
<!-- We do not have a robot connected, so publish fake joint states -->
<node name="joint_state_publisher" pkg="joint_state_publisher" type="joint_state_publisher">
<param name="use_gui" value="$(arg use_gui)"/>
<rosparam param="source_list">[move_group/fake_controller_joint_states]</rosparam>
</node>
<!-- Given the published joint states, publish tf for the robot links -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" respawn="true" output="screen" />
<!-- Run the main MoveIt! executable without trajectory execution (we do not have controllers configured by default) -->
<include file="$(find mycobot_320_pi_moveit)/launch/move_group.launch">
<arg name="allow_trajectory_execution" value="true"/>
<arg name="fake_execution" value="true"/>
<arg name="info" value="true"/>
<arg name="debug" value="$(arg debug)"/>
</include>
<!-- Run Rviz and load the default config to see the state of the move_group node -->
<include file="$(find mycobot_320_pi_moveit)/launch/moveit_rviz.launch">
<arg name="config" value="true"/>
<arg name="debug" value="$(arg debug)"/>
</include>
<!-- If database loading was enabled, start mongodb as well -->
<include file="$(find mycobot_320_pi_moveit)/launch/default_warehouse_db.launch" if="$(arg db)">
<arg name="moveit_warehouse_database_path" value="$(arg db_path)"/>
</include>
</launch>

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<launch>
<!-- By default, we do not start a database (it can be large) -->
<arg name="db" default="false" />
<!-- Allow user to specify database location -->
<arg name="db_path" default="$(find new_mycobot_320_pi_moveit)/default_warehouse_mongo_db" />
<!-- By default, we are not in debug mode -->
<arg name="debug" default="false" />
<!--
By default, hide joint_state_publisher's GUI
MoveIt!'s "demo" mode replaces the real robot driver with the joint_state_publisher.
The latter one maintains and publishes the current joint configuration of the simulated robot.
It also provides a GUI to move the simulated robot around "manually".
This corresponds to moving around the real robot without the use of MoveIt.
-->
<arg name="use_gui" default="false" />
<!-- Gazebo specific options -->
<arg name="gazebo_gui" default="true"/>
<arg name="paused" default="false"/>
<!-- By default, use the urdf location provided from the package -->
<arg name="urdf_path" default="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi_moveit.urdf"/>
<!-- launch the gazebo simulator and spawn the robot -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/gazebo.launch" >
<arg name="paused" value="$(arg paused)"/>
<arg name="gazebo_gui" value="$(arg gazebo_gui)"/>
<arg name="urdf_path" value="$(arg urdf_path)"/>
</include>
<!-- Load the URDF, SRDF and other .yaml configuration files on the param server -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/planning_context.launch">
<arg name="load_robot_description" value="false"/>
</include>
<!-- If needed, broadcast static tf for robot root -->
<!-- We do not have a robot connected, so publish fake joint states -->
<node name="joint_state_publisher" pkg="joint_state_publisher" type="joint_state_publisher">
<param name="use_gui" value="$(arg use_gui)"/>
<rosparam param="source_list">[/joint_states]</rosparam>
</node>
<!-- Given the published joint states, publish tf for the robot links -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" respawn="true" output="screen" />
<!-- Run the main MoveIt! executable without trajectory execution (we do not have controllers configured by default) -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/move_group.launch">
<arg name="allow_trajectory_execution" value="true"/>
<arg name="fake_execution" value="false"/>
<arg name="info" value="true"/>
<arg name="debug" value="$(arg debug)"/>
</include>
<!-- Run Rviz and load the default config to see the state of the move_group node -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/moveit_rviz.launch">
<arg name="config" value="true"/>
<arg name="debug" value="$(arg debug)"/>
</include>
<!-- If database loading was enabled, start mongodb as well -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/default_warehouse_db.launch" if="$(arg db)">
<arg name="moveit_warehouse_database_path" value="$(arg db_path)"/>
</include>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/fake_moveit_controller_manager.launch.xml Normal file
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<launch>
<!-- Set the param that trajectory_execution_manager needs to find the controller plugin -->
<param name="moveit_controller_manager" value="moveit_fake_controller_manager/MoveItFakeControllerManager"/>
<!-- The rest of the params are specific to this plugin -->
<rosparam file="$(find new_mycobot_320_pi_moveit)/config/fake_controllers.yaml"/>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/firefighter_moveit_controller_manager.launch.xml Normal file
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<launch>
<!-- loads moveit_controller_manager on the parameter server which is taken as argument
if no argument is passed, moveit_simple_controller_manager will be set -->
<arg name="moveit_controller_manager" default="moveit_simple_controller_manager/MoveItSimpleControllerManager" />
<param name="moveit_controller_manager" value="$(arg moveit_controller_manager)"/>
<!-- loads ros_controllers to the param server -->
<rosparam file="$(find new_mycobot_320_pi_moveit)/config/ros_controllers.yaml"/>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/firefighter_moveit_sensor_manager.launch.xml Normal file
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<launch>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/gazebo.launch Executable file
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<?xml version="1.0"?>
<launch>
<arg name="paused" default="false"/>
<arg name="gazebo_gui" default="true"/>
<arg name="urdf_path" default="$(find mycobot_description)/urdf/320_pi/mycobot_pro_320_pi_moveit.urdf"/>
<!-- startup simulated world -->
<include file="$(find gazebo_ros)/launch/empty_world.launch">
<arg name="world_name" default="worlds/empty.world"/>
<arg name="paused" value="$(arg paused)"/>
<arg name="gui" value="$(arg gazebo_gui)"/>
</include>
<!-- send robot urdf to param server -->
<param name="robot_description" textfile="$(arg urdf_path)" />
<!-- push robot_description to factory and spawn robot in gazebo at the origin, change x,y,z arguments to spawn in a different position -->
<node name="spawn_gazebo_model" pkg="gazebo_ros" type="spawn_model" args="-urdf -param robot_description -model robot -x 0 -y 0 -z 0"
respawn="false" output="screen" />
<include file="$(find new_mycobot_320_pi_moveit)/launch/ros_controllers.launch"/>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/joystick_control.launch Executable file
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<launch>
<!-- See moveit_ros/visualization/doc/joystick.rst for documentation -->
<arg name="dev" default="/dev/input/js0" />
<!-- Launch joy node -->
<node pkg="joy" type="joy_node" name="joy">
<param name="dev" value="$(arg dev)" /> <!-- Customize this to match the location your joystick is plugged in on-->
<param name="deadzone" value="0.2" />
<param name="autorepeat_rate" value="40" />
<param name="coalesce_interval" value="0.025" />
</node>
<!-- Launch python interface -->
<node pkg="moveit_ros_visualization" type="moveit_joy.py" output="screen" name="moveit_joy"/>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/move_group.launch Executable file
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<launch>
<include file="$(find new_mycobot_320_pi_moveit)/launch/planning_context.launch" />
<!-- GDB Debug Option -->
<arg name="debug" default="false" />
<arg unless="$(arg debug)" name="launch_prefix" value="" />
<arg if="$(arg debug)" name="launch_prefix"
value="gdb -x $(find new_mycobot_320_pi_moveit)/launch/gdb_settings.gdb --ex run --args" />
<!-- Verbose Mode Option -->
<arg name="info" default="$(arg debug)" />
<arg unless="$(arg info)" name="command_args" value="" />
<arg if="$(arg info)" name="command_args" value="--debug" />
<!-- move_group settings -->
<arg name="allow_trajectory_execution" default="true"/>
<arg name="fake_execution" default="false"/>
<arg name="max_safe_path_cost" default="1"/>
<arg name="jiggle_fraction" default="0.05" />
<arg name="publish_monitored_planning_scene" default="true"/>
<arg name="capabilities" default=""/>
<arg name="disable_capabilities" default=""/>
<!-- load these non-default MoveGroup capabilities (space seperated) -->
<!--
<arg name="capabilities" value="
a_package/AwsomeMotionPlanningCapability
another_package/GraspPlanningPipeline
" />
-->
<!-- inhibit these default MoveGroup capabilities (space seperated) -->
<!--
<arg name="disable_capabilities" value="
move_group/MoveGroupKinematicsService
move_group/ClearOctomapService
" />
-->
<!-- Planning Functionality -->
<include ns="move_group" file="$(find new_mycobot_320_pi_moveit)/launch/planning_pipeline.launch.xml">
<arg name="pipeline" value="ompl" />
</include>
<!-- Trajectory Execution Functionality -->
<include ns="move_group" file="$(find new_mycobot_320_pi_moveit)/launch/trajectory_execution.launch.xml" if="$(arg allow_trajectory_execution)">
<arg name="moveit_manage_controllers" value="true" />
<arg name="moveit_controller_manager" value="firefighter" unless="$(arg fake_execution)"/>
<arg name="moveit_controller_manager" value="fake" if="$(arg fake_execution)"/>
</include>
<!-- Sensors Functionality -->
<include ns="move_group" file="$(find new_mycobot_320_pi_moveit)/launch/sensor_manager.launch.xml" if="$(arg allow_trajectory_execution)">
<arg name="moveit_sensor_manager" value="firefighter" />
</include>
<!-- Start the actual move_group node/action server -->
<node name="move_group" launch-prefix="$(arg launch_prefix)" pkg="moveit_ros_move_group" type="move_group" respawn="false" output="screen" args="$(arg command_args)">
<!-- Set the display variable, in case OpenGL code is used internally -->
<env name="DISPLAY" value="$(optenv DISPLAY :0)" />
<param name="allow_trajectory_execution" value="$(arg allow_trajectory_execution)"/>
<param name="max_safe_path_cost" value="$(arg max_safe_path_cost)"/>
<param name="jiggle_fraction" value="$(arg jiggle_fraction)" />
<param name="capabilities" value="$(arg capabilities)"/>
<param name="disable_capabilities" value="$(arg disable_capabilities)"/>
<!-- Publish the planning scene of the physical robot so that rviz plugin can know actual robot -->
<param name="planning_scene_monitor/publish_planning_scene" value="$(arg publish_monitored_planning_scene)" />
<param name="planning_scene_monitor/publish_geometry_updates" value="$(arg publish_monitored_planning_scene)" />
<param name="planning_scene_monitor/publish_state_updates" value="$(arg publish_monitored_planning_scene)" />
<param name="planning_scene_monitor/publish_transforms_updates" value="$(arg publish_monitored_planning_scene)" />
</node>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/moveit.rviz Normal file
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Panels:
- Class: rviz/Displays
Help Height: 84
Name: Displays
Property Tree Widget:
Expanded:
- /MotionPlanning1
- /MotionPlanning1/Scene Geometry1
- /MotionPlanning1/Scene Robot1
- /MotionPlanning1/Planning Request1
- /MotionPlanning1/Planned Path1
Splitter Ratio: 0.742560029
Tree Height: 195
- Class: rviz/Help
Name: Help
- Class: rviz/Views
Expanded:
- /Current View1
Name: Views
Splitter Ratio: 0.5
Toolbars:
toolButtonStyle: 2
Visualization Manager:
Class: ""
Displays:
- Alpha: 0.5
Cell Size: 1
Class: rviz/Grid
Color: 160; 160; 164
Enabled: true
Line Style:
Line Width: 0.0299999993
Value: Lines
Name: Grid
Normal Cell Count: 0
Offset:
X: 0
Y: 0
Z: 0
Plane: XY
Plane Cell Count: 10
Reference Frame: <Fixed Frame>
Value: true
- Acceleration_Scaling_Factor: 1
Class: moveit_rviz_plugin/MotionPlanning
Enabled: true
Move Group Namespace: ""
MoveIt_Allow_Approximate_IK: false
MoveIt_Allow_External_Program: false
MoveIt_Allow_Replanning: false
MoveIt_Allow_Sensor_Positioning: false
MoveIt_Goal_Tolerance: 0
MoveIt_Planning_Attempts: 10
MoveIt_Planning_Time: 5
MoveIt_Use_Constraint_Aware_IK: true
MoveIt_Warehouse_Host: 127.0.0.1
MoveIt_Warehouse_Port: 33829
MoveIt_Workspace:
Center:
X: 0
Y: 0
Z: 0
Size:
X: 2
Y: 2
Z: 2
Name: MotionPlanning
Planned Path:
Color Enabled: false
Interrupt Display: false
Links:
All Links Enabled: true
Expand Joint Details: false
Expand Link Details: false
Expand Tree: false
Link Tree Style: Links in Alphabetic Order
base:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link1:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link2:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link3:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link4:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link5:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link6:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
Loop Animation: false
Robot Alpha: 0.5
Robot Color: 150; 50; 150
Show Robot Collision: false
Show Robot Visual: true
Show Trail: false
State Display Time: 0.05 s
Trail Step Size: 1
Trajectory Topic: move_group/display_planned_path
Planning Metrics:
Payload: 1
Show Joint Torques: false
Show Manipulability: false
Show Manipulability Index: false
Show Weight Limit: false
TextHeight: 0.0799999982
Planning Request:
Colliding Link Color: 255; 0; 0
Goal State Alpha: 1
Goal State Color: 250; 128; 0
Interactive Marker Size: 0
Joint Violation Color: 255; 0; 255
Planning Group: arm_group
Query Goal State: true
Query Start State: true
Show Workspace: false
Start State Alpha: 1
Start State Color: 0; 255; 0
Planning Scene Topic: move_group/monitored_planning_scene
Robot Description: robot_description
Scene Geometry:
Scene Alpha: 1
Scene Color: 50; 230; 50
Scene Display Time: 0.200000003
Show Scene Geometry: true
Voxel Coloring: Z-Axis
Voxel Rendering: Occupied Voxels
Scene Robot:
Attached Body Color: 150; 50; 150
Links:
All Links Enabled: true
Expand Joint Details: false
Expand Link Details: false
Expand Tree: false
Link Tree Style: Links in Alphabetic Order
base:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link1:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link2:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link3:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link4:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link5:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
link6:
Alpha: 1
Show Axes: false
Show Trail: false
Value: true
Robot Alpha: 0.5
Show Robot Collision: false
Show Robot Visual: false
Value: true
Velocity_Scaling_Factor: 1
Enabled: true
Global Options:
Background Color: 48; 48; 48
Default Light: true
Fixed Frame: base
Frame Rate: 30
Name: root
Tools:
- Class: rviz/Interact
Hide Inactive Objects: true
- Class: rviz/MoveCamera
- Class: rviz/Select
Value: true
Views:
Current:
Class: rviz/XYOrbit
Distance: 2.99650002
Enable Stereo Rendering:
Stereo Eye Separation: 0.0599999987
Stereo Focal Distance: 1
Swap Stereo Eyes: false
Value: false
Focal Point:
X: 0.113567002
Y: 0.105920002
Z: 2.23518001e-07
Focal Shape Fixed Size: true
Focal Shape Size: 0.0500000007
Invert Z Axis: false
Name: Current View
Near Clip Distance: 0.00999999978
Pitch: 0.0797968805
Target Frame: base
Value: XYOrbit (rviz)
Yaw: 2.89994884
Saved: ~
Window Geometry:
Displays:
collapsed: false
Height: 898
Help:
collapsed: false
Hide Left Dock: false
Hide Right Dock: false
MotionPlanning:
collapsed: false
MotionPlanning - Trajectory Slider:
collapsed: false
QMainWindow State: 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
Views:
collapsed: false
Width: 1855
X: 58
Y: 24

