ROS机器人编程实践——读书笔记4

一、ROS对图像处理，通过使用cv_bridge包来将ROS里的sensor_msgs/Image转换成OpenCV的格式。

follower_opencv.py

#!/usr/bin/env python
import rospy
from sensor_msgs.msg import Image
import cv2,cv_bridge

class Follower:
        def __init__(self):
                self.bridge=cv_bridge.CvBridge()
                cv2.namedWindow("window",1)
                self.image_sub=rospy.Subscriber('camera/rgb/image_raw',Image,self.image_callback)
        def image_callback(self,msg):
                image=self.bridge.imgmsg_to_cv2(msg,desired_encoding='bgr8')
                cv2.imshow("window",image)
                cv2.waitKey(3)
                
rospy.init_node('follower')
follower=Follower()
rospy.spin()

$ roslaunch turtlebot_gazebo turtlebot_world.launch

$python follower_opencv.py

通过移动机器人获取不同的图像。

二、检测指示线

        我们根据颜色对图像进行逐行扫描，让机器人沿着颜色区域中心行进。检测黄线最简单的方法就是通过RGB颜色过滤找出与黄色接近的区域，不过简单的方法并不是很有效，轻微的光照变化，就会很大程度影响结果。将RGB颜色变化到HSV来改善这一问题。HSV将RGB图像分解色调（H）、饱和度（S）、明度（V）。在HSV图像将色调值与黄色接近的区域滤出得到一副二值图。

follower_color_filter.py

#!/usr/bin/env python

import rospy
from sensor_msgs.msg import Image
import cv2, cv_bridge, numpy

class Follower:
    def __init__(self):
        self.bridge = cv_bridge.CvBridge()
        cv2.namedWindow("window", 1)
        self.image_sub = rospy.Subscriber('camera/rgb/image_raw', Image, self.image_callback)
        
    
    def image_callback(self, msg):
        image = self.bridge.imgmsg_to_cv2(msg)
        
        hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
        # yuyv: yellow
        lower_yellow = numpy.array([50, 50, 170])   
        upper_yellow = numpy.array([255, 255, 190])
        
        mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
        masked = cv2.bitwise_and(image, image, mask=mask)
        
        cv2.imshow("window", mask)
        cv2.imshow("hsv", hsv)
        cv2.waitKey(3)
        
rospy.init_node('follower')
follower = Follower()
rospy.spin()

三、跟踪黄线

        我们只考虑图像1/3高处的20行宽的部分，程序检测大概1m处的指示线的中心，然后标记一个圆点。

follower_line_finder.py

#!/usr/bin/env python
# BEGIN ALL
import rospy, cv2, cv_bridge, numpy
from sensor_msgs.msg import Image


class Follower:
  def __init__(self):
    self.bridge = cv_bridge.CvBridge()
    cv2.namedWindow("window", 1)
    self.image_sub = rospy.Subscriber('camera/rgb/image_raw', 
                                      Image, self.image_callback)

  def image_callback(self, msg):
    image = self.bridge.imgmsg_to_cv2(msg,desired_encoding='bgr8')
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    lower_yellow = numpy.array([ 10,  10,  10])
    upper_yellow = numpy.array([255, 255, 250])
    mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
    
    # BEGIN CROP
    h, w, d = image.shape
    search_top = 3*h/4
    search_bot = search_top + 20
    mask[0:search_top, 0:w] = 0
    mask[search_bot:h, 0:w] = 0
    # END CROP
    # BEGIN FINDER
    M = cv2.moments(mask)
    if M['m00'] > 0:
      cx = int(M['m10']/M['m00'])
      cy = int(M['m01']/M['m00'])
    # END FINDER
    # BEGIN CIRCLE
      cv2.circle(image, (cx, cy), 20, (0,0,255), -1)
    # END CIRCLE

    cv2.imshow("window", image)
    cv2.waitKey(3)

rospy.init_node('follower')
follower = Follower()
rospy.spin()
# END ALL

四、循线运动

        follower_p.py

#!/usr/bin/env python
# BEGIN ALL
import rospy, cv2, cv_bridge, numpy
from sensor_msgs.msg import Image
from geometry_msgs.msg import Twist

class Follower:
  def __init__(self):
    self.bridge = cv_bridge.CvBridge()
    cv2.namedWindow("window", 1)
    #self.image_sub = rospy.Subscriber('usb_cam/image_raw', 
    self.image_sub = rospy.Subscriber('camera/rgb/image_raw', 
                                      Image, self.image_callback)
    self.cmd_vel_pub = rospy.Publisher('cmd_vel_mux/input/teleop',
                                       Twist, queue_size=1)
    self.twist = Twist()
    
  def image_callback(self, msg):
    image = self.bridge.imgmsg_to_cv2(msg,desired_encoding='bgr8')
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    # gray color
    lower_yellow = numpy.array([ 10,  10,  10])
    upper_yellow = numpy.array([255, 255, 250])
    
    mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
    
    h, w, d = image.shape
    search_top = 3*h/4
    search_bot = 3*h/4 + 20
    mask[0:search_top, 0:w] = 0
    mask[search_bot:h, 0:w] = 0
    M = cv2.moments(mask)
    if M['m00'] > 0:
      cx = int(M['m10']/M['m00'])
      cy = int(M['m01']/M['m00'])
      cv2.circle(image, (cx, cy), 20, (0,0,255), -1)
      # BEGIN CONTROL
      err = cx - w/2
      self.twist.linear.x = 0.15
      self.twist.angular.z = -float(err) / 300   # 400: 0.1, 300: 0.15, 250, 0.2
      self.cmd_vel_pub.publish(self.twist)
      # END CONTROL
    cv2.imshow("window", image)
    cv2.imshow("mask", mask)
    cv2.waitKey(3)

rospy.init_node('follower')
follower = Follower()
rospy.spin()
# END ALL