diff --git a/.gitignore b/.gitignore
index 9771279..00c879a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,6 +4,7 @@
.vscode/
.history
+*.pyc
# Editor directories and files
.idea
diff --git a/mycobot_ai/CMakeLists.txt b/mycobot_ai/CMakeLists.txt
new file mode 100644
index 0000000..a7e50d3
--- /dev/null
+++ b/mycobot_ai/CMakeLists.txt
@@ -0,0 +1,204 @@
+cmake_minimum_required(VERSION 3.0.2)
+project(mycobot_ai)
+
+## Compile as C++11, supported in ROS Kinetic and newer
+# add_compile_options(-std=c++11)
+
+## Find catkin macros and libraries
+## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
+## is used, also find other catkin packages
+find_package(catkin REQUIRED COMPONENTS
+ mycobot_280
+)
+
+## System dependencies are found with CMake's conventions
+# find_package(Boost REQUIRED COMPONENTS system)
+
+
+## Uncomment this if the package has a setup.py. This macro ensures
+## modules and global scripts declared therein get installed
+## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
+# catkin_python_setup()
+
+################################################
+## Declare ROS messages, services and actions ##
+################################################
+
+## To declare and build messages, services or actions from within this
+## package, follow these steps:
+## * Let MSG_DEP_SET be the set of packages whose message types you use in
+## your messages/services/actions (e.g. std_msgs, actionlib_msgs, ...).
+## * In the file package.xml:
+## * add a build_depend tag for "message_generation"
+## * add a build_depend and a exec_depend tag for each package in MSG_DEP_SET
+## * If MSG_DEP_SET isn't empty the following dependency has been pulled in
+## but can be declared for certainty nonetheless:
+## * add a exec_depend tag for "message_runtime"
+## * In this file (CMakeLists.txt):
+## * add "message_generation" and every package in MSG_DEP_SET to
+## find_package(catkin REQUIRED COMPONENTS ...)
+## * add "message_runtime" and every package in MSG_DEP_SET to
+## catkin_package(CATKIN_DEPENDS ...)
+## * uncomment the add_*_files sections below as needed
+## and list every .msg/.srv/.action file to be processed
+## * uncomment the generate_messages entry below
+## * add every package in MSG_DEP_SET to generate_messages(DEPENDENCIES ...)
+
+## 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 # Or other packages containing msgs
+# )
+
+################################################
+## Declare ROS dynamic reconfigure parameters ##
+################################################
+
+## To declare and build dynamic reconfigure parameters within this
+## package, follow these steps:
+## * In the file package.xml:
+## * add a build_depend and a exec_depend tag for "dynamic_reconfigure"
+## * In this file (CMakeLists.txt):
+## * add "dynamic_reconfigure" to
+## find_package(catkin REQUIRED COMPONENTS ...)
+## * uncomment the "generate_dynamic_reconfigure_options" section below
+## and list every .cfg file to be processed
+
+## Generate dynamic reconfigure parameters in the 'cfg' folder
+# generate_dynamic_reconfigure_options(
+# cfg/DynReconf1.cfg
+# cfg/DynReconf2.cfg
+# )
+
+###################################
+## catkin specific configuration ##
+###################################
+## The catkin_package macro generates cmake config files for your package
+## Declare things to be passed to dependent projects
+## INCLUDE_DIRS: uncomment this if your package contains header files
+## LIBRARIES: libraries you create in this project that dependent projects also need
+## CATKIN_DEPENDS: catkin_packages dependent projects also need
+## DEPENDS: system dependencies of this project that dependent projects also need
+catkin_package(
+# INCLUDE_DIRS include
+# LIBRARIES mycobot_ai
+# CATKIN_DEPENDS mycobot_280
+# DEPENDS system_lib
+)
+
+###########
+## Build ##
+###########
+
+## Specify additional locations of header files
+## Your package locations should be listed before other locations
+include_directories(
+# include
+ ${catkin_INCLUDE_DIRS}
+)
+
+## Declare a C++ library
+# add_library(${PROJECT_NAME}
+# src/${PROJECT_NAME}/mycobot_ai.cpp
+# )
+
+## Add cmake target dependencies of the library
+## as an example, code may need to be generated before libraries
+## either from message generation or dynamic reconfigure
+# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
+
+## Declare a C++ executable
+## With catkin_make all packages are built within a single CMake context
+## The recommended prefix ensures that target names across packages don't collide
+# add_executable(${PROJECT_NAME}_node src/mycobot_ai_node.cpp)
+
+## Rename C++ executable without prefix
+## The above recommended prefix causes long target names, the following renames the
+## target back to the shorter version for ease of user use
+## e.g. "rosrun someones_pkg node" instead of "rosrun someones_pkg someones_pkg_node"
+# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")
+
+## Add cmake target dependencies of the executable
+## same as for the library above
+# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
+
+## Specify libraries to link a library or executable target against
+# target_link_libraries(${PROJECT_NAME}_node
+# ${catkin_LIBRARIES}
+# )
+
+#############
+## Install ##
+#############
+
+# all install targets should use catkin DESTINATION variables
+# See http://ros.org/doc/api/catkin/html/adv_user_guide/variables.html
+
+## Mark executable scripts (Python etc.) for installation
+## in contrast to setup.py, you can choose the destination
+# catkin_install_python(PROGRAMS
+# scripts/my_python_script
+# DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+# )
+
+## Mark executables for installation
+## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_executables.html
+# install(TARGETS ${PROJECT_NAME}_node
+# RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+# )
+
+## Mark libraries for installation
+## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_libraries.html
+# install(TARGETS ${PROJECT_NAME}
+# ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
+# LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
+# RUNTIME DESTINATION ${CATKIN_GLOBAL_BIN_DESTINATION}
+# )
+
+## Mark cpp header files for installation
+# install(DIRECTORY include/${PROJECT_NAME}/
+# DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
+# FILES_MATCHING PATTERN "*.h"
+# PATTERN ".svn" EXCLUDE
+# )
+
+## Mark other files for installation (e.g. launch and bag files, etc.)
