基于opencv-Python小车循线学习笔记
加入摄像头模块，让小车实现自动循迹行驶
思路为：摄像头读取图像，进行二值化，将白色的赛道凸显出来
选择下方的一行像素，黑色为0，白色为255
找到白色值的中点
目标中点与标准中点(320)进行比较得出偏移量
根据偏移量，采用PID控制器来控制小车左右轮的转速
# coding:utf-8
import RPi.GPIO as gpio
import time
import cv2
import numpy as np
def sign(x):
if x>0:
return 1.0
else:
return -1.0
# 定义引脚
pin1 = 16
#pin2 = 12
pin3 = 22
#pin4 = 18
# 设置GPIO口为BOARD编号规范
gpio.setmode(gpio.BOARD)
# 设置GPIO口为输出
gpio.setup(pin1, gpio.OUT)
#gpio.setup(pin2, gpio.OUT)
gpio.setup(pin3, gpio.OUT)
#gpio.setup(pin4, gpio.OUT)
# 设置PWM波,频率为500Hz
pwm1 = gpio.PWM(pin1, 500)
#pwm2 = gpio.PWM(pin2, 500)
pwm3 = gpio.PWM(pin3, 500)
#pwm4 = gpio.PWM(pin4, 500)
# pwm波控制初始化
pwm1.start(0)
#pwm2.start(0)
pwm3.start(0)
#pwm4.start(0)
# center定义
center_now = 320
# 打开摄像头，图像尺寸640*480(长*高)，opencv存储值为480*640(行*列)
cap = cv2.VideoCapture(0)
# PID 初始数据
error = [0.0] * 3
adjust = [0.0] * 3
# PID 参数配置
kp = 1.5
ki = 0.4
kd = 0.1
target = 320
while (1):
ret, frame = cap.read()
# 转化为灰度图
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 大津法二值化
retval, dst = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU)
# 膨胀，白区域变大
dst = cv2.dilate(dst, None, iterations=2)
# # 腐蚀，白区域变小
# dst = cv2.erode(dst, None, iterations=6)
# 单看第400行的像素值s
color = dst[400]
# 找到白色的像素点个数
white_count = np.sum(color == 255)
# 找到白色的像素点索引
white_index = np.where(color == 255)
# 防止white_count=0的报错
if white_count == 0:
white_count = 1
# 找到黑色像素的中心点位置
center_now = (white_index[0][white_count - 1] + white_index[0][0]) / 2
# 计算出center_now与标准中心点的偏移量
direction = center_now - 320
print(direction)
# 停止
if abs(direction) > 250:
pwm1.ChangeDutyCycle(0)
# pwm2.ChangeDutyCycle(0)
pwm3.ChangeDutyCycle(0)
# pwm4.ChangeDutyCycle(0)
# 更新PID误差
error[0] = error[1]
error[1] = error[2]
error[2] = center_now - target
# 更新PID输出(增量式PID表达式)
adjust[0] = adjust[1]
adjust[1] = adjust[2]
# adjust(k+2) = adjust(k+1) + kp * (e(k+2) - e(k+1)) + ki * e(k+2) + kd * (e(k+2)-2*e(k+1)+e(k))
adjust[2] = adjust[1] \
+ kp*(error[2] - error[1]) \
+ ki*error[2] \
+ kd*(error[2] - 2*error[1] + error[0]);
# 饱和输出限制在70绝对值之内
if abs(adjust[2]) > 70:
adjust[2] = sign(adjust[2]) * 70
# 执行PID
# 右转
elif adjust[2] > 0:
pwm1.ChangeDutyCycle(30+ adjust[2])
# pwm2.ChangeDutyCycle(0)
pwm3.ChangeDutyCycle(30)
# pwm4.ChangeDutyCycle(0)
# 左转
elif adjust[2] < 0:
pwm1.ChangeDutyCycle(30)
# pwm2.ChangeDutyCycle(0)
pwm3.ChangeDutyCycle(30 + abs(adjust[2]))
# pwm4.ChangeDutyCycle(0)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
time.sleep(0.05)
# 释放清理
cap.release()
cv2.destroyAllWindows()
pwm1.stop()
#pwm2.stop()
pwm3.stop()
#pwm4.stop()
gpio.cleanup()
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