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mycobot_320/new_mycobot_320_pi_moveit/launch/moveit_rviz.launch Executable file
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<launch>
<arg name="debug" default="false" />
<arg unless="$(arg debug)" name="launch_prefix" value="" />
<arg if="$(arg debug)" name="launch_prefix" value="gdb --ex run --args" />
<arg name="config" default="false" />
<arg unless="$(arg config)" name="command_args" value="" />
<arg if="$(arg config)" name="command_args" value="-d $(find new_mycobot_320_pi_moveit)/launch/moveit.rviz" />
<node name="$(anon rviz)" launch-prefix="$(arg launch_prefix)" pkg="rviz" type="rviz" respawn="false"
args="$(arg command_args)" output="screen">
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/kinematics.yaml"/>
</node>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/mycobot320_moveit.launch Executable file
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<launch>
<!-- By default, we do not start a database (it can be large) -->
<arg name="db" default="false" />
<!-- Allow user to specify database location -->
<arg name="db_path" default="$(find new_mycobot_320_pi_moveit)/default_warehouse_mongo_db" />
<!-- By default, we are not in debug mode -->
<arg name="debug" default="false" />
<!--
By default, hide joint_state_publisher's GUI
MoveIt!'s "demo" mode replaces the real robot driver with the joint_state_publisher.
The latter one maintains and publishes the current joint configuration of the simulated robot.
It also provides a GUI to move the simulated robot around "manually".
This corresponds to moving around the real robot without the use of MoveIt.
-->
<arg name="use_gui" default="false" />
<!-- Load the URDF, SRDF and other .yaml configuration files on the param server -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/planning_context.launch">
<arg name="load_robot_description" value="true"/>
</include>
<!-- If needed, broadcast static tf for robot root -->
<!-- We do not have a robot connected, so publish fake joint states -->
<node name="joint_state_publisher" pkg="joint_state_publisher" type="joint_state_publisher">
<param name="use_gui" value="$(arg use_gui)"/>
<rosparam param="source_list">[move_group/fake_controller_joint_states]</rosparam>
</node>
<!-- Given the published joint states, publish tf for the robot links -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" respawn="true" output="screen" />
<!-- Run the main MoveIt! executable without trajectory execution (we do not have controllers configured by default) -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/move_group.launch">
<arg name="allow_trajectory_execution" value="true"/>
<arg name="fake_execution" value="true"/>
<arg name="info" value="true"/>
<arg name="debug" value="$(arg debug)"/>
</include>
<!-- Run Rviz and load the default config to see the state of the move_group node -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/moveit_rviz.launch">
<arg name="config" value="true"/>
<arg name="debug" value="$(arg debug)"/>
</include>
<!-- If database loading was enabled, start mongodb as well -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/default_warehouse_db.launch" if="$(arg db)">
<arg name="moveit_warehouse_database_path" value="$(arg db_path)"/>
</include>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/ompl_planning_pipeline.launch.xml Normal file
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<launch>
<!-- OMPL Plugin for MoveIt! -->
<arg name="planning_plugin" value="ompl_interface/OMPLPlanner" />
<!-- The request adapters (plugins) used when planning with OMPL.
ORDER MATTERS -->
<arg name="planning_adapters" value="default_planner_request_adapters/AddTimeParameterization
default_planner_request_adapters/FixWorkspaceBounds
default_planner_request_adapters/FixStartStateBounds
default_planner_request_adapters/FixStartStateCollision
default_planner_request_adapters/FixStartStatePathConstraints" />
<arg name="start_state_max_bounds_error" value="0.1" />
<param name="planning_plugin" value="$(arg planning_plugin)" />
<param name="request_adapters" value="$(arg planning_adapters)" />
<param name="start_state_max_bounds_error" value="$(arg start_state_max_bounds_error)" />
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/ompl_planning.yaml"/>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/planning_context.launch Executable file
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<launch>
<!-- By default we do not overwrite the URDF. Change the following to true to change the default behavior -->
<arg name="load_robot_description" default="false"/>
<!-- The name of the parameter under which the URDF is loaded -->
<arg name="robot_description" default="robot_description"/>
<!-- Load universal robot description format (URDF) -->
<param if="$(arg load_robot_description)" name="$(arg robot_description)" textfile="$(find mycobot_description)/urdf/new_320_pi/new_mycobot_pro_320_pi_moveit.urdf"/>
<!-- The semantic description that corresponds to the URDF -->
<param name="$(arg robot_description)_semantic" textfile="$(find new_mycobot_320_pi_moveit)/config/firefighter.srdf" />
<!-- Load updated joint limits (override information from URDF) -->
<group ns="$(arg robot_description)_planning">
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/joint_limits.yaml"/>
</group>
<!-- Load default settings for kinematics; these settings are overridden by settings in a node's namespace -->
<group ns="$(arg robot_description)_kinematics">
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/kinematics.yaml"/>
</group>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/planning_pipeline.launch.xml Normal file
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<launch>
<!-- This file makes it easy to include different planning pipelines;
It is assumed that all planning pipelines are named XXX_planning_pipeline.launch -->
<arg name="pipeline" default="ompl" />
<include file="$(find new_mycobot_320_pi_moveit)/launch/$(arg pipeline)_planning_pipeline.launch.xml" />
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/ros_controllers.launch Executable file
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<?xml version="1.0"?>
<launch>
<!-- Load joint controller configurations from YAML file to parameter server -->
<rosparam file="$(find new_mycobot_320_pi_moveit)/config/ros_controllers.yaml" command="load"/>
<!-- Load the controllers -->
<node name="controller_spawner" pkg="controller_manager" type="spawner" respawn="false"
output="screen" args=""/>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/run_benchmark_ompl.launch Executable file
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<launch>
<!-- This argument must specify the list of .cfg files to process for benchmarking -->
<arg name="cfg" />
<!-- Load URDF -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/planning_context.launch">
<arg name="load_robot_description" value="true"/>
</include>
<!-- Start the database -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/warehouse.launch">
<arg name="moveit_warehouse_database_path" value="moveit_ompl_benchmark_warehouse"/>
</include>
<!-- Start Benchmark Executable -->
<node name="$(anon moveit_benchmark)" pkg="moveit_ros_benchmarks" type="moveit_run_benchmark" args="$(arg cfg) --benchmark-planners" respawn="false" output="screen">
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/kinematics.yaml"/>
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/ompl_planning.yaml"/>
</node>
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/sensor_manager.launch.xml Normal file
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<launch>
<!-- This file makes it easy to include the settings for sensor managers -->
<!-- Params for 3D sensors config -->
<rosparam command="load" file="$(find new_mycobot_320_pi_moveit)/config/sensors_3d.yaml" />
<!-- Params for the octomap monitor -->
<!-- <param name="octomap_frame" type="string" value="some frame in which the robot moves" /> -->
<param name="octomap_resolution" type="double" value="0.025" />
<param name="max_range" type="double" value="5.0" />
<!-- Load the robot specific sensor manager; this sets the moveit_sensor_manager ROS parameter -->
<arg name="moveit_sensor_manager" default="firefighter" />
<include file="$(find new_mycobot_320_pi_moveit)/launch/$(arg moveit_sensor_manager)_moveit_sensor_manager.launch.xml" />
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/setup_assistant.launch Executable file
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<!-- Re-launch the MoveIt! Setup Assistant with this configuration package already loaded -->
<launch>
<!-- Debug Info -->
<arg name="debug" default="false" />
<arg unless="$(arg debug)" name="launch_prefix" value="" />
<arg if="$(arg debug)" name="launch_prefix" value="gdb --ex run --args" />
<!-- Run -->
<node pkg="moveit_setup_assistant" type="moveit_setup_assistant" name="moveit_setup_assistant"
args="--config_pkg=new_mycobot_320_pi_moveit"
launch-prefix="$(arg launch_prefix)"
output="screen" />
</launch>

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mycobot_320/new_mycobot_320_pi_moveit/launch/trajectory_execution.launch.xml Normal file
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<launch>
<!-- This file makes it easy to include the settings for trajectory execution -->
<!-- Flag indicating whether MoveIt! is allowed to load/unload or switch controllers -->
<arg name="moveit_manage_controllers" default="true"/>
<param name="moveit_manage_controllers" value="$(arg moveit_manage_controllers)"/>
<!-- When determining the expected duration of a trajectory, this multiplicative factor is applied to get the allowed duration of execution -->
<param name="trajectory_execution/allowed_execution_duration_scaling" value="1.2"/> <!-- default 1.2 -->
<!-- Allow more than the expected execution time before triggering a trajectory cancel (applied after scaling) -->
<param name="trajectory_execution/allowed_goal_duration_margin" value="0.5"/> <!-- default 0.5 -->
<!-- Allowed joint-value tolerance for validation that trajectory's first point matches current robot state -->
<param name="trajectory_execution/allowed_start_tolerance" value="0.01"/> <!-- default 0.01 -->
<!-- Load the robot specific controller manager; this sets the moveit_controller_manager ROS parameter -->
<arg name="moveit_controller_manager" default="firefighter" />
<include file="$(find new_mycobot_320_pi_moveit)/launch/$(arg moveit_controller_manager)_moveit_controller_manager.launch.xml" />
</launch>

15
mycobot_320/new_mycobot_320_pi_moveit/launch/warehouse.launch Executable file
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@ -0,0 +1,15 @@
<launch>
<!-- The path to the database must be specified -->
<arg name="moveit_warehouse_database_path" />
<!-- Load warehouse parameters -->
<include file="$(find new_mycobot_320_pi_moveit)/launch/warehouse_settings.launch.xml" />
<!-- Run the DB server -->
<node name="$(anon mongo_wrapper_ros)" cwd="ROS_HOME" type="mongo_wrapper_ros.py" pkg="warehouse_ros_mongo">
<param name="overwrite" value="false"/>
<param name="database_path" value="$(arg moveit_warehouse_database_path)" />
</node>
</launch>

16
mycobot_320/new_mycobot_320_pi_moveit/launch/warehouse_settings.launch.xml Normal file
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@ -0,0 +1,16 @@
<launch>
<!-- Set the parameters for the warehouse and run the mongodb server. -->
<!-- The default DB port for moveit (not default MongoDB port to avoid potential conflicts) -->
<arg name="moveit_warehouse_port" default="33829" />
<!-- The default DB host for moveit -->
<arg name="moveit_warehouse_host" default="localhost" />
<!-- Set parameters for the warehouse -->
<param name="warehouse_port" value="$(arg moveit_warehouse_port)"/>
<param name="warehouse_host" value="$(arg moveit_warehouse_host)"/>
<param name="warehouse_exec" value="mongod" />
<param name="warehouse_plugin" value="warehouse_ros_mongo::MongoDatabaseConnection" />
</launch>

33
mycobot_320/new_mycobot_320_pi_moveit/package.xml Normal file
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@ -0,0 +1,33 @@
<?xml version="1.0"?>
<package format="2">
<name>new_mycobot_320_pi_moveit</name>
<version>0.0.0</version>
<description>The new_mycobot_320_pi_moveit package</description>
<author email="weijian.wang@elephantrobotics.com">zachary</author>
<maintainer email="weijian.wang@elephantrobotics.com">zachary</maintainer>
<license>BSD</license>
<url type="website">http://moveit.ros.org/</url>
<url type="bugtracker">https://github.com/ros-planning/moveit/issues</url>
<url type="repository">https://github.com/ros-planning/moveit</url>
<buildtool_depend>catkin</buildtool_depend>
<exec_depend>moveit_ros_move_group</exec_depend>
<exec_depend>moveit_fake_controller_manager</exec_depend>
<exec_depend>moveit_kinematics</exec_depend>
<exec_depend>moveit_planners_ompl</exec_depend>
<exec_depend>moveit_ros_visualization</exec_depend>
<exec_depend>moveit_setup_assistant</exec_depend>
<exec_depend>joint_state_publisher</exec_depend>
<exec_depend>robot_state_publisher</exec_depend>
<exec_depend>xacro</exec_depend>
<!-- This package is referenced in the warehouse launch files, but does not build out of the box at the moment. Commented the dependency until this works. -->
<!-- <exec_depend>warehouse_ros_mongo</exec_depend> -->
<build_depend>mycobot_description</build_depend>
<exec_depend>mycobot_description</exec_depend>
</package>