+# install(FILES
+# # myfile1
+# # myfile2
+# DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
+# )
+
+#############
+## Testing ##
+#############
+
+## Add gtest based cpp test target and link libraries
+# catkin_add_gtest(${PROJECT_NAME}-test test/test_mycobot_ai.cpp)
+# if(TARGET ${PROJECT_NAME}-test)
+# target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
+# endif()
+
+## Add folders to be run by python nosetests
+# catkin_add_nosetests(test)
diff --git a/mycobot_ai/launch/vision.launch b/mycobot_ai/launch/vision.launch
new file mode 100644
index 0000000..654f540
--- /dev/null
+++ b/mycobot_ai/launch/vision.launch
@@ -0,0 +1,27 @@
+
+
+
+
+
+
+
+
+
+
+
+
+ ["joint_states"]
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/mycobot_ai/local_photo/img/goal01.jpeg b/mycobot_ai/local_photo/img/goal01.jpeg
new file mode 100644
index 0000000..1c5b153
Binary files /dev/null and b/mycobot_ai/local_photo/img/goal01.jpeg differ
diff --git a/mycobot_ai/local_photo/img/goal02.jpeg b/mycobot_ai/local_photo/img/goal02.jpeg
new file mode 100644
index 0000000..0d6c5c5
Binary files /dev/null and b/mycobot_ai/local_photo/img/goal02.jpeg differ
diff --git a/mycobot_ai/local_photo/img/goal03.jpeg b/mycobot_ai/local_photo/img/goal03.jpeg
new file mode 100644
index 0000000..a6566fb
Binary files /dev/null and b/mycobot_ai/local_photo/img/goal03.jpeg differ
diff --git a/mycobot_ai/local_photo/img/goal04.jpeg b/mycobot_ai/local_photo/img/goal04.jpeg
new file mode 100644
index 0000000..d20e4ef
Binary files /dev/null and b/mycobot_ai/local_photo/img/goal04.jpeg differ
diff --git a/mycobot_ai/package.xml b/mycobot_ai/package.xml
new file mode 100644
index 0000000..239106b
--- /dev/null
+++ b/mycobot_ai/package.xml
@@ -0,0 +1,62 @@
+
+
+ mycobot_ai
+ 0.0.0
+ The mycobot_ai package
+
+
+
+
+ huang
+
+
+
+
+
+ TODO
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ catkin
+ mycobot_280
+ mycobot_280
+ mycobot_280
+
+
+
+
+
+
+
+
diff --git a/mycobot_ai/scripts/add_img.py b/mycobot_ai/scripts/add_img.py
new file mode 100644
index 0000000..0ea294a
--- /dev/null
+++ b/mycobot_ai/scripts/add_img.py
@@ -0,0 +1,89 @@
+# coding:utf-8
+import os, cv2, sys
+
+
+def take_photo():
+ # 提醒用户操作字典
+ print("*********************************************")
+ print("* 热键(请在摄像头的窗口使用)： *")
+ print("* z: 拍摄图片 *")
+ print("* q: 退出 *")
+ print("*********************************************")
+
+ # 创建/使用local_photo文件夹
+ class_name = "local_photo"
+ if (os.path.exists("local_photo")):
+ pass
+ else:
+ os.mkdir(class_name)
+
+ # 设置特定值
+
+ index = 'takephoto'
+ cap = cv2.VideoCapture(0)
+
+ while True:
+ # 读入每一帧
+ ret, frame = cap.read()
+
+ cv2.imshow("capture", frame)
+
+ # 存储
+ input = cv2.waitKey(1) & 0xFF
+ # 拍照
+ if input == ord('z'):
+ cv2.imwrite(
+ "%s/%s.jpeg" % (class_name, index),
+ cv2.resize(frame, (600, 480), interpolation=cv2.INTER_AREA))
+ break
+
+ # 退出
+ if input == ord('q'):
+
+ # 关闭窗口
+ cap.release()
+ cv2.destroyAllWindows()
+ sys.exit()
+
+
+def cut_photo():
+ path = os.getcwd() + '/local_photo/img'
+ for i, j, k in os.walk(path):
+ file_len = len(k)
+ print("请截取要识别的部分")
+ # root = tk.Tk()
+ # root.withdraw()
+ # temp1=filedialog.askopenfilename(parent=root) #rgb
+ # temp2=Image.open(temp1,mode='r')
+ # temp2= cv.cvtColor(np.asarray(temp2),cv.COLOR_RGB2BGR)
+ # cut = np.array(temp2)
+
+ cut = cv2.imread(r"local_photo/takephoto.jpeg")
+
+ cv2.imshow('original', cut)
+ # C:\Users\Elephant\Desktop\pymycobot+opencv\local_photo/takephoto.jpeg
+
+ # 选择ROI
+ roi = cv2.selectROI(windowName="original",
+ img=cut,
+ showCrosshair=False,
+ fromCenter=False)
+ x, y, w, h = roi
+ print(roi)
+
+ # 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!')
