From 7051e28bf9b63402706d583c96390e0f7854a2df Mon Sep 17 00:00:00 2001 From: 2929ss <1814754095@qq.com> Date: Tue, 12 Jul 2022 15:11:42 +0800 Subject: [PATCH] update --- mecharm/mecharm/config/mecharm.rviz | 15 +- mycobot_280/mycobot_280/config/mycobot.rviz | 21 +- .../scripts/listen_real_of_topic.py | 3 +- .../combine_detect_obj_img_folder_opt.py | 7 +- .../myCobot_280/launch/vision_m5.launch | 27 + .../{vision.launch => vision_pi.launch} | 0 .../scripts/combine_detect_obj_color .py | 472 +++++++++++++ .../combine_detect_obj_img_folder_opt.py | 668 ++++++++++++++++++ mycobot_ai/myCobot_280/scripts/test.py | 122 +--- .../urdf/mecharm/mecharm_aikit.urdf | 2 +- 10 files changed, 1232 insertions(+), 105 deletions(-) mode change 100644 => 100755 mycobot_280/mycobot_280/scripts/listen_real_of_topic.py create mode 100644 mycobot_ai/myCobot_280/launch/vision_m5.launch rename mycobot_ai/myCobot_280/launch/{vision.launch => vision_pi.launch} (100%) create mode 100755 mycobot_ai/myCobot_280/scripts/combine_detect_obj_color .py create mode 100644 mycobot_ai/myCobot_280/scripts/combine_detect_obj_img_folder_opt.py diff --git a/mecharm/mecharm/config/mecharm.rviz b/mecharm/mecharm/config/mecharm.rviz index ab16afc..764eb6f 100644 --- a/mecharm/mecharm/config/mecharm.rviz +++ b/mecharm/mecharm/config/mecharm.rviz @@ -66,6 +66,11 @@ Visualization Manager: Show Axes: false Show Trail: false Value: true + env: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true link1: Alpha: 1 Show Axes: false @@ -109,6 +114,8 @@ Visualization Manager: All Enabled: true base: Value: true + env: + Value: true link1: Value: true link2: @@ -128,6 +135,8 @@ Visualization Manager: Show Names: true Tree: base: + env: + {} link1: link2: link3: @@ -162,7 +171,7 @@ Visualization Manager: Views: Current: Class: rviz/Orbit - Distance: 0.949513793 + Distance: 1.49407828 Enable Stereo Rendering: Stereo Eye Separation: 0.0599999987 Stereo Focal Distance: 1 @@ -177,10 +186,10 @@ Visualization Manager: Invert Z Axis: false Name: Current View Near Clip Distance: 0.00999999978 - Pitch: 0.629796803 + Pitch: 0.344796687 Target Frame: Value: Orbit (rviz) - Yaw: 2.05177665 + Yaw: 1.20677686 Saved: ~ Window Geometry: Displays: diff --git a/mycobot_280/mycobot_280/config/mycobot.rviz b/mycobot_280/mycobot_280/config/mycobot.rviz index 51ba33e..68ab389 100644 --- a/mycobot_280/mycobot_280/config/mycobot.rviz +++ b/mycobot_280/mycobot_280/config/mycobot.rviz @@ -9,7 +9,7 @@ Panels: - /RobotModel1 - /TF1 Splitter Ratio: 0.5 - Tree Height: 775 + Tree Height: 607 - Class: rviz/Selection Name: Selection - Class: rviz/Tool Properties @@ -62,6 +62,11 @@ Visualization Manager: Expand Link Details: false Expand Tree: false Link Tree Style: Links in Alphabetic Order + env: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true joint1: Alpha: 1 Show Axes: false @@ -108,6 +113,8 @@ Visualization Manager: Frame Timeout: 15 Frames: All Enabled: true + env: + Value: true joint1: Value: true joint2: @@ -129,6 +136,8 @@ Visualization Manager: Show Names: true Tree: joint1: + env: + {} joint2: joint3: joint4: @@ -186,10 +195,10 @@ Visualization Manager: Window Geometry: Displays: collapsed: false - Height: 1056 + Height: 888 Hide Left Dock: false Hide Right Dock: false - QMainWindow State: 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 + QMainWindow State: 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 Selection: collapsed: false Time: @@ -198,6 +207,6 @@ Window Geometry: collapsed: false Views: collapsed: false - Width: 1855 - X: 65 - Y: 24 + Width: 1695 + X: 180 + Y: 34 diff --git a/mycobot_280/mycobot_280/scripts/listen_real_of_topic.py b/mycobot_280/mycobot_280/scripts/listen_real_of_topic.py old mode 100644 new mode 100755 index ea3df92..2c910da --- a/mycobot_280/mycobot_280/scripts/listen_real_of_topic.py +++ b/mycobot_280/mycobot_280/scripts/listen_real_of_topic.py @@ -1,6 +1,7 @@ #!