OpenCV实现机器人对物体进行移动跟随

Love The Way You Lie 2022-09-17 04:19 118阅读 0赞

转载自：[OpenCV实现机器人对物体进行移动跟随 - 古月居][OpenCV_ -]

OpenCV实现机器人对物体进行移动跟随  
小黑鸭  
分类：机器视觉  
发布时间 2020.12.02阅读数 2436 评论数 1  
机器人对物体进行移动跟随

1.物体识别  
2.移动跟随

1.物体识别  
本案例实现对特殊颜色物体的识别，并实现根据物体位置的改变进行控制跟随。

import cv2 as cv  
\# 定义结构元素  
kernel = cv.getStructuringElement(cv.MORPH\_RECT, (3, 3))  
\# print kernel  
capture = cv.VideoCapture(0)  
print capture.isOpened()  
ok, frame = capture.read()  
lower\_b = (65, 43, 46)  
upper\_b = (110, 255, 255)  
height, width = frame.shape\[0:2\]  
screen\_center = width / 2  
offset = 50  
while ok:  
\# 将图像转成HSV颜色空间  
hsv\_frame = cv.cvtColor(frame, cv.COLOR\_BGR2HSV)  
\# 基于颜色的物体提取  
mask = cv.inRange(hsv\_frame, lower\_b, upper\_b)  
mask2 = cv.morphologyEx(mask, cv.MORPH\_OPEN, kernel)  
mask3 = cv.morphologyEx(mask2, cv.MORPH\_CLOSE, kernel)  
\# 找出面积最大的区域  
\_, contours, \_ = cv.findContours(mask3, cv.RETR\_EXTERNAL, cv.CHAIN\_APPROX\_SIMPLE)  
maxArea = 0  
maxIndex = 0  
for i, c in enumerate(contours):  
area = cv.contourArea(c)  
if area > maxArea:  
maxArea = area  
maxIndex = i  
\# 绘制  
cv.drawContours(frame, contours, maxIndex, (255, 255, 0), 2)  
\# 获取外切矩形  
x, y, w, h = cv.boundingRect(contours\[maxIndex\])  
cv.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)  
\# 获取中心像素点  
center\_x = int(x + w/2)  
center\_y = int(y + h/2)  
cv.circle(frame, (center\_x, center\_y), 5, (0, 0, 255), -1)  
\# 简单的打印反馈数据，之后补充运动控制  
if center\_x < screen\_center - offset:  
print "turn left"  
elif screen\_center - offset <= center\_x <= screen\_center + offset:  
print "keep"  
elif center\_x > screen\_center + offset:  
print "turn right"  
cv.imshow("mask4", mask3)  
cv.imshow("frame", frame)  
cv.waitKey(1)

ok, frame = capture.read()

实际效果图  
1  
![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAVFlJTlk_size_20_color_FFFFFF_t_70_g_se_x_16][]  
2.移动跟随  
结合ROS控制turtlebot3或其他机器人运动，turtlebot3机器人的教程见我另一个博文：ROS控制Turtlebot3 首先启动turtlebot3，如下代码可以放在机器人的树莓派中，将相机插在USB口即可 代码示例：

import rospy  
import cv2 as cv  
from geometry\_msgs.msg import Twist  
def shutdown():  
twist = Twist()  
twist.linear.x = 0  
twist.angular.z = 0  
cmd\_vel\_Publisher.publish(twist)  
print "stop"  
if \_\_name\_\_ == '\_\_main\_\_':  
rospy.init\_node("follow\_node")  
rospy.on\_shutdown(shutdown)  
rate = rospy.Rate(100)  
cmd\_vel\_Publisher = rospy.Publisher("/cmd\_vel", Twist, queue\_size=1)  
\# 定义结构元素  
kernel = cv.getStructuringElement(cv.MORPH\_RECT, (3, 3))  
\# print kernel  
capture = cv.VideoCapture(0)  
print capture.isOpened()  
ok, frame = capture.read()  
lower\_b = (65, 43, 46)  
upper\_b = (110, 255, 255)  
height, width = frame.shape\[0:2\]  
screen\_center = width / 2  
offset = 50  
while not rospy.is\_shutdown():  
\# 将图像转成HSV颜色空间  
hsv\_frame = cv.cvtColor(frame, cv.COLOR\_BGR2HSV)  
\# 基于颜色的物体提取  
mask = cv.inRange(hsv\_frame, lower\_b, upper\_b)  
mask2 = cv.morphologyEx(mask, cv.MORPH\_OPEN, kernel)  
mask3 = cv.morphologyEx(mask2, cv.MORPH\_CLOSE, kernel)  
\# 找出面积最大的区域  
\_, contours, \_ = cv.findContours(mask3, cv.RETR\_EXTERNAL, cv.CHAIN\_APPROX\_SIMPLE)  
maxArea = 0  
maxIndex = 0  
for i, c in enumerate(contours):  
area = cv.contourArea(c)  
if area > maxArea:  
maxArea = area  
maxIndex = i  
\# 绘制  
cv.drawContours(frame, contours, maxIndex, (255, 255, 0), 2)  
\# 获取外切矩形  
x, y, w, h = cv.boundingRect(contours\[maxIndex\])  
cv.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)  
\# 获取中心像素点  
center\_x = int(x + w / 2)  
center\_y = int(y + h / 2)  
cv.circle(frame, (center\_x, center\_y), 5, (0, 0, 255), -1)  
\# 简单的打印反馈数据，之后补充运动控制  
twist = Twist()  
if center\_x < screen\_center - offset:  
twist.linear.x = 0.1  
twist.angular.z = 0.5  
print "turn left"  
elif screen\_center - offset <= center\_x <= screen\_center + offset:  
twist.linear.x = 0.3  
twist.angular.z = 0  
print "keep"  
elif center\_x > screen\_center + offset:  
twist.linear.x = 0.1  
twist.angular.z = -0.5  
print "turn right"  
else:  
twist.linear.x = 0  
twist.angular.z = 0  
print "stop"  
\# 将速度发出  
cmd\_vel\_Publisher.publish(twist)  
\# cv.imshow("mask4", mask3)  
\# cv.imshow("frame", frame)  
cv.waitKey(1)  
rate.sleep()

ok, frame = capture.read()

机器视觉  
物体识别  
Python  
openCV  
移动跟随

原创文章作者：小黑鸭。如若转载，请注明出处：古月居 https://www.guyuehome.com/18737

[OpenCV_ -]: https://www.guyuehome.com/18737
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAVFlJTlk_size_20_color_FFFFFF_t_70_g_se_x_16]: /images/20220828/ce90b56e035f44efbfe67a71900081c0.png