+
+ # 退出
+ cv2.waitKey(0)
+ cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+ take_photo()
+ cut_photo()
diff --git a/mycobot_ai/scripts/ai_windows.py b/mycobot_ai/scripts/ai_windows.py
new file mode 100644
index 0000000..340ecec
--- /dev/null
+++ b/mycobot_ai/scripts/ai_windows.py
@@ -0,0 +1,178 @@
+#!/usr/bin/env python3
+# encoding:utf-8
+
+from tkinter import ttk
+from tkinter import *
+import os, 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.ports = os.popen("ls /dev/ttyUSB*").readline()
+ if "dev" not in self.ports:
+ self.ports = os.popen("ls /dev/ttyACM*").readline()[:-1]
+ self.command = ''.format(
+ self.ports)
+ # 根据通信口修改ros启动文件
+ os.system(
+ "sed -i '2c {}' /home/h/catkin_mycobot/src/mycobot_ros/mycobot_ai/launch/vision.launch"
+ .format(self.command))
+ except Exception as e:
+ pass
+
+ # 设置标题
+ self.win.title("aikit启动工具")
+ self.win.geometry(
+ "500x300+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
+ # 打开ros按钮
+ self.btn = Button(self.win, text="open ROS", command=self.open_ros)
+ self.btn.grid(row=0)
+
+ 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.set_xy = Label(self.win, text="set_xy:", width=10)
+ # self.set_xy.grid(row=1)
+
+ # self.x = Label(self.win, text="x:")
+ # self.x.grid(row=2)
+ # self.v1 = StringVar()
+ # self.e1 = Entry(self.win,textvariable=self.v1, width=10)
+ # self.e1.insert(0,0)
+ # self.e1.grid(row=2,column=1)
+
+ # self.y = Label(self.win, text="y:")
+ # self.y.grid(row=3)
+ # self.v2 = StringVar()
+ # self.e2 = Entry(self.win,textvariable=self.v2, width=10)
+ # self.e2.insert(0,0)
+ # self.e2.grid(row=3,column=1)
+ self.tips = "1、首先打开ros\n2、选择所要运行的程序点击运行即可"
+
+ 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.code_list = ttk.Combobox(self.win, width=15)
+ # self.code_list["value"] = ("颜色识别", "物体识别", "二维码识别")
+ # self.code_list.current(0)
+ # self.code_list.grid(row=1, column=1)
+
+ def start_run(self):
+ try:
+ print(u"开始运行")
+ one = self.myCombox.get()
+ if one == u"颜色识别":
+ 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 /home/h/catkin_mycobot/src/mycobot_ros/mycobot_ai/scripts/detect_obj_img.py"
+ )
+
+ def open_py1(self):
+ os.system(
+ "python /home/h/catkin_mycobot/src/mycobot_ros/mycobot_ai/scripts/detect_obj_color.py"
+ )
+
+ def open_py2(self):
+ os.system(
+ "python /home/h/catkin_mycobot/src/mycobot_ros/mycobot_ai/scripts/detect_encode.py"
+ )
+
+ def add_img(self):
+ os.system(
+ "python /home/h/catkin_mycobot/src/mycobot_ros/mycobot_ai/scripts/add_img.py"
+ )
+
+ def open_ros(self):
+ if self.ros:
+ print("ros is opened")
+ return
+ t1 = threading.Thread(target=self.ross)
+ t1.setDaemon(True)
+ t1.start()
+ self.ros = True
+
+ def ross(self):
+ os.system(
+ "roslaunch ~/catkin_mycobot/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()
diff --git a/mycobot_ai/scripts/detect_encode.py b/mycobot_ai/scripts/detect_encode.py
new file mode 100644
index 0000000..18b1cd2
--- /dev/null
+++ b/mycobot_ai/scripts/detect_encode.py
@@ -0,0 +1,197 @@
+#encoding: UTF-8
+#!/usr/bin/env python2
+import cv2 as cv
+import os
+import numpy as np
+import time
+import rospy
+from visualization_msgs.msg import Marker
+from moving_utils import Movement
+
+# y轴偏移量
+pump_y = -55
+# x轴偏移量
+pump_x = 15
+
+class Detect_marker(Movement):
+ def __init__(self):
+ super(Detect_marker, self).__init__()
+ # set cache of real coord
+ self.cache_x = self.cache_y = 0
+
+ # which robot
+ self.robot = os.popen("ls /dev/ttyUSB*")
+ if "dev" in self.robot:
+ self.Pin = [2,5]
+ else:
+ self.Pin = [20,21]
+
+ # Creating a Camera Object
+ cap_num = 0
+ self.cap = cv.VideoCapture(cap_num)
+ # Get ArUco marker dict that can be detected.
