-
Notifications
You must be signed in to change notification settings - Fork 131
/
testvisionplanner.py
executable file
·190 lines (144 loc) · 6.75 KB
/
testvisionplanner.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
#!/usr/bin/env python
"""
moveit_cartesian_path.py - Version 0.1 2016-07-28
Based on the R. Patrick Goebel's moveit_cartesian_demo.py demo code.
Plan and execute a Cartesian path for the end-effector.
Created for the Pi Robot Project: http://www.pirobot.org
Copyright (c) 2014 Patrick Goebel. All rights reserved.
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.5
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details at:
http://www.gnu.org/licenses/gpl.html
"""
import rospy, sys, numpy as np
import moveit_commander
from copy import deepcopy
import geometry_msgs.msg
import moveit_msgs.msg
import cv2, cv_bridge
from sensor_msgs.msg import Image
from std_msgs.msg import Header
from trajectory_msgs.msg import JointTrajectory
from trajectory_msgs.msg import JointTrajectoryPoint
class MoveItCartesianPath:
def __init__(self):
self.bridge = cv_bridge.CvBridge()
self.image_sub = rospy.Subscriber('/ur5/usbcam/image_raw', Image, self.image_callback)
rospy.init_node("moveit_cartesian_path", anonymous=False)
rospy.loginfo("Starting node moveit_cartesian_path")
rospy.on_shutdown(self.cleanup)
# Initialize the move_group API
moveit_commander.roscpp_initialize(sys.argv)
# Initialize the move group for the ur5_arm
self.arm = moveit_commander.MoveGroupCommander('manipulator')
# Get the name of the end-effector link
end_effector_link = self.arm.get_end_effector_link()
# Set the reference frame for pose targets
reference_frame = "/base_link"
# Set the ur5_arm reference frame accordingly
self.arm.set_pose_reference_frame(reference_frame)
# Allow replanning to increase the odds of a solution
self.arm.allow_replanning(True)
# Allow some leeway in position (meters) and orientation (radians)
self.arm.set_goal_position_tolerance(0.01)
self.arm.set_goal_orientation_tolerance(0.1)
# Get the current pose so we can add it as a waypoint
start_pose = self.arm.get_current_pose(end_effector_link).pose
# Initialize the waypoints list
waypoints = []
# Set the first waypoint to be the starting pose
# Append the pose to the waypoints list
wpose = deepcopy(start_pose)
# Set the next waypoint to the right 0.5 meters
wpose.position.x = -0.2
wpose.position.y = -0.2
wpose.position.z = 0.3
waypoints.append(deepcopy(wpose))
wpose.position.x = 0.1052
wpose.position.y = -0.4271
wpose.position.z = 0.4005
wpose.orientation.x = 0.4811
wpose.orientation.y = 0.4994
wpose.orientation.z = -0.5121
wpose.orientation.w = 0.5069
waypoints.append(deepcopy(wpose))
if np.sqrt((wpose.position.x-start_pose.position.x)**2+(wpose.position.x-start_pose.position.x)**2 \
+(wpose.position.x-start_pose.position.x)**2)<0.1:
rospy.loginfo("Warnig: target position overlaps with the initial position!")
# self.arm.set_pose_target(wpose)
# Set the internal state to the current state
self.arm.set_start_state_to_current_state()
# Plan the Cartesian path connecting the waypoints
"""moveit_commander.move_group.MoveGroupCommander.compute_cartesian_path(
self, waypoints, eef_step, jump_threshold, avoid_collisios= True)
Compute a sequence of waypoints that make the end-effector move in straight line segments that follow the
poses specified as waypoints. Configurations are computed for every eef_step meters;
The jump_threshold specifies the maximum distance in configuration space between consecutive points
in the resultingpath. The return value is a tuple: a fraction of how much of the path was followed,
the actual RobotTrajectory.
"""
plan, fraction = self.arm.compute_cartesian_path(waypoints, 0.01, 0.0, True)
# plan = self.arm.plan()
# If we have a complete plan, execute the trajectory
if 1-fraction < 0.2:
rospy.loginfo("Path computed successfully. Moving the arm.")
num_pts = len(plan.joint_trajectory.points)
rospy.loginfo("\n# intermediate waypoints = "+str(num_pts))
self.arm.execute(plan)
rospy.loginfo("Path execution complete.")
else:
rospy.loginfo("Path planning failed")
def cleanup(self):
rospy.loginfo("Stopping the robot")
# Stop any current arm movement
self.arm.stop()
#Shut down MoveIt! cleanly
rospy.loginfo("Shutting down Moveit!")
moveit_commander.roscpp_shutdown()
moveit_commander.os._exit(0)
def image_callback(self,msg):
# BEGIN BRIDGE
image = self.bridge.imgmsg_to_cv2(msg,desired_encoding='bgr8')
# END BRIDGE
# BEGIN HSV
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
# END HSV
# BEGIN FILTER
lower_red = np.array([ 0, 100, 100])
upper_red = np.array([10, 255, 255])
mask = cv2.inRange(hsv, lower_red, upper_red)
(_, cnts, _) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
#area = cv2.contourArea(cnts)
h, w, d = image.shape
# print h, w, d (800,800,3)
#BEGIN FINDER
M = cv2.moments(mask)
if M['m00'] > 0:
cx = int(M['m10']/M['m00'])
cy = int(M['m01']/M['m00'])
# cx range (55,750) cy range( 55, ~ )
# END FINDER
# Isolate largest contour
# contour_sizes = [(cv2.contourArea(contour), contour) for contour in cnts]
# biggest_contour = max(contour_sizes, key=lambda x: x[0])[1]
for i, c in enumerate(cnts):
area = cv2.contourArea(c)
if area > 7500:
cv2.circle(image, (cx, cy), 10, (0,0,0), -1)
cv2.putText(image, "({}, {})".format(int(cx), int(cy)), (int(cx-5), int(cy+15)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
cv2.drawContours(image, cnts, -1, (255, 255, 255),1)
# BEGIN circle
# print max(contour_sizes)[0]
#area = cv2.contourArea(cnts)
#print area
#END circle
cv2.namedWindow("window", 1)
cv2.imshow("window", image )
cv2.waitKey(5)
follower=MoveItCartesianPath()
rospy.spin()