137
mycobot_320/new_mycobot_320_pi_moveit/scripts/path_planning_and_obstacle_avoidance_demo.py Executable file
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@ -0,0 +1,137 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import rospy, roslib, sys
import moveit_commander
from moveit_msgs.msg import RobotTrajectory
from trajectory_msgs.msg import JointTrajectoryPoint
from geometry_msgs.msg import PoseStamped, Pose
from tf.transformations import euler_from_quaternion, quaternion_from_euler
class MoveItPlanningDemo:
def __init__(self):
# API to initialize move_group,初始化move_group的API
moveit_commander.roscpp_initialize(sys.argv)
# Initialize the ROS node,初始化ROS节点
rospy.init_node("moveit_ik_demo")
# Initialize the scene object to monitor changes in the external environment
# 初始化场景对象，用来监听外部环境的变化
self.scene = moveit_commander.PlanningSceneInterface()
rospy.sleep(1)
# Initialize self.arm group in the robotic arm that needs to be controlled by move group
# 初始化需要使用move group控制的机械臂中的self.arm group
self.arm = moveit_commander.MoveGroupCommander("arm_group")
# Get the name of the terminal link,获取终端link的名称
self.end_effector_link = self.arm.get_end_effector_link()
# Set the reference coordinate system used for the target position
# 设置目标位置所使用的参考坐标系
self.reference_frame = "joint1"
self.arm.set_pose_reference_frame(self.reference_frame)
# Allow replanning when motion planning fails,当运动规划失败后，允许重新规划
self.arm.allow_replanning(True)
# Set the allowable error of position (unit: meter) and attitude (unit: radian)
# 设置位置(单位：米)和姿态（单位：弧度）的允许误差
self.arm.set_goal_position_tolerance(0.01)
self.arm.set_goal_orientation_tolerance(0.05)
def moving(self):
# # Control the robotic arm to return to the initialization position first
# 控制机械臂先回到初始化位置
self.arm.set_named_target("init_pose")
self.arm.go()
rospy.sleep(2)
# Set the target pose in the robotic arm workspace, the position is described by x, y, z coordinates,
# 设置机械臂工作空间中的目标位姿，位置使用x、y、z坐标描述，
# Pose is described by quaternion, based on base_link coordinate system
# 姿态使用四元数描述，基于base_link坐标系
target_pose = PoseStamped()
target_pose.header.frame_id = self.reference_frame
target_pose.header.stamp = rospy.Time.now()
target_pose.pose.position.x = 0.132
target_pose.pose.position.y = -0.150
target_pose.pose.position.z = 0.075
target_pose.pose.orientation.x = 0.026
target_pose.pose.orientation.y = 1.0
target_pose.pose.orientation.z = 0.0
target_pose.pose.orientation.w = 0.014
# Set the current state of the robot arm as the initial state of motion
# 设置机器臂当前的状态作为运动初始状态
self.arm.set_start_state_to_current_state()
# Set the target pose of the terminal motion of the robotic arm
# 设置机械臂终端运动的目标位姿
self.arm.set_pose_target(target_pose, self.end_effector_link)
# Plan the movement path,规划运动路径
traj = self.arm.plan()
# Control the motion of the robotic arm according to the planned motion path
# 按照规划的运动路径控制机械臂运动
self.arm.execute(traj)
rospy.sleep(1)
# Control the terminal of the robotic arm to move 5cm to the right. Parameter 1 represents y, 0,1,2,3,4,5 represents xyzrpy
# 控制机械臂终端向右移动5cm 參數1是代表y， 0,1,2,3,4,5 代表xyzrpy
self.arm.shift_pose_target(1, 0.12, self.end_effector_link)
self.arm.go()
rospy.sleep(1)
self.arm.shift_pose_target(1, 0.1, self.end_effector_link)
self.arm.go()
rospy.sleep(1)
# Control the terminal of the robotic arm to rotate 90 degrees in the opposite direction. 0,1,2,3,4,5 represent xyzrpy
# 控制机械臂终端反向旋转90度 0,1,2,3,4,5 代表xyzrpy
# self.arm.shift_pose_target(3, -1.57, end_effector_link)
# self.arm.go()
# rospy.sleep(1)
def run(self):
self.scene.remove_world_object("suit")
# Run once without obstacles,没有障碍物运行一次
self.moving()
# Add environment,添加环境
quat = quaternion_from_euler(3.1415, 0, -1.57)
suit_post = PoseStamped()
suit_post.header.frame_id = self.reference_frame
suit_post.pose.position.x = 0.0
suit_post.pose.position.y = 0.0
suit_post.pose.position.z = -0.02
suit_post.pose.orientation.x = quat[0]
suit_post.pose.orientation.y = quat[1]
suit_post.pose.orientation.z = quat[2]
suit_post.pose.orientation.w = quat[3]
suit_path = (
roslib.packages.get_pkg_dir("mycobot_description")
+ "/urdf/mycobot/suit_env.dae"
)
# need `pyassimp==3.3`
self.scene.add_mesh("suit", suit_post, suit_path)
rospy.sleep(2)
# Run it again if there is an environmental impact,有环境影响后再运行一次
self.moving()
# close and exit moveit，关闭并退出moveit
moveit_commander.roscpp_shutdown()
moveit_commander.os._exit(0)
if __name__ == "__main__":
o = MoveItPlanningDemo()
o.run()

41
mycobot_320/new_mycobot_320_pi_moveit/scripts/sync_plan.py Executable file
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@ -0,0 +1,41 @@
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import time
import subprocess
import rospy
from sensor_msgs.msg import JointState
from pymycobot.mycobot import MyCobot
mc = None
def callback(data):
rospy.loginfo(rospy.get_caller_id() + "%s", data)
data_list = []
for index, value in enumerate(data.position):
# if index != 2:
# value *= -1
data_list.append(value)
mc.send_radians(data_list, 80)
def listener():
global mc
rospy.init_node("mycobot_reciver", anonymous=True)
port = rospy.get_param("~port", "/dev/ttyAMA0")
baud = rospy.get_param("~baud", 115200)
# 115200
mc = MyCobot(port, baud)
rospy.Subscriber("joint_states", JointState, callback)
# spin() simply keeps python from exiting until this node is stopped
rospy.spin()
if __name__ == "__main__":
listener()

37
mycobot_ai/launch/Readme.md
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@ -1,37 +0,0 @@
### Tips：
1. 请使用与机械臂相同型号的文件名文件。
2. 请先执行以下操作:
+ 1. 打开一个新的终端
+ 2. 输入命令
```bash
chmod +x /home/h/catkin_mycobot/src/mycobot_ros/mycobot_communication/scripts/xxx.py
# 此处为各个新增文件的文件名
```
3. jetson nano的文件还没有使用机械臂进行过测试，可能存在问题。
4. 数莓派版本的使用:
+ 1. 打开VScode,新建一个文件，复制以下内容（请确保电脑与数莓派机械臂已经连接）并运行
```bash
from pymycobot import MyCobotSocket
mc = MyCobotSocket("192.168.10.10","9000")
mc.connect()
```
+ 2. 打开“网络与internet”设置
更改适配器选项
右键打开数莓派的以太网属性
打开 “internet协议版本4” 的属性
选择 “使用下面的IP地址”
IP地址为 ： 192.168.10.100 （最后一位非10都可）
子网掩码为： 255.255.255.0
确认

28
mycobot_ai/launch/pi.launch
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@ -1,28 +0,0 @@
<launch>
<arg name="port" default="192.168.10.10" />
<arg name="baud" default="9000" />
<!-- urdf文件，模型文件的路径 -->
<arg name="model" default="$(find mycobot_description)/urdf/jetsonNano/mycobot_urdf.urdf"/>
<arg name="rvizconfig" default="$(find mycobot_280)/config/mycobot.rviz" />
<!-- <arg name="gui" default="false" /> -->
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="state_publisher" >
<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
</node>
<!-- mycobot-topics -->
<include file="$(find mycobot_communication)/launch/communication_topic_pi.launch">
<arg name="port" value="$(arg port)" />
<arg name="baud" value="$(arg baud)" />
</include>
<!-- listen and pub the real angles -->
<node name="real_listener" pkg="mycobot_280" type="listen_real_of_topic.py" />
<!-- Show in Rviz -->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
</launch>

27
mycobot_ai/launch/seeed.launch
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@ -1,27 +0,0 @@
<launch>
<arg name="port" default="/dev/ttyACM0" />
<arg name="baud" default="115200" />
<arg name="model" default="$(find mycobot_description)/urdf/seeed/mycobot_urdf.urdf"/>
<arg name="rvizconfig" default="$(find mycobot_280)/config/mycobot.rviz" />
<!-- <arg name="gui" default="false" /> -->
<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
<!-- Combinejoin values to TF -->
<node name="robot_state_publisher" pkg="robot_state_publisher" type="state_publisher" >
<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
</node>
<!-- mycobot-topics -->
<include file="$(find mycobot_communication)/launch/communication_seeed.launch">
<arg name="port" value="$(arg port)" />
<arg name="baud" value="$(arg baud)" />
</include>
<!-- listen and pub the real angles -->
<node name="real_listener" pkg="mycobot_280" type="listen_real_of_topic.py" />
<!-- Show in Rviz -->
<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
</launch>

6
mycobot_ai/launch/vision.launch
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@ -1,6 +1,6 @@
<launch>
<arg name="port" default="/dev/ttyACM0" />
<arg name="baud" default="115200" />
<launch>
<arg name="port" default="/dev/ttyAMA0" />
<arg name="baud" default="1000000" />
<arg name="model" default="$(find mycobot_description)/urdf/mycobot/mycobot_with_vision.urdf"/>
<arg name="rvizconfig" default="$(find mycobot_280)/config/mycobot.rviz" />

6
mycobot_ai/launch/jsnn.launch → mycobot_ai/launch/vision_wio.launch
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@ -1,8 +1,8 @@
<launch>
<arg name="port" default="/dev/ttyTHS1" />
<arg name="port" default="/dev/ttyACM0" />
<arg name="baud" default="115200" />
<arg name="model" default="$(find mycobot_description)/urdf/jetsonNano/mycobot_urdf.urdf"/>
<arg name="model" default="$(find mycobot_description)/urdf/mycobot/mycobot_with_vision.urdf"/>
<arg name="rvizconfig" default="$(find mycobot_280)/config/mycobot.rviz" />
<!-- <arg name="gui" default="false" /> -->
@ -14,7 +14,7 @@
</node>
<!-- mycobot-topics -->
<include file="$(find mycobot_communication)/launch/communication_jsnn.launch">
<include file="$(find mycobot_communication)/launch/communication_topic.launch">
<arg name="port" value="$(arg port)" />
<arg name="baud" value="$(arg baud)" />
</include>

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49
mycobot_ai/scripts/add_img.py Normal file → Executable file
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@ -1,4 +1,5 @@
# coding:utf-8
from fileinput import filename
import os, cv2, sys
@ -11,8 +12,8 @@ def take_photo():
print("*********************************************")
# 创建/使用local_photo文件夹
class_name = "local_photo"
if (os.path.exists("local_photo")):
class_name = "res"
if (os.path.exists("res")):
pass
else:
os.mkdir(class_name)
@ -47,9 +48,22 @@ def take_photo():
def cut_photo():
path = os.getcwd() + '/local_photo/img'
for i, j, k in os.walk(path):
file_len = len(k)
path_red = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/red'
for i, j, k in os.walk(path_red):
file_len_red = len(k)
path_gray = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/gray'
for i, j, k in os.walk(path_gray):
file_len_gray = len(k)
path_green = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/green'
for i, j, k in os.walk(path_green):
file_len_green = len(k)
path_blue = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/blue'
for i, j, k in os.walk(path_blue):
file_len_blue = len(k)
print("请截取要识别的部分")
# root = tk.Tk()
# root.withdraw()
@ -58,7 +72,7 @@ def cut_photo():
# temp2= cv.cvtColor(np.asarray(temp2),cv.COLOR_RGB2BGR)
# cut = np.array(temp2)
cut = cv2.imread(r"local_photo/takephoto.jpeg")
cut = cv2.imread(r"res/takephoto.jpeg")
cv2.imshow('original', cut)
# C:\Users\Elephant\Desktop\pymycobot+opencv\local_photo/takephoto.jpeg
@ -71,13 +85,30 @@ def cut_photo():
x, y, w, h = roi
print(roi)
kw = input("请输入保存图片文件夹名称('red','gray','blue','green'）:")
# print(kw)
# 显示ROI并保存图片
if roi != (0, 0, 0, 0):
crop = cut[y:y + h, x:x + w]
cv2.imshow('crop', crop)
cv2.imwrite('local_photo/img/goal{}.jpeg'.format(str(file_len + 1)),
crop)
print('Saved!')
# 选择红桶文件夹
if kw == 'red':
cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/red/goal{}.jpeg'.format(str(file_len_red + 1)),crop)
print('Saved')
# 选择灰桶文件夹
elif kw == 'gray':
cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/gray/goal{}.jpeg'.format(str(file_len_gray+1)),crop)
print('Saved')
# 选择绿桶文件夹
elif kw == 'green':
cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/green/goal{}.jpeg'.format(str(file_len_green+1)),crop)
print('Saved')
# 选择蓝桶文件夹
elif kw == 'blue':
cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/blue/goal{}.jpeg'.format(str(file_len_blue+1)),crop)
print('Saved')
# 退出
cv2.waitKey(0)