+ self.aruco_dict = cv.aruco.Dictionary_get(cv.aruco.DICT_6X6_250)
+ # Get ArUco marker params.
+ self.aruco_params = cv.aruco.DetectorParameters_create()
+ self.calibrationParams = cv.FileStorage("calibrationFileName.xml", cv.FILE_STORAGE_READ)
+ # Get distance coefficient.
+ self.dist_coeffs = self.calibrationParams.getNode("distCoeffs").mat()
+
+ height = self.cap.get(4)
+ focal_length = width = self.cap.get(3)
+ center = [width / 2, height / 2]
+ # Calculate the camera matrix.
+ self.camera_matrix = np.array(
+ [
+ [focal_length, 0, center[0]],
+ [0, focal_length, center[1]],
+ [0, 0, 1],
+ ],
+ dtype=np.float32,
+ )
+ # init a node and a publisher
+ rospy.init_node("encode_marker", anonymous=True)
+ self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
+
+ 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
+ self.marker.color.r = 0.3
+ self.marker.color.g = 0.3
+ self.marker.color.b = 0.3
+
+
+ # 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
+
+ # Grasping motion
+ def move(self, x, y):
+
+ coords = [
+ [135.0, -65.5, 280.1, 178.99, 5.38, -179.9],
+ [136.1, -141.6, 243.9, 178.99, 5.38, -179.9]
+ ]
+
+ # publish marker
+ self.marker.header.stamp = rospy.Time.now()
+ self.marker.pose.position.x = (coords[0][0]-x)/1000.0
+ self.marker.pose.position.y = (coords[0][1]-y)/1000.0
+ self.pub.publish(self.marker)
+
+ # send coordinates to move mycobot
+ self.pub_coords(coords[0], 30, 1)
+ time.sleep(2)
+ self.pub_coords([coords[0][0]-x, coords[0][1]-y, 240, 178.99, 5.38, -179.9], 25, 1)
+ time.sleep(2)
+ self.pub_coords([coords[0][0]-x, coords[0][1]-y, 200, 178.99, 5.38, -179.9], 25, 1)
+ time.sleep(2)
+ if "dev" in self.robot:
+ self.pub_coords([coords[0][0]-x, coords[0][1]-y, 90, 178.99, 5.38, -179.9], 25, 1)
+ else:
+ self.pub_coords([coords[0][0]-x+20, coords[0][1]-y-10, 70, 178.99, 5.38, -179.9], 25, 1)
+ time.sleep(3.5)
+ self.pub_pump(True,self.Pin)
+ self.pub_coords(coords[0], 30, 1)
+ time.sleep(3)
+ self.pub_coords(coords[1], 30, 1)
+ time.sleep(2)
+ self.pub_pump(False,self.Pin)
+ # publish marker
+ self.marker.header.stamp = rospy.Time.now()
+ self.marker.pose.position.x = coords[1][0]/1000.0
+ self.marker.pose.position.y = coords[1][1]/1000.0
+ self.pub.publish(self.marker)
+
+ self.pub_coords(coords[0], 30, 1)
+ time.sleep(2)
+
+ # decide whether grab cube
+ def decide_move(self, x, y):
+
+ print(x,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)
+
+ # init mycobot
+ def init_mycobot(self):
+ self.pub_pump(False,self.Pin)
+ for _ in range(5):
+ print _
+ self.pub_coords([135.0, -65.5, 280.1, 178.99, 5.38, -179.9], 20, 1)
+ time.sleep(0.5)
+
+
+
+ def run(self):
+ global pump_y, pump_x
+ self.init_mycobot()
+ num = sum_x = sum_y = 0
+ while cv.waitKey(1) < 0:
+ success, img = self.cap.read()
+ if not success:
+ print("It seems that the image cannot be acquired correctly.")