/usr/bin/env python2 -import math +# encoding:utf-8 +import math import rospy from sensor_msgs.msg import JointState from std_msgs.msg import Header diff --git a/mycobot_ai/mechArm_270/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/mechArm_270/scripts/combine_detect_obj_img_folder_opt.py index 143f8c3..9f676ca 100755 --- a/mycobot_ai/mechArm_270/scripts/combine_detect_obj_img_folder_opt.py +++ b/mycobot_ai/mechArm_270/scripts/combine_detect_obj_img_folder_opt.py @@ -34,7 +34,7 @@ class Object_detect(Movement): # get path of file dir_path = os.path.dirname(__file__) - # declare mypal260 + # declare 270 self.mc = None # 移动角度 self.move_angles = [ @@ -83,6 +83,7 @@ class Object_detect(Movement): self.raspi = True if self.raspi: self.gpio_status(False) + # choose place to set cube self.color = 0 # parameters to calculate camera clipping parameters @@ -236,7 +237,9 @@ class Object_detect(Movement): # init 270 def run(self): - if "dev" in self.robot_m5: + if "dev" in self.robot_wio : + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_m5: self.mc = MyCobot(self.robot_m5, 115200) elif "dev" in self.robot_raspi: self.mc = MyCobot(self.robot_raspi, 1000000) diff --git a/mycobot_ai/myCobot_280/launch/vision_m5.launch b/mycobot_ai/myCobot_280/launch/vision_m5.launch new file mode 100644 index 0000000..a8feb9a --- /dev/null +++ b/mycobot_ai/myCobot_280/launch/vision_m5.launch @@ -0,0 +1,27 @@ + + + + + + + + + + + + + ["joint_states"] + + + + + + + + + + + + + + diff --git a/mycobot_ai/myCobot_280/launch/vision.launch b/mycobot_ai/myCobot_280/launch/vision_pi.launch similarity index 100% rename from mycobot_ai/myCobot_280/launch/vision.launch rename to mycobot_ai/myCobot_280/launch/vision_pi.launch diff --git a/mycobot_ai/myCobot_280/scripts/combine_detect_obj_color .py b/mycobot_ai/myCobot_280/scripts/combine_detect_obj_color .py new file mode 100755 index 0000000..d0ac0bf --- /dev/null +++ b/mycobot_ai/myCobot_280/scripts/combine_detect_obj_color .py @@ -0,0 +1,472 @@ +# encoding:utf-8 +#!/usr/bin/env python2 + +from tokenize import Pointfloat +import cv2 +import numpy as np +import time +import json +import os,sys +import rospy +from visualization_msgs.msg import Marker +from pymycobot.mycobot import MyCobot +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 = 170, camera_y = -10): + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + self.mc = None + + # 移动角度 + self.move_angles = [ + [-7.11, -6.94, -55.01, -24.16, 0, -15], # init the point + [18.8, -7.91, -54.49, -23.02, -0.79, -14.76], # point to grab + ] + + # 移动坐标 + self.move_coords = [ + [120.8, -134.4, 258.0, -172.72, -5.31, -109.09], # above the red bucket + [219.8, -126.4, 249.7, -158.68, -7.93, -101.6], # green + [124.7, 145.3, 250.4, -173.5, -2.23, -11.7], # blue + [14.6, 175.9, 250.4, -177.42, -0.08, 25.93], # gray + ] + # which robot: USB* is m5; ACM* is wio; AMA* is raspi + 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] + self.raspi = False + if "dev" in self.robot_m5: + self.Pin = [2, 5] + elif "dev" in self.robot_wio: + self.Pin = [20, 21] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + + # 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) + + 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) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + # Grasping motion + def move(self, x, y, color): + # send Angle to move mycobot + print (color) + self.mc.send_angles(self.move_angles[1], 25) + time.sleep(3) + + # send coordinates to move mycobot + self.mc.send_coords([x, y, 190.6, -173.3, -5.48, -57.9], 25, 1) + time.sleep(3) + + self.mc.send_coords([x, y, 150, -173.3, -5.48, -57.9], 25, 0) + time.sleep(3) + + self.mc.send_coords([x, y, 123, -173.3, -5.48, -57.9], 10, 0) + time.sleep(3) + + # open pump + if "dev" in self.robot_m5: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + tmp = [] + while True: + if not tmp: + tmp = self.mc.get_angles() + else: + break + time.sleep(0.5) + + # print(tmp) + self.mc.send_angles([tmp[0], -0.71, -54.49, -23.02, -0.79, tmp[5]],25) # [18.8, -7.91, -54.49, -23.02, -0.79, -14.76] + 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.mc.send_coords(self.move_coords[color], 25, 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(3) + + # close pump + if "dev" in self.robot_m5: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(6) + 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) + self.mc.send_angles(self.move_angles[0], 25) + 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 + self.move(x, y, color) + + # init mycobot + def run(self): + if "dev" in