182
mycobot_ai/scripts/ai_windows.py
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@ -1,182 +0,0 @@
#!/usr/bin/env python3
# encoding:utf-8
from tkinter import ttk
from tkinter import *
import os
import time
import threading
from multiprocessing import Process
class Application(object):
def __init__(self):
self.win = Tk()
# 窗口置顶
self.win.wm_attributes('-topmost', 1)
self.ros = False
# 运行的文件
self.run_py = ""
# 判断通信口并给权限
try:
self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1]
self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1]
self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
if "dev" in self.robot_wio:
self.set_file(self.robot_wio)
elif "dev" in self.robot_m5:
self.set_file(self.robot_m5)
elif "dev" in self.robot_raspi:
self.change_file(self.robot_raspi)
elif "dev" in self.robot_jes:
self.change_file(self.robot_jes)
except Exception as e:
pass
# 设置标题
self.win.title("aikit启动工具")
self.win.geometry(
"550x350+100+100") # 290 160为窗口大小，+10 +10 定义窗口弹出时的默认展示位置
self.chanse_code = Label(self.win, text="选择程序:", width=10)
self.chanse_code.grid(row=1)
self.myComboList = [u"颜色识别", u"物体识别", u"二维码识别"]
self.myCombox = ttk.Combobox(self.win, values=self.myComboList)
self.myCombox.grid(row=1, column=1)
self.add_btn = Button(self.win, text="添加新的物体图像", command=self.add_img)
self.add_btn.grid(row=1, column=2)
self.tips = "1、等待打开ros,大概需要15s\n2、选择所要运行的程序点击运行即可,开启大概需要10秒,可以通过查看终端查看开启情况。\n\n添加新的图像：\n1、点击按钮，等待开启摄像头\n2、选中图像框，按z键拍照\n3、使用鼠标框出需要识别的图像区域\n4、按Enter键提取图像\n5、再次按Enter键保存即可"
self.btn = Button(self.win, text="运行", command=self.start_run)
self.btn.grid(row=5)
self.close = Button(self.win, text="close", command=self.close_py)
self.close.grid(row=5, column=1)
self.t2 = None
self.log_data = Text(self.win, width=66, height=10)
self.log_data.grid(row=16, column=0, columnspan=10)
self.log_data.insert(END, self.tips)
self.open_ros()
self.win.protocol('WM_DELETE_WINDOW', self.close_rviz)
def close_rviz(self):
os.system(
"ps -ef | grep -E mycobot.rviz | grep -v 'grep' | awk '{print $2}' | xargs kill -9")
sys.exit(0)
def set_file(self,port):
self.command = '<arg name="port" default="{}" />'.format(
port)
# 根据通信口修改ros启动文件
os.system(
"sed -i '2c {}' ~/catkin_ws/src/mycobot_ros/mycobot_ai/launch/vision.launch"
.format(self.command))
def change_file(self, port):
command1 = '<arg name="port" default="{}" />'.format(port)
command2 = '<arg name="baud" default="{}" />'.format(1000000)
# 根据通信口修改ros启动文件
os.system(
"sed -i '2c {}' ~/catkin_ws/src/mycobot_ros/mycobot_ai/launch/vision.launch".format(command1))
os.system(
"sed -i '3c {}' ~/catkin_ws/src/mycobot_ros/mycobot_ai/launch/vision.launch".format(command2))
def start_run(self):
try:
print(u"开始运行")
one = self.myCombox.get()
if one == u"颜色识别":
self.run_py = "detect_obj_color.py"
t2 = threading.Thread(target=self.open_py1)
t2.setDaemon(True)
t2.start()
elif one == u"物体识别":
self.run_py = "detect_obj_img.py"
t3 = threading.Thread(target=self.open_py)
t3.setDaemon(True)
t3.start()
elif one == u"二维码识别":
self.run_py = "detect_encode.py"
t3 = threading.Thread(target=self.open_py2)
t3.setDaemon(True)
t3.start()
except Exception as e:
self.tips = str(e)
self.log_data.insert(END, self.tips)
def open_py(self):
os.system(
"python ~/catkin_ws/src/mycobot_ros/mycobot_ai/scripts/detect_obj_img.py"
)
def open_py1(self):
os.system(
"python ~/catkin_ws/src/mycobot_ros/mycobot_ai/scripts/detect_obj_color.py"
)
def open_py2(self):
os.system(
"python ~/catkin_ws/src/mycobot_ros/mycobot_ai/scripts/detect_encode.py"
)
def add_img(self):
os.system(
"python ~/catkin_ws/src/mycobot_ros/mycobot_ai/scripts/add_img.py"
)
def open_ros(self):
t1 = threading.Thread(target=self.ross)
t1.setDaemon(True)
t1.start()
self.ros = True
def ross(self):
os.system(
"roslaunch ~/catkin_ws/src/mycobot_ros/mycobot_ai/launch/vision.launch"
)
def close_py(self):
t1 = threading.Thread(target=self.close_p)
t1.setDaemon(True)
t1.start()
def close_p(self):
# 关闭ai程序
os.system("ps -ef | grep -E " + self.run_py +
" | grep -v 'grep' | awk '{print $2}' | xargs kill -9")
def get_current_time(self):
# 日志时间
"""Get current time with format."""
current_time = time.strftime("%Y-%m-%d %H:%M:%S",
time.localtime(time.time()))
return current_time
def write_log_to_Text(self, logmsg):
# 设置日志函数
global LOG_NUM
current_time = self.get_current_time()
logmsg_in = str(current_time) + " " + str(logmsg) + "\n" # 换行
if LOG_NUM <= 18:
self.log_data_Text.insert(END, logmsg_in)
LOG_NUM += len(logmsg_in.split("\n"))
# print(LOG_NUM)
else:
self.log_data_Text.insert(END, logmsg_in)
self.log_data_Text.yview("end")
def run(self):
self.win.mainloop()
if __name__ == "__main__":
mc = Application()
mc.run()

0
mycobot_ai/scripts/detect_encode.py Normal file → Executable file
View file

50
mycobot_ai/scripts/detect_obj_color.py Normal file → Executable file
View file

@ -64,6 +64,7 @@ class Object_detect(Movement):
self.raspi = True
if self.raspi:
self.gpio_status(False)
self.Pin = [2, 5]
# choose place to set cube
self.color = 0
@ -147,20 +148,10 @@ class Object_detect(Movement):
# send coordinates to move mycobot
self.pub_coords([x, y, 165, -178.9, -1.57, -25.95], 20, 1)
time.sleep(1.5)
if "dev" in self.robot_m5 or self.raspi:
self.pub_coords([x, y, 90, -178.9, -1.57, -25.95], 20, 1)
elif "dev" in self.robot_wio:
h = 0
if 165 < x < 180:
h = 10
elif x > 180:
h = 20
elif x < 135:
h = -20
self.pub_coords([x, y, 31.9+h, -178.9, -1, -25.95], 20, 1)
time.sleep(1.5)
self.pub_coords([x, y, 80, -178.9, -1.57, -25.95], 20, 1)
time.sleep(1)
# open pump
if self.raspi:
self.gpio_status(True)
@ -213,34 +204,9 @@ class Object_detect(Movement):
else:
self.cache_x = self.cache_y = 0
# 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动
if "dev" in self.robot_wio:
if (y < -30 and x > 140) or (x > 150 and y < -10):
x -= 10
y += 10
elif y > -10:
y += 10
elif x > 170:
x -= 10
y += 10
elif "dev" in self.robot_raspi:
if x > 160:
y += 10
elif y < -20:
x -= 10
y += 10
elif "dev" in self.robot_jes:
y += 13
x += 4
elif "dev" in self.robot_m5:
x -= 10
if y < 0:
y += 10
if y < -30:
y += 7
print x, y
self.move(x, y, color)
self.move(x,y, color)
# init mycobot
def run(self):

393
mycobot_ai/scripts/detect_obj_color_wio.py Executable file
View file

@ -0,0 +1,393 @@
#encoding:utf-8
from tokenize import Pointfloat
import cv2
import numpy as np
import time
import json
import os
import rospy
from visualization_msgs.msg import Marker
from moving_utils import Movement
IS_CV_4 = cv2.__version__[0] == '4'
class Object_detect(Movement):
def __init__(self, camera_x=150, camera_y=-10):
# inherit the parent class
super(Object_detect, self).__init__()
# get path of file
dir_path = os.path.dirname(__file__)
# choose place to set cube
self.color = 0
# parameters to calculate camera clipping parameters
self.x1 = self.x2 = self.y1 = self.y2 =0
# set cache of real coord
self.cache_x = self.cache_y = 0
# set color HSV
self.HSV = {
"yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])],
"red": [np.array([0, 43, 46]), np.array([8, 255, 255])],
}
# use to calculate coord between cube and mycobot
self.sum_x1= self.sum_x2= self.sum_y2= self.sum_y1= 0
# The coordinates of the grab center point relative to the mycobot
self.camera_x, self.camera_y = camera_x, camera_y
# The coordinates of the cube relative to the mycobot
self.c_x, self.c_y = 0,0
# The ratio of pixels to actual values
self.ratio = 0
# Get ArUco marker dict that can be detected.
self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
# Get ArUco marker params.
self.aruco_params = cv2.aruco.DetectorParameters_create()
# init a node and a publisher
rospy.init_node("marker", anonymous=True)
self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
# init a Marker
self.marker = Marker()
self.marker.header.frame_id = "/joint1"
self.marker.ns = "cube"
self.marker.type = self.marker.CUBE
self.marker.action = self.marker.ADD
self.marker.scale.x = 0.04
self.marker.scale.y = 0.04
self.marker.scale.z = 0.04
self.marker.color.a = 1.0
self.marker.color.g = 1.0
self.marker.color.r = 1.0
# marker position initial
self.marker.pose.position.x = 0
self.marker.pose.position.y = 0
self.marker.pose.position.z = 0.03
self.marker.pose.orientation.x = 0
self.marker.pose.orientation.y = 0
self.marker.pose.orientation.z = 0
self.marker.pose.orientation.w = 1.0
# publish marker
def pub_marker(self, x, y , z=0.03):
self.marker.header.stamp = rospy.Time.now()
self.marker.pose.position.x = x
self.marker.pose.position.y = y
self.marker.pose.position.z = z
self.marker.color.g = self.color
self.pub.publish(self.marker)
# Grasping motion
def move(self, x,y,color):
angles = [
[-7.11, -6.94, -55.01, -24.16, 0, -38.84], # init the point
[-1.14, -10.63, -87.8, 9.05, -3.07, -37.7], # point to grab
[17.4, -10.1, -87.27, 5.8, -2.02, -37.7], # point to grab
]
coords = [
[106.1, -141.6, 240.9, -173.34, -8.15, -83.11], # above the red bucket
[208.2, -127.8, 246.9, -157.51, -17.5, -71.18], # above the green bucket
[209.7, -18.6, 230.4, -168.48, -9.86, -39.38],
[196.9, -64.7, 232.6, -166.66, -9.44, -52.47],
[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
]
# send Angle to move mycobot
self.pub_angles(angles[0], 20)
time.sleep(1.5)
self.pub_angles(angles[1], 20)
time.sleep(1.5)
self.pub_angles(angles[2], 20)
time.sleep(1.5)
# send coordinates to move mycobot
self.pub_coords([x, y, 165, -178.9, -1.57, -25.95], 20, 1)
time.sleep(1.5)
self.pub_coords([x, y, 40, -178.9, -1.57, -25.95], 20, 1)
time.sleep(1.5)
# open pump
self.pub_pump(True,[20,21])
time.sleep(0.5)
self.pub_angles(angles[2], 20)
time.sleep(3)
self.pub_marker(coords[2][0]/1000.0, coords[2][1]/1000.0, coords[2][2]/1000.0)
self.pub_angles(angles[1], 20)
time.sleep(1.5)
self.pub_marker(coords[3][0]/1000.0, coords[3][1]/1000.0, coords[3][2]/1000.0)
self.pub_angles(angles[0], 20)
time.sleep(1.5)
self.pub_marker(coords[4][0]/1000.0, coords[4][1]/1000.0, coords[4][2]/1000.0)
self.pub_coords(coords[color], 20, 1)
self.pub_marker(coords[color][0]/1000.0, coords[color][1]/1000.0, coords[color][2]/1000.0)
time.sleep(2)
# close pump
self.pub_pump(False,[20,21])
if color==1:
self.pub_marker(coords[color][0]/1000.0+0.04, coords[color][1]/1000.0-0.02)
elif color==0:
self.pub_marker(coords[color][0]/1000.0+0.03, coords[color][1]/1000.0)
self.pub_angles(angles[0], 20)
time.sleep(3)
# decide whether grab cube
def decide_move(self, x, y, color):
print(x, y,self.cache_x, self.cache_y)
# detect the cube status move or run
if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
self.cache_x, self.cache_y = x, y
return
else:
self.cache_x = self.cache_y = 0
self.move(x-10,y+10,color)
# init mycobot
def run(self):
for _ in range(10):
self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -38.84], 20)
print(_)
time.sleep(0.5)
self.pub_pump(False,[20,21])
# draw aruco
def draw_marker(self,img,x,y):
# draw rectangle on img
cv2.rectangle(
img,
(x - 20, y - 20),
(x + 20, y + 20),
(0, 255, 0),
thickness=2,
lineType=cv2.FONT_HERSHEY_COMPLEX,
)
# add text on rectangle
cv2.putText(img,"({},{})".format(x,y),(x,y),cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,)
# get points of two aruco
def get_calculate_params(self,img):
# Convert the image to a gray image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detect ArUco marker.
corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
gray, self.aruco_dict, parameters=self.aruco_params
)
"""
Two Arucos must be present in the picture and in the same order.
There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
Determine the center of the aruco by the four corners of the aruco.
"""
if len(corners) > 0:
if ids is not None:
if len(corners) <= 1 or ids[0]==1:
return None
x1=x2=y1=y2 = 0
point_11,point_21,point_31,point_41 = corners[0][0]
x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int((point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0)
point_1,point_2,point_3,point_4 = corners[1][0]
x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int((point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0)
return x1,x2,y1,y2
return None
# set camera clipping parameters
def set_cut_params(self, x1, y1, x2, y2):
self.x1 = int(x1)
self.y1 = int(y1)
self.x2 = int(x2)
self.y2 = int(y2)
print(self.x1,self.y1,self.x2,self.y2)
# set parameters to calculate the coords between cube and mycobot
def set_params(self, c_x, c_y, ratio):
self.c_x = c_x
self.c_y = c_y
self.ratio = 220.0/ratio
# calculate the coords between cube and mycobot
def get_position(self, x, y):
return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y)
"""
Calibrate the camera according to the calibration parameters.
Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
If two ARuco values have been calculated, clip the video.
"""
def transform_frame(self, frame):
# enlarge the image by 1.5 times
fx = 1.5
fy = 1.5
frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy, interpolation=cv2.INTER_CUBIC)
if self.x1 != self.x2:
# the cutting ratio here is adjusted according to the actual situation
frame = frame[int(self.y2*0.2):int(self.y1*1.15), int(self.x1*0.7):int(self.x2*1.15)]
return frame
# detect cube color
def color_detect(self, img):
# set the arrangement of color'HSV
x = y = 0
for mycolor, item in self.HSV.items():
redLower = np.array(item[0])
redUpper = np.array(item[1])
# transfrom the img to model of gray
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# wipe off all color expect color in range
mask = cv2.inRange(hsv, item[0], item[1])
# a etching operation on a picture to remove edge roughness
erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2)
# the image for expansion operation, its role is to deepen the color depth in the picture
dilation =cv2.dilate(erosion, np.ones((1, 1), np.uint8), iterations=2)
# adds pixels to the image
target = cv2.bitwise_and(img, img, mask=dilation)
# the filtered image is transformed into a binary image and placed in binary
ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY)
# get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected
contours, hierarchy = cv2.findContours(
dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if len(contours) > 0:
# do something about misidentification
boxes = [
box
for box in [cv2.boundingRect(c) for c in contours]
if min(img.shape[0], img.shape[1]) / 10
< min(box[2], box[3])
< min(img.shape[0], img.shape[1]) / 1
]
if boxes:
for box in boxes:
x, y, w, h = box
# find the largest object that fits the requirements
c = max(contours, key=cv2.contourArea)
# get the lower left and upper right points of the positioning object
x, y, w, h = cv2.boundingRect(c)
# locate the target by drawing rectangle
cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2)
# calculate the rectangle center
x, y = (x*2+w)/2, (y*2+h)/2
# calculate the real coordinates of mycobot relative to the target
if mycolor == "yellow":
self.color = 1
elif mycolor == "red":
self.color = 0
if abs(x) + abs(y) > 0:
return x, y
else:
return None
if __name__ == "__main__":
# open the camera
cap_num = 0
cap = cv2.VideoCapture(cap_num)
if not cap.isOpened():
cap.open()
# init a class of Object_detect
detect = Object_detect()
# init mycobot
detect.run()
_init_ = 20 #
init_num = 0
nparams = 0
num = 0
real_sx = real_sy = 0
while cv2.waitKey(1) < 0:
# read camera
_,frame = cap.read()
# deal img
frame = detect.transform_frame(frame)
if _init_ > 0:
_init_-=1
continue
# calculate the parameters of camera clipping
if init_num < 20:
if detect.get_calculate_params(frame) is None:
cv2.imshow("figure",frame)
continue
else:
x1,x2,y1,y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame,x1,y1)
detect.draw_marker(frame,x2,y2)
detect.sum_x1+=x1
detect.sum_x2+=x2
detect.sum_y1+=y1
detect.sum_y2+=y2
init_num+=1
continue
elif init_num==20:
detect.set_cut_params(
(detect.sum_x1)/20.0,
(detect.sum_y1)/20.0,
(detect.sum_x2)/20.0,
(detect.sum_y2)/20.0,
)
detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
init_num+=1
continue
# calculate params of the coords between cube and mycobot
if nparams < 10:
if detect.get_calculate_params(frame) is None:
cv2.imshow("figure",frame)
continue
else:
x1,x2,y1,y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame,x1,y1)
detect.draw_marker(frame,x2,y2)
detect.sum_x1+=x1
detect.sum_x2+=x2
detect.sum_y1+=y1
detect.sum_y2+=y2
nparams+=1
continue
elif nparams==10:
nparams+=1
# calculate and set params of calculating real coord between cube and mycobot
detect.set_params(
(detect.sum_x1+detect.sum_x2)/20.0,
(detect.sum_y1+detect.sum_y2)/20.0,
abs(detect.sum_x1-detect.sum_x2)/10.0+abs(detect.sum_y1-detect.sum_y2)/10.0
)
print "ok"
continue
# get detect result
detect_result = detect.color_detect(frame)
if detect_result is None:
cv2.imshow("figure",frame)
continue
else:
x, y = detect_result
# calculate real coord between cube and mycobot
real_x, real_y = detect.get_position(x, y)
if num == 20:
detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0)
detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color)
num = real_sx = real_sy = 0
else:
num += 1
real_sy += real_y
real_sx += real_x
cv2.imshow("figure",frame)