+ break
+
+ # transfrom the img to model of gray
+ gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+ # Detect ArUco marker.
+ corners, ids, rejectImaPoint = cv.aruco.detectMarkers(
+ gray, self.aruco_dict, parameters=self.aruco_params
+ )
+
+ if len(corners) > 0:
+ if ids is not None:
+ # get informations of aruco
+ ret = cv.aruco.estimatePoseSingleMarkers(
+ corners, 0.03, self.camera_matrix, self.dist_coeffs
+ )
+ # rvec:rotation offset,tvec:translation deviator
+ (rvec, tvec) = (ret[0], ret[1])
+ (rvec - tvec).any()
+ xyz = tvec[0, 0, :]
+ # calculate the coordinates of the aruco relative to the pump
+ xyz = [round(xyz[0]*1000+pump_y, 2), round(xyz[1]*1000+pump_x, 2), round(xyz[2]*1000, 2)]
+
+
+ for i in range(rvec.shape[0]):
+ # draw the aruco on img
+ cv.aruco.drawDetectedMarkers(img, corners)
+ cv.aruco.drawAxis(
+ img,
+ self.camera_matrix,
+ self.dist_coeffs,
+ rvec[i, :, :],
+ tvec[i, :, :],
+ 0.03,
+ )
+
+ if num < 40 :
+ sum_x += xyz[1]
+ sum_y += xyz[0]
+ num += 1
+ elif num ==40 :
+ self.decide_move(sum_x/40.0, sum_y/40.0)
+ num = sum_x = sum_y = 0
+
+ cv.imshow("encode_image", img)
+
+if __name__ == "__main__":
+ detect = Detect_marker()
+ detect.run()
diff --git a/mycobot_ai/scripts/detect_obj_color.py b/mycobot_ai/scripts/detect_obj_color.py
new file mode 100644
index 0000000..ccd4fae
--- /dev/null
+++ b/mycobot_ai/scripts/detect_obj_color.py
@@ -0,0 +1,432 @@
+#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'
+__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, -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
+ ]
+ # 移动坐标
+ self.move_coords = [
+ [120.1, -141.6, 240.9, -173.34, -8.15, -83.11], # above the red bucket
+ [228.2, -127.8, 260.9, -157.51, -17.5, -71.18], # above the yello 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],
+ ]
+ # which robot
+ self.robot = os.popen("ls /dev/ttyUSB*")
+ if "dev" in self.robot:
+ self.Pin = [2,5]
+ else:
+ self.Pin = [20,21]
+ for i in self.move_coords:
+ i[2] -= 20
+
+ # 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])],
+ "green": [np.array([35, 43, 46]), np.array([77, 255, 255])],
+ "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])],
+ "cyan": [np.array([78, 43, 46]), np.array([99, 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):
+ # send Angle to move mycobot
+ print color
+ 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, -25.95], 20, 1)
+ time.sleep(1.5)
+ if "dev" in self.robot:
+ self.pub_coords([x, y, 90, -178.9, -1.57, -25.95], 20, 1)
+ else:
+
+ h = 0
+
+ if 165180:
+ h = 20
+ elif x<135:
+ h = -20
+ print 'down_1:',[x, y, 31.9+h, -178.9, -1, -25.95]
+ self.pub_coords([x, y, 31.9+h, -178.9, -1, -25.95], 20, 1)
+ time.sleep(1.5)
+ # open pump
+ self.pub_pump(True,self.Pin)
+ 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(2)
+ 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 'down:',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(2)
+ # close pump
+ self.pub_pump(False,self.Pin)
+ if color==1:
+ self.pub_marker(self.move_coords[color][0]/1000.0+0.04, self.move_coords[color][1]/1000.0-0.02)
+ elif color==0:
+ self.pub_marker(self.move_coords[color][0]/1000.0+0.03, self.move_coords[color][1]/1000.0)
+ 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
+ if "dev" not in self.robot:
+
+ 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
+ print x,y
+ 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,self.Pin)
+
+ # 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
+ else:
+ self.color = 1
+
+ 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)
+
+
+
diff --git a/mycobot_ai/scripts/detect_obj_img.py b/mycobot_ai/scripts/detect_obj_img.py
new file mode 100644
index 0000000..d42ab21
--- /dev/null
+++ b/mycobot_ai/scripts/detect_obj_img.py
@@ -0,0 +1,602 @@
+#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 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, -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
+ ]
+ # 移动坐标
+ self.move_coords = [
+ [120.1, -141.6, 240.9, -173.34, -8.15, -83.11], # above the red bucket
+ [228.2, -127.8, 260.9, -157.51, -17.5, -71.18], # above the yello 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],
+ ]
+ # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
+ self.robot = os.popen("ls /dev/ttyUSB*")
+ if "dev" in self.robot:
+ self.Pin = [2,5]
+ else:
+ self.Pin = [20,21]
+ for i in self.move_coords:
+ i[2] -= 20
+
+ # 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):
+ # 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, -25.95], 20, 1)
+ time.sleep(1.5)
+
+ if "dev" in self.robot:
+ self.pub_coords([x, y, 90, -178.9, -1.57, -25.95], 20, 1)
+ else:
+
+ h = 0
+ if 165180:
+ h = 20
+ elif x<135:
+ h = -20
+ #print 'down_1:',[x, y, 31.9+h, -178.9, -1, -25.95]
+ self.pub_coords([x, y, 31.9+h, -178.9, -1, -25.95], 20, 1)
+ time.sleep(1.5)
+ # open pump
+ self.pub_pump(True,self.Pin)
+ 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)
+
+ 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(2)
+ # close pump
+ self.pub_pump(False,self.
