-----形状的ros巡线代码

在ROS (Robot Operating System) 中编写形状识别并进行巡线的代码通常涉及到视觉SLAM（Simultaneous Localization And Mapping）算法以及机器学习库，如OpenCV用于图像处理，以及ROS包如tf和nav_msgs用于定位和路径规划。以下是一个简化的示例：

import rospy
from geometry_msgs.msg import Twist
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
import cv2

class LineFollowingNode:
    def __init__(self):
        self.bridge = CvBridge()
        self.subscriber = rospy.Subscriber("/camera/image_color", Image, self.image_callback)
        self.publisher = rospy.Publisher('/cmd_vel', Twist, queue_size=10)

        self.prev_color = None
        self.speed = Twist()

    def image_callback(self, data):
        try:
            img = self.bridge.imgmsg_to_cv2(data, "bgr8")
            # 进行边缘检测或颜色识别寻找线条
            edges = cv2.Canny(img, threshold1=50, threshold2=150)
            color_difference = cv2.absdiff(img, self.prev_color)

            # 根据检测结果调整速度
            if lines_found and color_difference is not None:
                # ...此处编写基于检测到的线条和颜色差异调整速度的逻辑
                self.speed.linear.x = ...  # 线条靠近则减速，远离则加速
                self.speed.angular.z = ...  # 转向以跟随线条

            self.prev_color = img
            self.publisher.publish(self.speed)
        except CvBridgeError as e:
            print(e)

if __name__ == "__main__":
    rospy.init_node('line_following')
    line_follower = LineFollowingNode()
    rospy.spin()

在这个例子中，节点会订阅相机的图像消息，然后转换成OpenCV可以处理的格式。接着进行边缘检测或颜色对比来识别车道线。根据检测到的结果，它会实时发布控制指令给移动机器人。