29
mycobot_ai/scripts/detect_obj_img.py Normal file → Executable file
View file

@ -25,6 +25,8 @@ class Object_detect(Movement):
super(Object_detect, self).__init__()
# get path of file
dir_path = os.path.dirname(__file__)
# 移动角度
self.move_angles = [
[-7.11, -6.94, -55.01, -24.16, 0, 15], # init the point
@ -64,7 +66,7 @@ class Object_detect(Movement):
self.raspi = True
if self.raspi:
self.gpio_status(False)
self.Pin = [2, 5]
# choose place to set cube
self.color = 0
# parameters to calculate camera clipping parameters
@ -77,6 +79,10 @@ class Object_detect(Movement):
# self.label_path = os.path.join(dir_path, "labels.json")
# load class labels
# self.labels = json.load(open(self.label_path))
# use to calculate coord between cube and mycobot
self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
# The coordinates of the grab center point relative to the mycobot
@ -121,6 +127,8 @@ class Object_detect(Movement):
self.marker.pose.orientation.w = 1.0
self.cache_x = self.cache_y = 0
# publish marker
def pub_marker(self, x, y, z=0.03):
@ -152,8 +160,8 @@ class Object_detect(Movement):
self.pub_coords([x, y, 165, -178.9, -1.57, -66], 20, 1)
time.sleep(1.5)
# 根据不同底板机械臂，调整吸泵高度
if "dev" in self.robot_m5 or "dev" in self.robot_raspi:
# m5 and raspi
if "dev" in self.robot_m5:
# m5 and jetson nano
self.pub_coords([x, y, 90, -178.9, -1.57, -66], 25, 1)
elif "dev" in self.robot_wio:
h = 0
@ -166,8 +174,8 @@ class Object_detect(Movement):
self.pub_coords([x, y, 31.9+h, -178.9, -1, -66], 20, 1)
elif "dev" in self.robot_jes:
h = 0
if x < 130:
h = 15
if x<130:
h=15
self.pub_coords([x, y, 90-h, -178.9, -1.57, -66], 25, 1)
time.sleep(1.5)
# open pump
@ -237,11 +245,11 @@ class Object_detect(Movement):
y += 5
# print x,y
elif "dev" in self.robot_jes:
if y < 0:
x += 5
y += 3
y += 10
print x, y
if y<0:
x+=5
y+=3
y+=10
print x,y
self.move(x, y, color)
# init mycobot
@ -476,6 +484,7 @@ def run():
for i, j, k in os.walk(path):
for l in k:
goal.append(cv2.imread('local_photo/img/{}'.format(l)))
cap_num = 0
cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
if not cap.isOpened():