+Pin)
+ if color==1:
+ self.pub_marker(self.move_coords[color][0]/1000.0+0.04, self.move_coords[color][1]/1000.0-0.02)
+ elif color==0:
+ self.pub_marker(self.move_coords[color][0]/1000.0+0.03, self.move_coords[color][1]/1000.0)
+ 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
+ if "dev" not in self.robot:
+ 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
+ #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, -38.84], 20)
+ print(_)
+ time.sleep(0.5)
+ self.pub_pump(False,self.Pin)
+
+ # 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):
+ # 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,
+ # )
+ i = 0
+ MIN_MATCH_COUNT = 10
+ 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
+ def take_photo(self):
+ # 提醒用户操作字典
+ print("*********************************************")
+ print("* 热键(请在摄像头的窗口使用)： *")
+ print("* z: 拍摄图片 *")
+ print("* q: 退出 *")
+ print("*********************************************")
+
+ # 创建/使用local_photo文件夹
+ class_name = "local_photo"
+ if(os.path.exists("local_photo")):
+ pass
+ else:
+ os.mkdir(class_name)
+
+ # 设置特定值
+
+ index = 'takephoto'
+ cap = cv2.VideoCapture(0)
+
+ while True:
+ # 读入每一帧
+ ret, frame = cap.read()
+
+ cv2.imshow("capture", frame)
+
+ # 存储
+ input = cv2.waitKey(1) & 0xFF
+ # 拍照
+ if input == ord('z'):
+ cv2.imwrite("%s/%s.jpeg" % (class_name, index),
+ cv2.resize(frame, (600, 480), interpolation=cv2.INTER_AREA))
+ break
+
+ # 退出
+ if input == ord('q'):
+ break
+
+ # 关闭窗口
+ cap.release()
+ cv2.destroyAllWindows()
+
+ def cut_photo(self):
+ path = os.getcwd()+'/local_photo/img'
+ print path
+ for i,j,k in os.walk(path):
+ file_len = len(k)
+ print("请截取要识别的部分")
+ # root = tk.Tk()
+ # root.withdraw()
+ # temp1=filedialog.askopenfilename(parent=root) #rgb
+ # temp2=Image.open(temp1,mode='r')
+ # temp2= cv.cvtColor(np.asarray(temp2),cv.COLOR_RGB2BGR)
+ # cut = np.array(temp2)
+
+ cut = cv2.imread(r"local_photo/takephoto.jpeg")
+
+ cv2.imshow('original', cut)
+ # C:\Users\Elephant\Desktop\pymycobot+opencv\local_photo/takephoto.jpeg
+
+ # 选择ROI
+ roi = cv2.selectROI(windowName="original", img=cut,
+ showCrosshair=False, fromCenter=False)
+ x, y, w, h = roi
+ print(roi)
+
+ # 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!')
