激光雷达去畸变结果图ros

好的，以下是使用`laser_scan_matcher`包进行激光雷达去畸变处理并展示结果图的ROS代码示例：

#!/usr/bin/env python

import rospy
from sensor_msgs.msg import LaserScan
from laser_scan_matcher.msg import AdjustedCloud
import matplotlib.pyplot as plt
import numpy as np

class LaserScanProcessor:
    def __init__(self):
        self.scan_sub = rospy.Subscriber('/scan', LaserScan, self.scan_callback)
        self.adjusted_sub = rospy.Subscriber('/adjusted_cloud', AdjustedCloud, self.adjusted_callback)
        self.fig, self.ax = plt.subplots(1, 2, figsize=(12, 6))

    def scan_callback(self, msg):
        self.ax[0].clear()
        ranges = np.array(msg.ranges)
        angles = np.linspace(msg.angle_min, msg.angle_max, len(ranges))
        self.ax[0].plot(angles, ranges)
        self.ax[0].set_title('Original Scan')

    def adjusted_callback(self, msg):
        self.ax[1].clear()
        ranges = np.array(msg.ranges)
        angles = np.linspace(msg.angle_min, msg.angle_max, len(ranges))
        self.ax[1].plot(angles, ranges)
        self.ax[1].set_title('Adjusted Scan')
        plt.draw()
        plt.pause(0.001)

if __name__ == '__main__':
    try:
        rospy.init_node('laser_scan_processor')
        processor = LaserScanProcessor()
        plt.show()
        rospy.spin()
    except rospy.ROSInterruptException:
        pass

这个程序订阅原始激光雷达数据和去畸变后的激光雷达数据，通过matplotlib库展示两个图像，左边是原始激光雷达数据，右边是去畸变后的激光雷达数据。可以看到，右边的图像比左边的图像更加平滑。

注意，这个程序需要使用`laser_scan_matcher`包来进行激光雷达去畸变处理，并需要在程序中设置原始激光雷达数据的话题名称和去畸变后的激光雷达数据的话题名称。