530
mycobot_ai/scripts/detect_obj_img_folder.py Executable file
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@ -0,0 +1,530 @@
# encoding:utf-8
#!/usr/bin/env python2
from cgi import parse
from difflib import restore
# import queue
from sys import path
from tokenize import Pointfloat
from turtle import color
# from typing_extensions import Self
import cv2
import numpy as np
import time
import json
import os
import rospy
from visualization_msgs.msg import Marker
from PIL import Image
from threading import Thread
import tkFileDialog as filedialog
import Tkinter as tk
from moving_utils import Movement
IS_CV_4 = cv2.__version__[0] == '4'
__version__ = "1.0" # Adaptive seeed
class Object_detect(Movement):
def __init__(self, camera_x=150, camera_y=-10):
# inherit the parent class
super(Object_detect, self).__init__()
# get path of file
dir_path = os.path.dirname(__file__)
# 移动角度
self.move_angles = [
[-7.11, -6.94, -55.01, -24.16, 0, 15], # init the point
[-1.14, -10.63, -87.8, 9.05, -3.07, 15], # point to grab
[17.4, -10.1, -87.27, 5.8, -2.02, 15], # point to grab
]
# 移动坐标
self.move_coords = [
[120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket
# above the yello bucket
#[208.2, -127.8, 260.9, -157.51, -17.5, -71.18],
[205.6, -130.5, 263.0, -150.99, -0.07, -107.35], # above the green bucket
[-20.0, 176.7, 242.6, -166.66, -9.44, -52.47], # above the gray bucket
[104.9, 176.7, 242.6, -166.66, -9.44, -52.47], # above the blue bucket
[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
]
# 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
self.raspi = False
import RPi.GPIO as GPIO
self.GPIO = GPIO
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(20, GPIO.OUT)
GPIO.setup(21, GPIO.OUT)
self.gpio_status(False)
self.Pin = [2, 5]
# choose place to set cube
self.color = 0
# parameters to calculate camera clipping parameters
self.x1 = self.x2 = self.y1 = self.y2 = 0
# set cache of real coord
self.cache_x = self.cache_y = 0
# load model of img recognition
# self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb")
# self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt")
# self.label_path = os.path.join(dir_path, "labels.json")
# # load class labels
# self.labels = json.load(open(self.label_path))
# use to calculate coord between cube and mycobot
self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
# The coordinates of the grab center point relative to the mycobot
self.camera_x, self.camera_y = camera_x, camera_y
# The coordinates of the cube relative to the mycobot
self.c_x, self.c_y = 0, 0
# The ratio of pixels to actual values
self.ratio = 0
# Get ArUco marker dict that can be detected.
self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
# Get ArUco marker params.
self.aruco_params = cv2.aruco.DetectorParameters_create()
# if IS_CV_4:
# self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path)
# else:
# print('Load tensorflow model need the version of opencv is 4.')
# exit(0)
# init a node and a publisher
rospy.init_node("marker", anonymous=True)
self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
# init a Marker
self.marker = Marker()
self.marker.header.frame_id = "/joint1"
self.marker.ns = "cube"
self.marker.type = self.marker.CUBE
self.marker.action = self.marker.ADD
self.marker.scale.x = 0.04
self.marker.scale.y = 0.04
self.marker.scale.z = 0.04
self.marker.color.a = 1.0
self.marker.color.g = 1.0
self.marker.color.r = 1.0
# marker position initial
self.marker.pose.position.x = 0
self.marker.pose.position.y = 0
self.marker.pose.position.z = 0.03
self.marker.pose.orientation.x = 0
self.marker.pose.orientation.y = 0
self.marker.pose.orientation.z = 0
self.marker.pose.orientation.w = 1.0
self.cache_x = self.cache_y = 0
# publish marker
def pub_marker(self, x, y, z=0.03):
self.marker.header.stamp = rospy.Time.now()
self.marker.pose.position.x = x
self.marker.pose.position.y = y
self.marker.pose.position.z = z
self.marker.color.g = self.color
self.pub.publish(self.marker)
def gpio_status(self, flag):
if flag:
self.GPIO.output(20, 0)
self.GPIO.output(21, 0)
else:
self.GPIO.output(20, 1)
self.GPIO.output(21, 1)
# Grasping motion
def move(self, x, y, color):
# send Angle to move mycobot
self.pub_angles(self.move_angles[0], 20)
time.sleep(1.5)
self.pub_angles(self.move_angles[1], 20)
time.sleep(1.5)
self.pub_angles(self.move_angles[2], 20)
time.sleep(1.5)
# send coordinates to move mycobot
self.pub_coords([x, y, 165, -178.9, -1.57, -66], 20, 1)
time.sleep(1.5)
# 根据不同底板机械臂，调整吸泵高度
self.pub_coords([x, y, 90, -178.9, -1.57, -66], 25, 1)
time.sleep(1.5)
# open pump
self.gpio_status(True)
time.sleep(0.5)
self.pub_angles(self.move_angles[2], 20)
time.sleep(3)
self.pub_marker(self.move_coords[2][0] / 1000.0,
self.move_coords[2][1] / 1000.0,
self.move_coords[2][2] / 1000.0)
self.pub_angles(self.move_angles[1], 20)
time.sleep(1.5)
self.pub_marker(self.move_coords[3][0] / 1000.0,
self.move_coords[3][1] / 1000.0,
self.move_coords[3][2] / 1000.0)
self.pub_angles(self.move_angles[0], 20)
time.sleep(1.5)
self.pub_marker(self.move_coords[4][0] / 1000.0,
self.move_coords[4][1] / 1000.0,
self.move_coords[4][2] / 1000.0)
print(self.move_coords[color])
self.pub_coords(self.move_coords[color], 20, 1)
self.pub_marker(self.move_coords[color][0] / 1000.0,
self.move_coords[color][1] / 1000.0,
self.move_coords[color][2] / 1000.0)
time.sleep(4)
# close pump
self.gpio_status(False)
time.sleep(1)
self.pub_marker(self.move_coords[color][0] / 1000.0 + 0.04,
self.move_coords[color][1] / 1000.0 - 0.02)
self.pub_angles(self.move_angles[0], 20)
time.sleep(3)
# decide whether grab cube
def decide_move(self, x, y, color):
print(x, y, self.cache_x, self.cache_y)
# detect the cube status move or run
if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
self.cache_x, self.cache_y = x, y
return
else:
self.cache_x = self.cache_y = 0
# 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动
print(x, y)
self.move(x, y, color)
# init mycobot
def run(self):
for _ in range(5):
self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20)
print(_)
time.sleep(0.5)
# draw aruco
def draw_marker(self, img, x, y):
# draw rectangle on img
cv2.rectangle(
img,
(x - 20, y - 20),
(x + 20, y + 20),
(0, 255, 0),
thickness=2,
lineType=cv2.FONT_HERSHEY_COMPLEX,
)
# add text on rectangle
cv2.putText(
img,
"({},{})".format(x, y),
(x, y),
cv2.FONT_HERSHEY_COMPLEX_SMALL,
1,
(243, 0, 0),
2,
)
# get points of two aruco
def get_calculate_params(self, img):
# Convert the image to a gray image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detect ArUco marker.
corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
gray, self.aruco_dict, parameters=self.aruco_params)
"""
Two Arucos must be present in the picture and in the same order.
There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
Determine the center of the aruco by the four corners of the aruco.
"""
if len(corners) > 0:
if ids is not None:
if len(corners) <= 1 or ids[0] == 1:
return None
x1 = x2 = y1 = y2 = 0
point_11, point_21, point_31, point_41 = corners[0][0]
x1, y1 = int(
(point_11[0] + point_21[0] + point_31[0] + point_41[0]) /
4.0), int(
(point_11[1] + point_21[1] + point_31[1] + point_41[1])
/ 4.0)
point_1, point_2, point_3, point_4 = corners[1][0]
x2, y2 = int(
(point_1[0] + point_2[0] + point_3[0] + point_4[0]) /
4.0), int(
(point_1[1] + point_2[1] + point_3[1] + point_4[1]) /
4.0)
return x1, x2, y1, y2
return None
# set camera clipping parameters
def set_cut_params(self, x1, y1, x2, y2):
self.x1 = int(x1)
self.y1 = int(y1)
self.x2 = int(x2)
self.y2 = int(y2)
print(self.x1, self.y1, self.x2, self.y2)
# set parameters to calculate the coords between cube and mycobot
def set_params(self, c_x, c_y, ratio):
self.c_x = c_x
self.c_y = c_y
self.ratio = 220.0 / ratio
# calculate the coords between cube and mycobot
def get_position(self, x, y):
return ((y - self.c_y) * self.ratio +
self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y)
"""
Calibrate the camera according to the calibration parameters.
Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
If two ARuco values have been calculated, clip the video.
"""
def transform_frame(self, frame):
# enlarge the image by 1.5 times
fx = 1.5
fy = 1.5
frame = cv2.resize(frame, (0, 0),
fx=fx,
fy=fy,
interpolation=cv2.INTER_CUBIC)
if self.x1 != self.x2:
# the cutting ratio here is adjusted according to the actual situation
frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15),
int(self.x1 * 0.7):int(self.x2 * 1.15)]
return frame
# according the class_id to get object name
def id_class_name(self, class_id):
for key, value in self.labels.items():
if class_id == int(key):
return value
# detect object
def obj_detect(self, img, goal):
i = 0
MIN_MATCH_COUNT = 5
sift = cv2.xfeatures2d.SIFT_create()
# find the keypoints and descriptors with SIFT
kp = []
des = []
for i in goal:
kp0, des0 = sift.detectAndCompute(i, None)
kp.append(kp0)
des.append(des0)
# kp1, des1 = sift.detectAndCompute(goal, None)
kp2, des2 = sift.detectAndCompute(img, None)
# FLANN parameters
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params, search_params)
x, y = 0, 0
try:
for i in range(len(des)):
matches = flann.knnMatch(des[i], des2, k=2)
# store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。
good = []
for m, n in matches:
if m.distance < 0.7 * n.distance:
good.append(m)
# When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时
if len(good) > MIN_MATCH_COUNT:
# extract corresponding point pairs from matching 从匹配中提取出对应点对
# query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引
src_pts = np.float32([kp[i][m.queryIdx].pt
for m in good]).reshape(-1, 1, 2)
dst_pts = np.float32([kp2[m.trainIdx].pt
for m in good]).reshape(-1, 1, 2)
# Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,
5.0)
matchesMask = mask.ravel().tolist()
# Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置
h, w, d = goal[i].shape
pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1],
[w - 1, 0]]).reshape(-1, 1, 2)
dst = cv2.perspectiveTransform(pts, M)
ccoord = (dst[0][0] + dst[1][0] + dst[2][0] +
dst[3][0]) / 4.0
cv2.putText(img,
"{}".format(ccoord), (50, 60),
fontFace=None,
fontScale=1,
color=(0, 255, 0),
lineType=1)
print(format(dst[0][0][0]))
x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] +
dst[3][0][0]) / 4.0
y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] +
dst[3][0][1]) / 4.0
# bound box 绘制边框
img = cv2.polylines(img, [np.int32(dst)], True, 244, 3,
cv2.LINE_AA)
# cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA)
except Exception as e:
pass
# else:
# if(len(good) < MIN_MATCH_COUNT):
# i += 1
# if(i % 10 == 0):
# print("Not enough matches are found - %d/%d" %
# (len(good), MIN_MATCH_COUNT))
# matchesMask = None
if x + y > 0:
return x, y
else:
return None
# The path to save the image folder
def parse_folder(folder):
restore = []
path = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/' + folder
for i, j, k in os.walk(path):
for l in k:
restore.append(cv2.imread(folder + '/{}'.format(l)))
return restore
def run():
# Object_detect().take_photo()
# Object_detect().cut_photo()
# goal = Object_detect().distinguist()
res_queue = [[], [], [], []]
res_queue[0] = parse_folder('res/red')
res_queue[1] = parse_folder('res/green')
res_queue[2] = parse_folder('res/gray')
res_queue[3] = parse_folder('res/blue')
cap_num = 0
cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
if not cap.isOpened():
cap.open()
# init a class of Object_detect
detect = Object_detect()
# init mycobot
detect.run()
# _init_ = 20 #
init_num = 0
nparams = 0
num = 0
real_sx = real_sy = 0
while cv2.waitKey(1) < 0:
start_time = time.time()
# read camera
_, frame = cap.read()
# deal img
frame = detect.transform_frame(frame)
# if _init_ > 0:
# _init_ -= 1
# continue
# calculate the parameters of camera clipping
if init_num < 20:
if detect.get_calculate_params(frame) is None:
cv2.imshow("figure", frame)
continue
else:
x1, x2, y1, y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame, x1, y1)
detect.draw_marker(frame, x2, y2)
detect.sum_x1 += x1
detect.sum_x2 += x2
detect.sum_y1 += y1
detect.sum_y2 += y2
init_num += 1
continue
elif init_num == 20:
detect.set_cut_params(
(detect.sum_x1) / 20.0,
(detect.sum_y1) / 20.0,
(detect.sum_x2) / 20.0,
(detect.sum_y2) / 20.0,
)
detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
init_num += 1
continue
# calculate params of the coords between cube and mycobot
if nparams < 10:
if detect.get_calculate_params(frame) is None:
cv2.imshow("figure", frame)
continue
else:
x1, x2, y1, y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame, x1, y1)
detect.draw_marker(frame, x2, y2)
detect.sum_x1 += x1
detect.sum_x2 += x2
detect.sum_y1 += y1
detect.sum_y2 += y2
nparams += 1
print "ok"
continue
elif nparams == 10:
nparams += 1
# calculate and set params of calculating real coord between cube and mycobot
detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0,
(detect.sum_y1 + detect.sum_y2) / 20.0,
abs(detect.sum_x1 - detect.sum_x2) / 10.0 +
abs(detect.sum_y1 - detect.sum_y2) / 10.0)
print("ok")
continue
# get detect result
for i, v in enumerate(res_queue):
detect_result = detect.obj_detect(frame, v)
if detect_result is None:
cv2.imshow("figure", frame)
continue
else:
x, y = detect_result
# calculate real coord between cube and mycobot
real_x, real_y = detect.get_position(x, y)
if num == 5:
detect.color = i
detect.pub_marker(real_sx / 5.0 / 1000.0,
real_sy / 5.0 / 1000.0)
detect.decide_move(real_sx / 5.0, real_sy / 5.0,
detect.color)
num = real_sx = real_sy = 0
else:
num += 1
real_sy += real_y
real_sx += real_x
cv2.imshow("figure", frame)
end_time = time.time()
print("loop_time = ", end_time - start_time)
if __name__ == "__main__":
run()
# Object_detect().take_photo()
# Object_detect().cut_photo()