self.robot_wio : + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_m5: + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyCobot(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20) + time.sleep(3) + + # 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 == "red": + self.color = 0 + elif mycolor == "green": + self.color = 1 + elif mycolor == "cyan": + self.color = 2 + else: + self.color = 3 + + 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, 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: + # 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/myCobot_280/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/myCobot_280/scripts/combine_detect_obj_img_folder_opt.py new file mode 100644 index 0000000..0b6bfbf --- /dev/null +++ b/mycobot_ai/myCobot_280/scripts/combine_detect_obj_img_folder_opt.py @@ -0,0 +1,668 @@ +# 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,sys +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 pymycobot.mycobot import MyCobot +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 = 170, camera_y = -5): + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + self.mc = None + + # 移动角度 + self.move_angles = [ + [-7.11, -6.94, -55.01, -24.16, 0, -15], # init the point + [18.8, -7.91, -54.49, -23.02, -0.79, -14.76], # point to grab + ] + + # 移动坐标 + self.move_coords = [ + [120.8, -134.4, 258.0, -172.72, -5.31, -109.09], # above the red bucket + [219.8, -126.4, 249.7, -158.68, -7.93, -101.6], # green + [124.7, 145.3, 250.4, -173.5, -2.23, -11.7], # blue + [14.6, 175.9, 250.4, -177.42, -0.08, 25.93], # gray + ] + + # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed + self.raspi = False + 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_m5: + self.Pin = [2, 5] + elif "dev" in self.robot_wio: + self.Pin = [20, 21] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + + # 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) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + + # Grasping motion + def move(self, x, y, color): + # send Angle to move mycobot + print (color) + self.mc.send_angles(self.move_angles[1], 25) + time.sleep(3) + + # send coordinates to move mycobot + self.mc.send_coords([x, y, 190.6, -173.3, -5.48, -57.9], 25, 1) + time.sleep(2.5) + + self.mc.send_coords([x, y, 150, -173.3, -5.48, -57.9], 25, 0) + time.sleep(2.5) + + self.mc.send_coords([x, y, 123, -173.3, -5.48, -57.9], 10, 0) + time.sleep(3) + + # open pump + if "dev" in self.robot_m5: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + tmp = [] + while True: + if not tmp: + tmp = self.mc.get_angles() + else: + break + time.sleep(0.5) + + # print(tmp) + self.mc.send_angles([tmp[0], -0.71, -54.49, -23.02, -0.79, tmp[5]],25) # [18.8, -7.91, -54.49, -23.02, -0.79, -14.76] + time.sleep(3) + + + + self.mc.send_coords(self.move_coords[color], 25, 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(3) + + # close pump + if "dev" in self.robot_m5: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(6) + + self.mc.send_angles(self.move_angles[0], 25) + 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 + self.move(x, y, color) + + # init mycobot + def run(self): + if "dev" in self.robot_wio : + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_m5: + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyCobot(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20) + time.sleep(3) + + # 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 + + if x + y > 0: + return x, y + else: + return None + +# The path to save the image folder +def parse_folder(folder): + restore = [] + path1 = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myCobot_280' + folder + path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/myCobot_280/' + folder + if os.path.exists(path1): + path = path1 + elif os.path.exists(path2): + path = path2 + 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/blue') + res_queue[3] = parse_folder('res/gray') + + # 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) + + # close the window + if cv2.waitKey(1) & 0xFF == ord('q'): + # cap.release() + cv2.destroyAllWindows() + sys.exit() + child.join() + + +if __name__ == "__main__": + run() + # Object_detect().take_photo() + # Object_detect().cut_photo() diff --git a/mycobot_ai/myCobot_280/scripts/test.py b/mycobot_ai/myCobot_280/scripts/test.py index 8f974fb..5f6f7eb 100755 --- a/mycobot_ai/myCobot_280/scripts/test.py +++ b/mycobot_ai/myCobot_280/scripts/test.py @@ -1,104 +1,42 @@ # -*- coding: utf-8 -*- - -# from fileinput import filename -# from genericpath import isfile -# import os -# from sys import path -# import cv2 -# from PIL import Image - - -# # #count=0 -# for file in dirs: -# pic_dir=os.path.join(path,file) # res中子文件夹的路径 -# print(pic_dir) -# for i in os.listdir(pic_dir): -# imgdir=os.path.join(pic_dir,i) -# print(imgdir) -# for i in os.listdir(pic_dir): -# image_dir=os.path.join(pic_dir,i) #res中每个子文件夹中图片的路径 -# img1 = cv2.imread(image_dir) # 读取res中每个子文件夹中的图片 -# #count+=1 -# print(image_dir)#输出图片的路径 -#print(img1)#输出图片 -#print(count)#图片个数 -# dir_path = os.path.dirname(__file__) -# print(dir_path) -# # path1 = os.path.split(os.path.realpath(__file__))[0] -# # print(path1) -# path3=os.path.join(os.path.split(dir_path)[0]+'/res/') - -# print(path3) -# #for file in os.listdir(path3): -# pic_dir=os.path.join(path3+'red') -# # print(pic_dir) -# for i in os.listdir(pic_dir): -# img=os.path.join(pic_dir,i) -# print(img) -# print(os.getcwd()+'/mycobot_ai/res/red') - -# list1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]] -# print(list1[0][0]) -# for i, v in enumerate(list1): -# print(i) - -# res = [] -# for i in list1: -# res.append(i) -# print(res) - -# # for i in list1: -# # print(i) - -# color=i -# print(color) -# for color in range(0,4): -# print(color) - 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/ttyACM0", 115200) +mc = MyCobot("/dev/ttyUSB0", 115200) +# mc = MyCobot("/dev/ttyAMA0", 1000000) -mc = MyCobot("/dev/ttyAMA0", 1000000) -# mc.send_angles([0,0,0,0,0,0], 20) +# mc.send_angles([0,0,0,0,90,0], 20) +mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 30) +time.sleep(4) -time.sleep(2) -# move_coords = [ -# [120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket -# # above the green 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], -# [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], -# ] +# mc.send_coords([120.8, -134.4, 258.0, -172.72, -5.31, -109.09], 30, 1) # red bucket +# time.sleep(4) -# mc.send_coords([126.6, -118.1, 305.0, -157.57, -13.72, -75.3],20,1) -# time.sleep(2) -# mc.send_coords([104.9, 176.7, 242.6, -166.66, -9.44, -52.47],20,1) # above the blue bucket -# time.sleep(2) -# mc.send_coords([-20.0, 176.7, 242.6, -166.66, -9.44, -52.47],20,1) # abobe the gray bucket -# time.sleep(2) -# mc.send_coords([120.1,151.6,250.0,-173.34,-8.15,-110.11],20,1) -# time.sleep(2) -# mc.send_coords([104.9, 176.7, 242.6, -166.66, -9.44, -52.47],20,1) +# mc.send_coords([219.8, -126.4, 249.7, -158.68, -7.93, -101.6], 30, 1) # green bucket +# time.sleep(4) + +# mc.send_coords([124.7, 145.3, 250.4, -173.5, -2.23, -11.7], 30, 1) # above the blue bucket +# time.sleep(4) + +# mc.send_coords([14.6, 175.9, 250.4, -177.42, -0.08, 25.93], 30, 1) # abobe the gray bucket +# time.sleep(4) + +# mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20, 0) +# mc.send_angles([1.4, 0, -53.61, -33.39, -3.51, -20.3],20) +# time.sleep(3) + +# mc.send_coords([155.8, -8.4, 140, -173.3, -5.48, -57.9], 30, 1) +# time.sleep(6) + +# mc.send_coords([161.5, -1.1, 115.6, -177.4, 1.09, -51.97], 30, 1) +# time.sleep(3) -mc.send_angles([-26.11, -6.94, -55.01, -24.16, 0, 15],20) # mc.release_all_servos() -time.sleep(3) -print(mc.get_angles()) -# mc.send_angles([-1.14, 3.63, -87.8, 9.05, -3.07, 15],20) -time.sleep(2) -# print(mc.get_angles()) -# mc.send_angles([17.4, -10.1, -87.27, 5.8, -2.02, 15],20) -# time.sleep(2) -# print(mc.get_angles()) - -# mc.release_servo(6) -mc.release_all_servos() -# mc.set_servo_calibration(6) -# if os.listdir(path,filename='blue'): -# pass \ No newline at end of file +# time.sleep(1) +# while True: +# print("angles:%s"% mc.get_angles()) +# print("coords:%s"% mc.get_coords()) +# print("\n") diff --git a/mycobot_description/urdf/mecharm/mecharm_aikit.urdf b/mycobot_description/urdf/mecharm/mecharm_aikit.urdf index 2392f1d..d5c81f3 100644 --- a/mycobot_description/urdf/mecharm/mecharm_aikit.urdf +++ b/mycobot_description/urdf/mecharm/mecharm_aikit.urdf @@ -6,7 +6,7 @@ - +