使用python写一个OpenCV和机械臂配合使用的代码
时间: 2023-07-15 20:11:12 浏览: 196
以下是一个使用Python编写的OpenCV和机械臂配合使用的示例代码:
```python
import cv2
import numpy as np
import time
from pyrobot import Robot
# 初始化机械臂
robot = Robot('locobot')
# 设置机械臂末端执行器的初始位置
robot.arm.go_home()
# 初始化摄像头
cap = cv2.VideoCapture(0)
while True:
# 读取摄像头中的图像
ret, frame = cap.read()
# 将图像转换为灰度图
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 对灰度图进行二值化处理
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
# 查找轮廓
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# 找到最大的轮廓
max_area = 0
max_contour = None
for contour in contours:
area = cv2.contourArea(contour)
if area > max_area:
max_area = area
max_contour = contour
# 如果找到了轮廓
if max_contour is not None:
# 找到轮廓的中心点
M = cv2.moments(max_contour)
cx = int(M['m10'] / M['m00'])
cy = int(M['m01'] / M['m00'])
# 将中心点的坐标转换为机械臂的坐标系中的坐标
x = (cx - 320) / 320 * 0.2
y = (cy - 240) / 240 * 0.2
# 移动机械臂到指定位置
robot.arm.set_ee_pose_relative([x, y, 0, 0, 0, 0], plan=True)
# 显示图像
cv2.imshow('frame', frame)
# 按下q键退出程序
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# 释放摄像头
cap.release()
# 关闭窗口
cv2.destroyAllWindows()
```
这个程序使用机械臂和摄像头配合实现了跟踪物体的功能。程序首先初始化机械臂并将其设置为初始位置,然后初始化摄像头并进入循环,不断读取摄像头中的图像。程序将图像转换为灰度图并进行二值化处理,然后查找图像中的轮廓。程序找到最大的轮廓并计算出轮廓的中心点,然后将中心点的坐标转换为机械臂的坐标系中的坐标,并将机械臂移动到指定位置。程序最后显示图像,直到按下q键退出程序。
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