判断机械臂抓取到物体的Python程序

判断机械臂是否成功抓取物体的Python程序通常涉及传感器数据处理和机器学习算法。下面是一个简单的示例，假设我们有一个视觉传感器（如摄像头）捕捉物体位置，并使用OpenCV库分析图像：

import cv2
import numpy as np

# 定义阈值和目标区域
threshold = 50   # 物体颜色或灰度对比度阈值
target_area = (x_min, y_min, x_max, y_max)  # 物体预计出现的矩形区域

def detect_object(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    _, thresh = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)
    
    contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:
        if cv2.contourArea(contour) > target_area[2]*target_area[3]:  # 检查面积是否足够大
            x, y, w, h = cv2.boundingRect(contour)  # 获取矩形边界
            return True  # 如果找到物体，返回True

    return False  # 如果未检测到物体，返回False

# 使用相机或视频流获取实时图像
cap = cv2.VideoCapture(0)
while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break
    
    if detect_object(frame):  
        print("Mechanical arm has successfully grabbed the object.")
    else:
        print("Object not detected.")

cap.release()
cv2.destroyAllWindows()