648
mycobot_ai/scripts/detect_obj_img_folder_opt.py Normal file
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@ -0,0 +1,648 @@
# encoding:utf-8
#!/usr/bin/env python2
from multiprocessing import Process, Pipe
from cgi import parse
from difflib import restore
# import queue
from sys import path
from tokenize import Pointfloat
from turtle import color
# from typing_extensions import Self
import cv2
import numpy as np
import time
import json
import os
import rospy
from visualization_msgs.msg import Marker
from PIL import Image
from threading import Thread
import tkFileDialog as filedialog
import Tkinter as tk
from moving_utils import Movement
IS_CV_4 = cv2.__version__[0] == '4'
__version__ = "1.0" # Adaptive seeed
class Object_detect(Movement):
def __init__(self, camera_x=150, camera_y=-10):
# inherit the parent class
super(Object_detect, self).__init__()
# get path of file
dir_path = os.path.dirname(__file__)
# 移动角度
self.move_angles = [
[-26.11, -6.94, -55.01, -24.16, 0, 15], # init the point
[-1.14, 0.63, -87.8, 9.05, -3.07, 15], # point to grab
[17.4, -10.1, -87.27, 5.8, -2.02, 15], # point to grab
]
# 移动坐标
self.move_coords = [
[120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket
# above the yello bucket
#[208.2, -127.8, 260.9, -157.51, -17.5, -71.18],
[205.6, -130.5, 263.0, -150.99, -0.07, -107.35], # above the green bucket
[-20.0, 176.7, 242.6, -166.66, -9.44, -52.47], # above the gray bucket
[104.9, 176.7, 242.6, -166.66, -9.44, -52.47], # above the blue bucket
[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
]
# 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
self.raspi = False
import RPi.GPIO as GPIO
self.GPIO = GPIO
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(20, GPIO.OUT)
GPIO.setup(21, GPIO.OUT)
self.gpio_status(False)
self.Pin = [2, 5]
# choose place to set cube
self.color = 0
# parameters to calculate camera clipping parameters
self.x1 = self.x2 = self.y1 = self.y2 = 0
# set cache of real coord
self.cache_x = self.cache_y = 0
# load model of img recognition
# self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb")
# self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt")
# self.label_path = os.path.join(dir_path, "labels.json")
# # load class labels
# self.labels = json.load(open(self.label_path))
# use to calculate coord between cube and mycobot
self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
# The coordinates of the grab center point relative to the mycobot
self.camera_x, self.camera_y = camera_x, camera_y
# The coordinates of the cube relative to the mycobot
self.c_x, self.c_y = 0, 0
# The ratio of pixels to actual values
self.ratio = 0
# Get ArUco marker dict that can be detected.
self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
# Get ArUco marker params.
self.aruco_params = cv2.aruco.DetectorParameters_create()
# if IS_CV_4:
# self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path)
# else:
# print('Load tensorflow model need the version of opencv is 4.')
# exit(0)
# init a node and a publisher
rospy.init_node("marker", anonymous=True)
self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
# init a Marker
self.marker = Marker()
self.marker.header.frame_id = "/joint1"
self.marker.ns = "cube"
self.marker.type = self.marker.CUBE
self.marker.action = self.marker.ADD
self.marker.scale.x = 0.04
self.marker.scale.y = 0.04
self.marker.scale.z = 0.04
self.marker.color.a = 1.0
self.marker.color.g = 1.0
self.marker.color.r = 1.0
# marker position initial
self.marker.pose.position.x = 0
self.marker.pose.position.y = 0
self.marker.pose.position.z = 0.03
self.marker.pose.orientation.x = 0
self.marker.pose.orientation.y = 0
self.marker.pose.orientation.z = 0
self.marker.pose.orientation.w = 1.0
self.cache_x = self.cache_y = 0
# publish marker
def pub_marker(self, x, y, z=0.03):
self.marker.header.stamp = rospy.Time.now()
self.marker.pose.position.x = x
self.marker.pose.position.y = y
self.marker.pose.position.z = z
self.marker.color.g = self.color
self.pub.publish(self.marker)
def gpio_status(self, flag):
if flag:
self.GPIO.output(20, 0)
self.GPIO.output(21, 0)
else:
self.GPIO.output(20, 1)
self.GPIO.output(21, 1)
# Grasping motion
def move(self, x, y, color):
# send Angle to move mycobot
self.pub_angles(self.move_angles[0], 20)
time.sleep(1.5)
self.pub_angles(self.move_angles[1], 20)
time.sleep(1.5)
self.pub_angles(self.move_angles[2], 20)
time.sleep(1.5)
# send coordinates to move mycobot
self.pub_coords([x, y, 165, -178.9, -1.57, -66], 20, 1)
time.sleep(1.5)
# 根据不同底板机械臂，调整吸泵高度
self.pub_coords([x, y, 90, -178.9, -1.57, -66], 25, 1)
time.sleep(1.5)
# open pump
self.gpio_status(True)
time.sleep(0.5)
self.pub_angles(self.move_angles[2], 20)
time.sleep(3)
self.pub_marker(self.move_coords[2][0] / 1000.0,
self.move_coords[2][1] / 1000.0,
self.move_coords[2][2] / 1000.0)
self.pub_angles(self.move_angles[1], 20)
time.sleep(1.5)
self.pub_marker(self.move_coords[3][0] / 1000.0,
self.move_coords[3][1] / 1000.0,
self.move_coords[3][2] / 1000.0)
self.pub_angles(self.move_angles[0], 20)
time.sleep(1.5)
self.pub_marker(self.move_coords[4][0] / 1000.0,
self.move_coords[4][1] / 1000.0,
self.move_coords[4][2] / 1000.0)
print(self.move_coords[color])
self.pub_coords(self.move_coords[color], 20, 1)
self.pub_marker(self.move_coords[color][0] / 1000.0,
self.move_coords[color][1] / 1000.0,
self.move_coords[color][2] / 1000.0)
time.sleep(4)
# close pump
self.gpio_status(False)
time.sleep(1)
self.pub_marker(self.move_coords[color][0] / 1000.0 + 0.04,
self.move_coords[color][1] / 1000.0 - 0.02)
self.pub_angles(self.move_angles[0], 20)
time.sleep(3)
# decide whether grab cube
def decide_move(self, x, y, color):
print(x, y, self.cache_x, self.cache_y)
# detect the cube status move or run
if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
self.cache_x, self.cache_y = x, y
return
else:
self.cache_x = self.cache_y = 0
# 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动
print(x, y)
self.move(x, y, color)
# init mycobot
def run(self):
for _ in range(5):
self.pub_angles([-26.11, -6.94, -55.01, -24.16, 0, -15], 20)
print(_)
time.sleep(0.5)
# draw aruco
def draw_marker(self, img, x, y):
# draw rectangle on img
cv2.rectangle(
img,
(x - 20, y - 20),
(x + 20, y + 20),
(0, 255, 0),
thickness=2,
lineType=cv2.FONT_HERSHEY_COMPLEX,
)
# add text on rectangle
cv2.putText(
img,
"({},{})".format(x, y),
(x, y),
cv2.FONT_HERSHEY_COMPLEX_SMALL,
1,
(243, 0, 0),
2,
)
# get points of two aruco
def get_calculate_params(self, img):
# Convert the image to a gray image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detect ArUco marker.
corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
gray, self.aruco_dict, parameters=self.aruco_params)
"""
Two Arucos must be present in the picture and in the same order.
There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
Determine the center of the aruco by the four corners of the aruco.
"""
if len(corners) > 0:
if ids is not None:
if len(corners) <= 1 or ids[0] == 1:
return None
x1 = x2 = y1 = y2 = 0
point_11, point_21, point_31, point_41 = corners[0][0]
x1, y1 = int(
(point_11[0] + point_21[0] + point_31[0] + point_41[0]) /
4.0), int(
(point_11[1] + point_21[1] + point_31[1] + point_41[1])
/ 4.0)
point_1, point_2, point_3, point_4 = corners[1][0]
x2, y2 = int(
(point_1[0] + point_2[0] + point_3[0] + point_4[0]) /
4.0), int(
(point_1[1] + point_2[1] + point_3[1] + point_4[1]) /
4.0)
return x1, x2, y1, y2
return None
# set camera clipping parameters
def set_cut_params(self, x1, y1, x2, y2):
self.x1 = int(x1)
self.y1 = int(y1)
self.x2 = int(x2)
self.y2 = int(y2)
print(self.x1, self.y1, self.x2, self.y2)
# set parameters to calculate the coords between cube and mycobot
def set_params(self, c_x, c_y, ratio):
self.c_x = c_x
self.c_y = c_y
self.ratio = 220.0 / ratio
# calculate the coords between cube and mycobot
def get_position(self, x, y):
return ((y - self.c_y) * self.ratio +
self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y)
"""
Calibrate the camera according to the calibration parameters.
Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
If two ARuco values have been calculated, clip the video.
"""
def transform_frame(self, frame):
# enlarge the image by 1.5 times
fx = 1.5
fy = 1.5
frame = cv2.resize(frame, (0, 0),
fx=fx,
fy=fy,
interpolation=cv2.INTER_CUBIC)
if self.x1 != self.x2:
# the cutting ratio here is adjusted according to the actual situation
frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15),
int(self.x1 * 0.7):int(self.x2 * 1.15)]
return frame
# according the class_id to get object name
def id_class_name(self, class_id):
for key, value in self.labels.items():
if class_id == int(key):
return value
# detect object
def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection):
i = 0
MIN_MATCH_COUNT = 5
# sift = cv2.xfeatures2d.SIFT_create()
# find the keypoints and descriptors with SIFT
# kp = []
# des = []
kp = kp_list
des = desc_list
# for i in goal:
# kp0, des0 = sift.detectAndCompute(i, None)
# kp.append(kp0)
# des.append(des0)
# kp1, des1 = sift.detectAndCompute(goal, None)
# kp2, des2 = sift.detectAndCompute(img, None)
kp2, des2 = kp_img, desc_img
# FLANN parameters
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params, search_params)
x, y = 0, 0
try:
for i in range(len(des)):
matches = flann.knnMatch(des[i], des2, k=2)
# store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。
good = []
for m, n in matches:
if m.distance < 0.7 * n.distance:
good.append(m)
# When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时
if len(good) > MIN_MATCH_COUNT:
# extract corresponding point pairs from matching 从匹配中提取出对应点对
# query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引
src_pts = np.float32([kp[i][m.queryIdx].pt
for m in good]).reshape(-1, 1, 2)
dst_pts = np.float32([kp2[m.trainIdx].pt
for m in good]).reshape(-1, 1, 2)
# Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,
5.0)
matchesMask = mask.ravel().tolist()
# Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置
h, w, d = goal[i].shape
pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1],
[w - 1, 0]]).reshape(-1, 1, 2)
dst = cv2.perspectiveTransform(pts, M)
coord = (dst[0][0] + dst[1][0] + dst[2][0] +
dst[3][0]) / 4.0
connection.send((DRAW_COORDS, coord))
# cv2.putText(img, "{}".format(coord), (50, 60),
# fontFace=None, fontScale=1,
# color=(0, 255, 0), lineType=1)
print(format(dst[0][0][0]))
x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] +
dst[3][0][0]) / 4.0
y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] +
dst[3][0][1]) / 4.0
# bound box 绘制边框
# img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA)
connection.send((DRAW_RECT, dst))
# cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA)
except Exception as e:
pass
# else:
# if(len(good) < MIN_MATCH_COUNT):
# i += 1
# if(i % 10 == 0):
# print("Not enough matches are found - %d/%d" %
# (len(good), MIN_MATCH_COUNT))
# matchesMask = None
if x + y > 0:
return x, y
else:
return None
# The path to save the image folder
def parse_folder(folder):
restore = []
path = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/' + folder
for i, j, k in os.walk(path):
for l in k:
restore.append(cv2.imread(folder + '/{}'.format(l)))
return restore
def compute_keypoints_and_descriptors(sift, images_lists):
kp_list = []
desc_list = []
for images in images_lists:
kp_tmp = []
desc_tmp = []
for img in images:
kp, desc = sift.detectAndCompute(img, None)
kp_tmp.append(kp)
desc_tmp.append(desc)
kp_list.append(kp_tmp)
desc_list.append(desc_tmp)
return kp_list, desc_list
GET_FRAME = 1
STOP_PROCESSING = 2
DRAW_COORDS = 3
DRAW_RECT = 4
CLEAR_DRAW = 5
CROP_FRAME = 6
def get_frame(connection):
connection.send(GET_FRAME)
frame = connection.recv()
return frame
def process_transform_frame(frame, x1, y1, x2, y2):
# enlarge the image by 1.5 times
fx = 1.5
fy = 1.5
frame = cv2.resize(frame, (0, 0),
fx=fx,
fy=fy,
interpolation=cv2.INTER_CUBIC)
# if x1 != x2:
# the cutting ratio here is adjusted according to the actual situation
# frame = frame[int(y2 * 0.2):int(y1 * 1.15),
# int(x1 * 0.7):int(x2 * 1.15)]
return frame
def process_display_frame(connection):
cap_num = 0
coord = None
dst = None
x1 = 0
y1 = 0
x2 = 0
y2 = 0
cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
if not cap.isOpened():
cap.open()
while cv2.waitKey(1) < 0:
_, frame = cap.read()
frame = process_transform_frame(frame, x1, y1, x2, y2)
if connection.poll():
request = connection.recv()
if request == GET_FRAME:
connection.send(frame)
elif request == CLEAR_DRAW:
coord = None
dst = None
elif type(request) is tuple:
if request[0] == DRAW_COORDS:
coord = request[1]
elif request[0] == DRAW_RECT:
dst = request[1]
elif request[0] == CROP_FRAME:
x1 = request[1]
y1 = request[2]
x2 = request[3]
y2 = request[4]
if not coord is None:
cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None,
fontScale=1, color=(0, 255, 0), lineType=1)
if not dst is None:
frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA)
cv2.imshow("figure", frame)
time.sleep(0.04)
connection.send(STOP_PROCESSING)
def run():
parent_conn, child_conn = Pipe()
child = Process(target=process_display_frame, args=(child_conn,))
child.start()
# Object_detect().take_photo()
# Object_detect().cut_photo()
# goal = Object_detect().distinguist()
res_queue = [[], [], [], []]
res_queue[0] = parse_folder('res/red')
res_queue[1] = parse_folder('res/green')
res_queue[2] = parse_folder('res/gray')
res_queue[3] = parse_folder('res/blue')
# res_queue = []
# res_queue.extend(parse_folder('res/red'))
# res_queue.extend(parse_folder('res/green'))
# res_queue.extend(parse_folder('res/gray'))
# res_queue.extend(parse_folder('res/blue'))
sift = cv2.xfeatures2d.SIFT_create()
kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue)
# init a class of Object_detect
detect = Object_detect()
# init mycobot
detect.run()
# _init_ = 20 #
init_num = 0
nparams = 0
# num = 0
# real_sx = real_sy = 0
while True:
start_time = time.time()
if parent_conn.poll():
data = parent_conn.recv()
if data == STOP_PROCESSING:
break
# read camera
frame = get_frame(parent_conn)
# deal img
#frame = detect.transform_frame(frame)
# if _init_ > 0:
# _init_ -= 1
# continue
# calculate the parameters of camera clipping
if init_num < 20:
if detect.get_calculate_params(frame) is None:
# cv2.imshow("figure", frame)
continue
else:
x1, x2, y1, y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame, x1, y1)
detect.draw_marker(frame, x2, y2)
detect.sum_x1 += x1
detect.sum_x2 += x2
detect.sum_y1 += y1
detect.sum_y2 += y2
init_num += 1
continue
elif init_num == 20:
detect.set_cut_params(
(detect.sum_x1) / 20.0,
(detect.sum_y1) / 20.0,
(detect.sum_x2) / 20.0,
(detect.sum_y2) / 20.0,
)
parent_conn.send((CROP_FRAME,
(detect.sum_x1) / 20.0,
(detect.sum_y1) / 20.0,
(detect.sum_x2) / 20.0,
(detect.sum_y2) / 20.0))
detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
init_num += 1
continue
# calculate params of the coords between cube and mycobot
if nparams < 10:
if detect.get_calculate_params(frame) is None:
# cv2.imshow("figure", frame)
continue
else:
x1, x2, y1, y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame, x1, y1)
detect.draw_marker(frame, x2, y2)
detect.sum_x1 += x1
detect.sum_x2 += x2
detect.sum_y1 += y1
detect.sum_y2 += y2
nparams += 1
print "ok"
continue
elif nparams == 10:
nparams += 1
# calculate and set params of calculating real coord between cube and mycobot
detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0,
(detect.sum_y1 + detect.sum_y2) / 20.0,
abs(detect.sum_x1 - detect.sum_x2) / 10.0 +
abs(detect.sum_y1 - detect.sum_y2) / 10.0)
print("ok")
continue
# get detect result
kp_img, desc_img = sift.detectAndCompute(frame, None)
frame = get_frame(parent_conn)
for i, v in enumerate(res_queue):
# HACK: to update frame every time
detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn)
if detect_result:
x, y = detect_result
# calculate real coord between cube and mycobot
real_x, real_y = detect.get_position(x, y)
detect.color = i
detect.pub_marker(real_x / 1000.0, real_y / 1000.0)
detect.decide_move(real_x, real_y, detect.color)
# if num == 5:
# detect.color = i
# detect.pub_marker(real_sx / 5.0 / 1000.0,
# real_sy / 5.0 / 1000.0)
# detect.decide_move(real_sx / 5.0, real_sy / 5.0,
# detect.color)
# num = real_sx = real_sy = 0
# else:
# num += 1
# real_sy += real_y
# real_sx += real_x
parent_conn.send(CLEAR_DRAW)
# cv2.imshow("figure", frame)
time.sleep(0.05)
end_time = time.time()
print("loop_time = ", end_time - start_time)
child.join()
if __name__ == "__main__":
run()
# Object_detect().take_photo()
# Object_detect().cut_photo()

