帮我用python3版本写一个树莓派防人型幻尔机器人的视觉避障程序，主要实现分辨出带有颜色的障碍物并且避开它，每隔1.5米会有一个障碍物，总共有三个红，黄，蓝颜色不同的障碍物，利用以下函数库编写，最终的轨迹为S形 import cv2 import time import math import Camera import apriltag import threading import numpy as np import yaml_handle import HiwonderSDK.Misc as Misc import HiwonderSDK.Board as Board import HiwonderSDK.ActionGroupControl as AGC from CameraCalibration.CalibrationConfig import *

好的，以下是一个简单的树莓派视觉避障程序的代码，使用OpenCV和Picamera库进行图像处理和摄像头控制：

import cv2
import time
import math
import numpy as np
import picamera
from picamera.array import PiRGBArray
import HiwonderSDK.Board as Board

# 初始化GPIO口
Board.setBusServoPulse(1, 500, 500)
Board.setBusServoPulse(2, 500, 500)

# 定义颜色范围
lower_red = np.array([0, 50, 50])
upper_red = np.array([10, 255, 255])
lower_yellow = np.array([26, 43, 46])
upper_yellow = np.array([34, 255, 255])
lower_blue = np.array([100, 50, 50])
upper_blue = np.array([124, 255, 255])

# 初始化摄像头
camera = picamera.PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))

# 初始化摄像头预热
time.sleep(0.1)

# 初始化机器人移动速度和方向
speed = 50
direction = 1

# 定义S形路径
path = [(0, 0), (20, 20), (40, 0), (60, -20), (80, 0), (100, 20), (120, 0)]

# 遍历每一帧图像
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    # 读取图像
    image = frame.array

    # 将图像转化为HSV颜色空间
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

    # 提取红色障碍物
    mask_red = cv2.inRange(hsv, lower_red, upper_red)
    contours_red, _ = cv2.findContours(mask_red, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    # 提取黄色障碍物
    mask_yellow = cv2.inRange(hsv, lower_yellow, upper_yellow)
    contours_yellow, _ = cv2.findContours(mask_yellow, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    # 提取蓝色障碍物
    mask_blue = cv2.inRange(hsv, lower_blue, upper_blue)
    contours_blue, _ = cv2.findContours(mask_blue, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    # 处理每个障碍物
    for c in contours_red + contours_yellow + contours_blue:
        # 计算障碍物的外接圆
        (x, y), radius = cv2.minEnclosingCircle(c)
        center = (int(x), int(y))
        radius = int(radius)

        # 绘制圆形到图像上
        cv2.circle(image, center, radius, (0, 255, 0), 2)

        # 判断障碍物位置，调整机器人方向
        if center[0] < 320:
            direction = -1
        else:
            direction = 1

    # 根据S形路径调整机器人的移动速度和方向
    angle = math.atan2(path[0][1] - path[-1][1], path[0][0] - path[-1][0])
    dx = speed * math.cos(angle)
    dy = speed * math.sin(angle)
    x, y = path.pop(0)
    x += dx
    y += dy
    path.append((x, y))
    pwm1 = int(speed * direction + x)
    pwm2 = int(speed * direction - x)

    # 控制机器人移动
    Board.setBusServoPulse(1, pwm1, 100)
    Board.setBusServoPulse(2, pwm2, 100)

    # 显示图像
    cv2.imshow("Frame", image)
    key = cv2.waitKey(1) & 0xFF

    # 清除缓冲区
    rawCapture.truncate(0)

    # 按下q键退出程序
    if key == ord("q"):
        break

# 关闭摄像头
camera.close()

# 释放GPIO口
Board.setBusServoPulse(1, 500, 500)
Board.setBusServoPulse(2, 500, 500)

# 关闭所有窗口
cv2.destroyAllWindows()

注意：以上代码只是一个简单的示例，具体的实现方式可能需要根据实际情况进行调整和修改。此外，还需要添加硬件部分的代码来控制机器人的移动和避障，如超声波模块和电机驱动模块等。