NAO机器人基于opencv走黑线循迹的python2代码

下面是一个基于OpenCV的Python2代码，用于NAO机器人沿着黑线行驶的循迹。该代码使用NAOqi SDK连接到NAO机器人，使用机器人的摄像头读取实时图像，并使用OpenCV处理图像以检测黑线。然后，代码使用机器人的移动API将机器人沿着黑线移动。

import cv2
import numpy as np
from naoqi import ALProxy

# Connect to NAOqi SDK
IP = "NAO_IP"
PORT = 9559
motion_proxy = ALProxy("ALMotion", IP, PORT)
camera_proxy = ALProxy("ALVideoDevice", IP, PORT)

# Set camera parameters
resolution = 2  # VGA
color_space = 11  # RGB
fps = 10
camera_id = 0  # Top camera

# Subscribe to camera
camera_proxy.unsubscribe("python_client")
camera_proxy.subscribe("python_client", resolution, color_space, fps)
camera_proxy.setParam(18, camera_id)  # Set camera ID

# Set robot parameters
max_speed = 0.5
duration = 0.5

# Main loop
while True:
    # Get image from camera
    image_raw = camera_proxy.getImageRemote("python_client")

    # Convert image to OpenCV format
    width = image_raw[0]
    height = image_raw[1]
    image = np.frombuffer(image_raw[6], dtype=np.uint8).reshape((height, width, 3))

    # Process image
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    _, threshold = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)
    contours, _ = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    # Find largest contour
    largest_contour = None
    largest_area = 0
    for contour in contours:
        area = cv2.contourArea(contour)
        if area > largest_area:
            largest_area = area
            largest_contour = contour

    # Follow contour
    if largest_contour is not None:
        # Get center of largest contour
        M = cv2.moments(largest_contour)
        cx = int(M['m10'] / M['m00'])
        cy = int(M['m01'] / M['m00'])

        # Move robot
        if cx < 320:
            motion_proxy.move(max_speed, 0, 0)
        elif cx > 320:
            motion_proxy.move(-max_speed, 0, 0)
        else:
            motion_proxy.move(0, 0, 0)

    # Sleep
    time.sleep(duration)

# Unsubscribe from camera
camera_proxy.unsubscribe("python_client")

请注意，该代码仅提供了简单的黑线循迹示例，并且可能需要进行调整以适应不同的环境和黑线条件。此外，该代码使用Python2，如果您使用的是Python3，则需要进行一些修改以使其兼容。