406
mycobot_ai/scripts/detect_obj_img_wio.py Executable file
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@ -0,0 +1,406 @@
#encoding:utf-8
from tokenize import Pointfloat
import cv2
import numpy as np
import time
import json
import os
import rospy
from visualization_msgs.msg import Marker
from moving_utils import Movement
IS_CV_4 = cv2.__version__[0] == '4'
class Object_detect(Movement):
def __init__(self, camera_x=150, camera_y=-10):
# inherit the parent class
super(Object_detect, self).__init__()
# get path of file
dir_path = os.path.dirname(__file__)
# choose place to set cube
self.color = 0
# parameters to calculate camera clipping parameters
self.x1 = self.x2 = self.y1 = self.y2 =0
# set cache of real coord
self.cache_x = self.cache_y = 0
# load model of img recognition
self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb")
self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt")
self.label_path = os.path.join(dir_path, "labels.json")
# load class labels
self.labels = json.load(open(self.label_path))
# use to calculate coord between cube and mycobot
self.sum_x1= self.sum_x2= self.sum_y2= self.sum_y1= 0
# The coordinates of the grab center point relative to the mycobot
self.camera_x, self.camera_y = camera_x, camera_y
# The coordinates of the cube relative to the mycobot
self.c_x, self.c_y = 0,0
# The ratio of pixels to actual values
self.ratio = 0
# Get ArUco marker dict that can be detected.
self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
# Get ArUco marker params.
self.aruco_params = cv2.aruco.DetectorParameters_create()
if IS_CV_4:
self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path)
else:
print('Load tensorflow model need the version of opencv is 4.')
exit(0)
# init a node and a publisher
rospy.init_node("marker", anonymous=True)
self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
# init a Marker
self.marker = Marker()
self.marker.header.frame_id = "/joint1"
self.marker.ns = "cube"
self.marker.type = self.marker.CUBE
self.marker.action = self.marker.ADD
self.marker.scale.x = 0.04
self.marker.scale.y = 0.04
self.marker.scale.z = 0.04
self.marker.color.a = 1.0
self.marker.color.g = 1.0
self.marker.color.r = 1.0
# marker position initial
self.marker.pose.position.x = 0
self.marker.pose.position.y = 0
self.marker.pose.position.z = 0.03
self.marker.pose.orientation.x = 0
self.marker.pose.orientation.y = 0
self.marker.pose.orientation.z = 0
self.marker.pose.orientation.w = 1.0
self.cache_x = self.cache_y = 0
# publish marker
def pub_marker(self, x, y , z=0.03):
self.marker.header.stamp = rospy.Time.now()
self.marker.pose.position.x = x
self.marker.pose.position.y = y
self.marker.pose.position.z = z
self.marker.color.g = self.color
self.pub.publish(self.marker)
# Grasping motion
def move(self, x,y,color):
angles = [
[-7.11, -6.94, -55.01, -24.16, 0, -38.84], # init the point
[-1.14, -10.63, -87.8, 9.05, -3.07, -37.7], # point to grab
[17.4, -10.1, -87.27, 5.8, -2.02, -37.7], # point to grab
]
coords = [
[106.1, -141.6, 240.9, -173.34, -8.15, -83.11], # above the red bucket
[208.2, -127.8, 246.9, -157.51, -17.5, -71.18], # above the green bucket
[209.7, -18.6, 230.4, -168.48, -9.86, -39.38],
[196.9, -64.7, 232.6, -166.66, -9.44, -52.47],
[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
]
# send Angle to move mycobot
self.pub_angles(angles[0], 20)
time.sleep(1.5)
self.pub_angles(angles[1], 20)
time.sleep(1.5)
self.pub_angles(angles[2], 20)
time.sleep(1.5)
# send coordinates to move mycobot
self.pub_coords([x, y, 165, -178.9, -1.57, -25.95], 20, 1)
time.sleep(1.5)
self.pub_coords([x, y, 40, -178.9, -1.57, -25.95], 20, 1)
time.sleep(1.5)
# open pump
self.pub_pump(True)
time.sleep(0.5)
self.pub_angles(angles[2], 20)
time.sleep(3)
self.pub_marker(coords[2][0]/1000.0, coords[2][1]/1000.0, coords[2][2]/1000.0)
self.pub_angles(angles[1], 20)
time.sleep(1.5)
self.pub_marker(coords[3][0]/1000.0, coords[3][1]/1000.0, coords[3][2]/1000.0)
self.pub_angles(angles[0], 20)
time.sleep(1.5)
self.pub_marker(coords[4][0]/1000.0, coords[4][1]/1000.0, coords[4][2]/1000.0)
self.pub_coords(coords[color], 20, 1)
self.pub_marker(coords[color][0]/1000.0, coords[color][1]/1000.0, coords[color][2]/1000.0)
time.sleep(2)
# close pump
self.pub_pump(False)
if color==1:
self.pub_marker(coords[color][0]/1000.0+0.04, coords[color][1]/1000.0-0.02)
elif color==0:
self.pub_marker(coords[color][0]/1000.0+0.03, coords[color][1]/1000.0)
self.pub_angles(angles[0], 20)
time.sleep(3)
# decide whether grab cube
def decide_move(self, x, y, color):
print(x, y,self.cache_x, self.cache_y)
# detect the cube status move or run
if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
self.cache_x, self.cache_y = x, y
return
else:
self.cache_x = self.cache_y = 0
self.move(x,y,color)
# init mycobot
def run(self):
for _ in range(10):
self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -38.84], 20)
print(_)
time.sleep(0.5)
self.pub_pump(False)
# draw aruco
def draw_marker(self,img,x,y):
# draw rectangle on img
cv2.rectangle(
img,
(x - 20, y - 20),
(x + 20, y + 20),
(0, 255, 0),
thickness=2,
lineType=cv2.FONT_HERSHEY_COMPLEX,
)
# add text on rectangle
cv2.putText(img,"({},{})".format(x,y),(x,y),cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,)
# get points of two aruco
def get_calculate_params(self,img):
# Convert the image to a gray image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detect ArUco marker.
corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
gray, self.aruco_dict, parameters=self.aruco_params
)
"""
Two Arucos must be present in the picture and in the same order.
There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
Determine the center of the aruco by the four corners of the aruco.
"""
if len(corners) > 0:
if ids is not None:
if len(corners) <= 1 or ids[0]==1:
return None
x1=x2=y1=y2 = 0
point_11,point_21,point_31,point_41 = corners[0][0]
x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int((point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0)
point_1,point_2,point_3,point_4 = corners[1][0]
x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int((point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0)
return x1,x2,y1,y2
return None
# set camera clipping parameters
def set_cut_params(self, x1, y1, x2, y2):
self.x1 = int(x1)
self.y1 = int(y1)
self.x2 = int(x2)
self.y2 = int(y2)
print(self.x1,self.y1,self.x2,self.y2)
# set parameters to calculate the coords between cube and mycobot
def set_params(self, c_x, c_y, ratio):
self.c_x = c_x
self.c_y = c_y
self.ratio = 220.0/ratio
# calculate the coords between cube and mycobot
def get_position(self, x, y):
return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y)
"""
Calibrate the camera according to the calibration parameters.
Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
If two ARuco values have been calculated, clip the video.
"""
def transform_frame(self, frame):
# enlarge the image by 1.5 times
fx = 1.5
fy = 1.5
frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy, interpolation=cv2.INTER_CUBIC)
if self.x1 != self.x2:
# the cutting ratio here is adjusted according to the actual situation
frame = frame[int(self.y2*0.2):int(self.y1*1.15), int(self.x1*0.7):int(self.x2*1.15)]
return frame
# according the class_id to get object name
def id_class_name(self, class_id):
for key, value in self.labels.items():
if class_id == int(key):
return value
# detect object
def obj_detect(self, frame):
rows, cols = frame.shape[:-1]
# Resize image and swap BGR to RGB.
blob = cv2.dnn.blobFromImage(
frame,
size=(300, 300),
mean=(0, 0, 0),
swapRB=True,
crop=False,
)
# Detecting.
self.net.setInput(blob)
out = self.net.forward()
x, y = 0, 0
# Processing result.
for detection in out[0, 0, :, :]:
score = float(detection[2])
if score > 0.3:
class_id = detection[1]
left = detection[3] * cols
top = detection[4] * rows
right = detection[5] * cols
bottom = detection[6] * rows
if abs(right + bottom - left - top) > 380:
continue
x, y = (left + right) / 2.0, (top + bottom) / 2.0
cv2.rectangle(
frame,
(int(left), int(top)),
(int(right), int(bottom)),
(0, 230, 0),
thickness=2,
)
cv2.putText(
frame,
"{}: {}%".format(self.id_class_name(class_id),round(score * 100, 2)),
(int(left), int(top) - 10),
cv2.FONT_HERSHEY_COMPLEX_SMALL,
1,
(243, 0, 0),
2,
)
if x+y > 0:
return x, y
else:
return None
if __name__ == "__main__":
# open the camera
cap_num = 0
cap = cv2.VideoCapture(cap_num)
if not cap.isOpened():
cap.open()
# init a class of Object_detect
detect = Object_detect()
# init mycobot
detect.run()
_init_ = 20 #
init_num = 0
nparams = 0
num = 0
real_sx = real_sy = 0
while cv2.waitKey(1) < 0:
# read camera
_,frame = cap.read()
# deal img
frame = detect.transform_frame(frame)
if _init_ > 0:
_init_-=1
continue
# calculate the parameters of camera clipping
if init_num < 20:
if detect.get_calculate_params(frame) is None:
cv2.imshow("figure",frame)
continue
else:
x1,x2,y1,y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame,x1,y1)
detect.draw_marker(frame,x2,y2)
detect.sum_x1+=x1
detect.sum_x2+=x2
detect.sum_y1+=y1
detect.sum_y2+=y2
init_num+=1
continue
elif init_num==20:
detect.set_cut_params(
(detect.sum_x1)/20.0,
(detect.sum_y1)/20.0,
(detect.sum_x2)/20.0,
(detect.sum_y2)/20.0,
)
detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
init_num+=1
continue
# calculate params of the coords between cube and mycobot
if nparams < 10:
if detect.get_calculate_params(frame) is None:
cv2.imshow("figure",frame)
continue
else:
x1,x2,y1,y2 = detect.get_calculate_params(frame)
detect.draw_marker(frame,x1,y1)
detect.draw_marker(frame,x2,y2)
detect.sum_x1+=x1
detect.sum_x2+=x2
detect.sum_y1+=y1
detect.sum_y2+=y2
nparams+=1
continue
elif nparams==10:
nparams+=1
# calculate and set params of calculating real coord between cube and mycobot
detect.set_params(
(detect.sum_x1+detect.sum_x2)/20.0,
(detect.sum_y1+detect.sum_y2)/20.0,
abs(detect.sum_x1-detect.sum_x2)/10.0+abs(detect.sum_y1-detect.sum_y2)/10.0
)
print "ok"
continue
# get detect result
detect_result = detect.obj_detect(frame)
if detect_result is None:
cv2.imshow("figure",frame)
continue
else:
x, y = detect_result
# calculate real coord between cube and mycobot
real_x, real_y = detect.get_position(x, y)
if num == 5:
detect.pub_marker(real_sx/5.0/1000.0, real_sy/5.0/1000.0)
detect.decide_move(real_sx/5.0, real_sy/5.0, detect.color)
num = real_sx = real_sy = 0
else:
num += 1
real_sy += real_y
real_sx += real_x
cv2.imshow("figure",frame)

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mycobot_ai/scripts/graph.pbtxt
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mycobot_ai/scripts/labels.json
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@ -1,82 +1,82 @@
{
"1": "person",
"2": "bicycle",
"3": "car",
"4": "motorcycle",
"5": "airplane",
"6": "bus",
"7": "train",
"8": "truck",
"9": "boat",
"10": "traffic light",
"11": "fire hydrant",
"13": "stop sign",
"14": "parking meter",
"15": "bench",
"16": "bird",
"17": "cat",
"18": "dog",
"19": "horse",
"20": "sheep",
"21": "cow",
"22": "elephant",
"23": "bear",
"24": "zebra",
"25": "giraffe",
"27": "backpack",
"28": "umbrella",
"31": "handbag",
"32": "tie",
"33": "suitcase",
"34": "frisbee",
"35": "skis",
"36": "snowboard",
"37": "sports ball",
"38": "kite",
"39": "baseball bat",
"40": "baseball glove",
"41": "skateboard",
"42": "surfboard",
"43": "tennis racket",
"44": "bottle",
"46": "wine glass",
"47": "cup",
"48": "fork",
"49": "knife",
"50": "spoon",
"51": "bowl",
"52": "banana",
"53": "apple",
"54": "sandwich",
"55": "orange",
"56": "broccoli",
"57": "carrot",
"58": "hot dog",
"59": "pizza",
"60": "donut",
"61": "cake",
"62": "chair",
"63": "couch",
"64": "potted plant",
"65": "bed",
"67": "dining table",
"70": "toilet",
"72": "tv",
"73": "laptop",
"74": "mouse",
"75": "remote",
"76": "keyboard",
"77": "cell phone",
"78": "microwave",
"79": "oven",
"80": "toaster",
"81": "sink",
"82": "refrigerator",
"84": "book",
"85": "clock",
"86": "vase",
"87": "scissors",
"88": "teddy bear",
"89": "hair drier",
"90": "toothbrush"
{
"1": "person",
"2": "bicycle",
"3": "car",
"4": "motorcycle",
"5": "airplane",
"6": "bus",
"7": "train",
"8": "truck",
"9": "boat",
"10": "traffic light",
"11": "fire hydrant",
"13": "stop sign",
"14": "parking meter",
"15": "bench",
"16": "bird",
"17": "cat",
"18": "dog",
"19": "horse",
"20": "sheep",
"21": "cow",
"22": "elephant",
"23": "bear",
"24": "zebra",
"25": "giraffe",
"27": "backpack",
"28": "umbrella",
"31": "handbag",
"32": "tie",
"33": "suitcase",
"34": "frisbee",
"35": "skis",
"36": "snowboard",
"37": "sports ball",
"38": "kite",
"39": "baseball bat",
"40": "baseball glove",
"41": "skateboard",
"42": "surfboard",
"43": "tennis racket",
"44": "bottle",
"46": "wine glass",
"47": "cup",
"48": "fork",
"49": "knife",
"50": "spoon",
"51": "bowl",
"52": "banana",
"53": "apple",
"54": "sandwich",
"55": "orange",
"56": "broccoli",
"57": "carrot",
"58": "hot dog",
"59": "pizza",
"60": "donut",
"61": "cake",
"62": "chair",
"63": "couch",
"64": "potted plant",
"65": "bed",
"67": "dining table",
"70": "toilet",
"72": "tv",
"73": "laptop",
"74": "mouse",
"75": "remote",
"76": "keyboard",
"77": "cell phone",
"78": "microwave",
"79": "oven",
"80": "toaster",
"81": "sink",
"82": "refrigerator",
"84": "book",
"85": "clock",
"86": "vase",
"87": "scissors",
"88": "teddy bear",
"89": "hair drier",
"90": "toothbrush"
}

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