+
+ # 退出
+ cv2.waitKey(0)
+ cv2.destroyAllWindows()
+
+ def distinguist(self):
+ print("请选择要识别的物体图片")
+ root = tk.Tk() # 显式创建根窗体
+ root.withdraw() # 将根窗体隐藏
+ file = filedialog.askopenfilename(parent=root)
+ load = Image.open(file, mode='r')
+ load = cv.cvtColor(np.asarray(load), cv.COLOR_RGB2BGR)
+ goal = np.array(load)
+ return goal
+
+
+def run(stop):
+
+ #Object_detect().take_photo()
+ #Object_detect().cut_photo()
+ # goal = Object_detect().distinguist()
+ goal = []
+ path = os.getcwd()+'/local_photo/img'
+ print path
+ 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)
+ 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,goal)
+ 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)
+
+
+if __name__ == "__main__":
+ run(0)
+ #Object_detect().take_photo()
+ #Object_detect().cut_photo()
+
diff --git a/mycobot_ai/scripts/frozen_inference_graph.pb b/mycobot_ai/scripts/frozen_inference_graph.pb
new file mode 100644
index 0000000..92189ed
Binary files /dev/null and b/mycobot_ai/scripts/frozen_inference_graph.pb differ
diff --git a/mycobot_ai/scripts/graph.pbtxt b/mycobot_ai/scripts/graph.pbtxt
new file mode 100644
index 0000000..9791f03
--- /dev/null
+++ b/mycobot_ai/scripts/graph.pbtxt
@@ -0,0 +1,2682 @@
+node {
+ name: "image_tensor"
+ op: "Placeholder"
+ attr {
+ key: "dtype"
+ value {
+ type: DT_UINT8
+ }
+ }
+ attr {
+ key: "shape"
+ value {
+ shape {
+ dim {
+ size: -1
+ }
+ dim {
+ size: 300
+ }
+ dim {
+ size: 300
+ }
+ dim {
+ size: 3
+ }
+ }
+ }
+ }
+}
+node {
+ name: "Preprocessor/mul"
+ op: "Mul"
+ input: "image_tensor"
+ input: "Preprocessor/mul/x"
+}
+node {
+ name: "Preprocessor/sub"
+ op: "Sub"
+ input: "Preprocessor/mul"
+ input: "Preprocessor/sub/y"
+}
+node {
+ name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1"
+ op: "Conv2D"
+ input: "Preprocessor/sub"
+ input: "FeatureExtractor/MobilenetV1/Conv2d_0/weights/read/_104__cf__107"
+ input: "^FeatureExtractor/Assert/Assert"
+ attr {
+ key: "data_format"
+ value {
+ s: "NHWC"
+ }
+ }
+ attr {
+ key: "padding"
+ value {
+ s: "SAME"
+ }
+ }
+ attr {
+ key: "strides"
+ value {
+ list {
+ i: 1
+ i: 2
+ i: 2
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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diff --git a/mycobot_ai/scripts/labels.json b/mycobot_ai/scripts/labels.json
new file mode 100644
index 0000000..c8926c6
--- /dev/null
+++ b/mycobot_ai/scripts/labels.json
@@ -0,0 +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"
+}
\ No newline at end of file
diff --git a/mycobot_ai/scripts/moving_utils.py b/mycobot_ai/scripts/moving_utils.py
new file mode 100644
index 0000000..1b6a651
--- /dev/null
+++ b/mycobot_ai/scripts/moving_utils.py
@@ -0,0 +1,49 @@
+#encoding: UTF-8
+#!/usr/bin/env python2
+import rospy
+import time,os
+
+from mycobot_communication.msg import MycobotSetAngles, MycobotSetCoords, MycobotPumpStatus
+
+
+class Movement(object):
+ """Tools class: Communication with mycobot."""
+ def __init__(self):
+ super(Movement, self).__init__()
+ self.angle_pub = rospy.Publisher("mycobot/angles_goal", MycobotSetAngles, queue_size=5)
+ self.coord_pub = rospy.Publisher("mycobot/coords_goal", MycobotSetCoords, queue_size=5)
+
+ self.pump_pub = rospy.Publisher("mycobot/pump_status", MycobotPumpStatus, queue_size=10)
+
+ self.angles = MycobotSetAngles()
+ self.coords = MycobotSetCoords()
+ self.pump = MycobotPumpStatus()
+
+ def pub_coords(self, item, sp=20, m=1):
+ self.coords.x = item[0]
+ self.coords.y = item[1]
+ self.coords.z = item[2]
+ self.coords.rx = item[3]
+ self.coords.ry = item[4]
+ self.coords.rz = item[5]
+ self.coords.speed = sp
+ self.coords.model = m
+ self.coord_pub.publish(self.coords)
+
+
+ def pub_angles(self, item, sp):
+ self.angles.joint_1 = item[0]
+ self.angles.joint_2 = item[1]
+ self.angles.joint_3 = item[2]
+ self.angles.joint_4 = item[3]
+ self.angles.joint_5 = item[4]
+ self.angles.joint_6 = item[5]
+ self.angles.speed = sp
+ self.angle_pub.publish(self.angles)
+
+
+ def pub_pump(self, flag,Pin):
+ self.pump.Status = flag
+ self.pump.Pin1 = Pin[0]
+ self.pump.Pin2 = Pin[1]
+ self.pump_pub.publish(self.pump)
diff --git a/mycobot_ai/scripts/mtx_dist.npz b/mycobot_ai/scripts/mtx_dist.npz
new file mode 100644
index 0000000..88f1cee
Binary files /dev/null and b/mycobot_ai/scripts/mtx_dist.npz differ
diff --git a/mycobot_ai/scripts/openVideo.py b/mycobot_ai/scripts/openVideo.py
new file mode 100644
index 0000000..a95db11
--- /dev/null
+++ b/mycobot_ai/scripts/openVideo.py
@@ -0,0 +1,8 @@
+import cv2 as cv
+
+if __name__ == "__main__":
+ cap_num = 0
+ cap = cv.VideoCapture(cap_num)
+ while cv.waitKey(1)<0:
+ _, img = cap.read()
+ cv.imshow("", img)
diff --git a/mycobot_ai/scripts/pump.py b/mycobot_ai/scripts/pump.py
new file mode 100644
index 0000000..3feb6d2
--- /dev/null
+++ b/mycobot_ai/scripts/pump.py
@@ -0,0 +1,23 @@
+#encoding: UTF-8
+#!/usr/bin/env python2
+
+import rospy
+import time
+from moving_utils import Movement
+
+class Pump(Movement):
+
+ def __init__(self):
+ super(Pump, self).__init__()
+ rospy.init_node("pump", anonymous=True)
+
+ def run(self):
+ self.pub_pump(False)
+ time.sleep(1)
+ self.pub_pump(True)
+ time.sleep(5)
+ self.pub_pump(False)
+
+if __name__ == "__main__":
+ pump = Pump()
+ pump.run()
\ No newline at end of file
diff --git a/mycobot_ai/scripts/send_maker.py b/mycobot_ai/scripts/send_maker.py
new file mode 100644
index 0000000..7fb84b4
--- /dev/null
+++ b/mycobot_ai/scripts/send_maker.py
@@ -0,0 +1,72 @@
+# encoding: utf-8
+
+import rospy
+import time
+from visualization_msgs.msg import Marker
+
+class Send_marker(object):
+ def __init__(self):
+ # 继承object类对象
+ super(Send_marker, self).__init__()
+ # 初始化一个节点，如果没有创建节点会导致无法发布信息
+ rospy.init_node("send_marker", anonymous=True)
+ # 创建一个发布者，用来发布marker
+ self.pub = rospy.Publisher("/test_marker", Marker, queue_size=1)
+ # 创建一个marker用来创建方块模型
+ self.marker = Marker()
+ # 配置其所属关系，其坐标均是相对于/joint1而言的。
+ # /joint1在模型中代表机械臂的底部
+ self.marker.header.frame_id = "/joint1"
+ # 设置marker的名称
+ self.marker.ns = "test_marker"
+ # 设置marker的类型是方块
+ self.marker.type = self.marker.CUBE
+ # 设置marker的动作为添加（没有这个名称的marker就为其添加一个）
+ self.marker.action = self.marker.ADD
+ # 设置marker的实际大小情况，单位为m
+ self.marker.scale.x = 0.04
+ self.marker.scale.y = 0.04
+ self.marker.scale.z = 0.04
+ # 设置marker的颜色，1.0表示255（这表示着一种比率换算）
+ self.marker.color.a = 1.0
+ self.marker.color.g = 1.0
+ self.marker.color.r = 1.0
+ # 初始化marker的位置以及其四维姿态
+ 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
+
+ # 修改坐标并发布marker
+ def pub_marker(self, x, y, z=0.03):
+ # 设置marker的时间戳
+ self.marker.header.stamp = rospy.Time.now()
+ # 设置marker的空间坐标
+ self.marker.pose.position.x = x
+ self.marker.pose.position.y = y
+ self.marker.pose.position.z = z
+ # 发布marker
+ self.pub.publish(self.marker)
+
+ # 让marker发生位移效果
+ def run(self):
+ time.sleep(1)
+ self.pub_marker(0.2, 0)
+ time.sleep(1)
+ self.pub_marker(0.15, -0.05)
+ time.sleep(1)
+ self.pub_marker(0.15, 0.05)
+ time.sleep(1)
+ self.pub_marker(0.1, 0)
+ time.sleep(1)
+ self.pub_marker(0.136, -0.141)
+ time.sleep(1)
+ self.pub_marker(0.238, -0.147)
+ time.sleep(1)
+
+if __name__ == '__main__':
+ marker = Send_marker()
+ marker.run()
diff --git a/mycobot_ai/scripts/tools.py b/mycobot_ai/scripts/tools.py
new file mode 100644
index 0000000..2e955fb
--- /dev/null
+++ b/mycobot_ai/scripts/tools.py
@@ -0,0 +1,11 @@
+from pymycobot.mycobot import MyCobot
+
+# name of device
+port = "/dev/ttyUSB0"
+mc = MyCobot(port)
+
+# release mycobot
+# mc.release_all_servos()
+
+# calibrate the sixth servo
+mc.set_servo_calibration(6)