移动机器人速度平滑代码

以下是一个基于ROS的移动机器人速度平滑示例代码，使用了ROS中的PID控制器：

#!/usr/bin/env python
import rospy
from geometry_msgs.msg import Twist, PoseStamped
from nav_msgs.msg import Odometry
from move_base_msgs.msg import MoveBaseAction, MoveBaseGoal
import actionlib

class RobotController:
    def __init__(self):
        # 初始化ROS节点
        rospy.init_node('robot_controller', anonymous=True)
        
        # 订阅机器人当前位置和速度
        rospy.Subscriber('/odom', Odometry, self.odom_callback)
        rospy.Subscriber('/cmd_vel', Twist, self.vel_callback)
        
        # 初始化移动机器人的客户端
        self.move_base_client = actionlib.SimpleActionClient('move_base', MoveBaseAction)
        self.move_base_client.wait_for_server()
        
        # 初始化机器人速度控制器
        self.vel_pub = rospy.Publisher('/cmd_vel', Twist, queue_size=1)
        self.vel_msg = Twist()
        self.linear_speed = 0
        self.angular_speed = 0
        
        # 初始化机器人位置信息
        self.current_pose = PoseStamped()
        
    def odom_callback(self, odom_msg):
        self.current_pose.pose = odom_msg.pose.pose
        
    def vel_callback(self, vel_msg):
        self.linear_speed = vel_msg.linear.x
        self.angular_speed = vel_msg.angular.z
        
    def move_to_goal(self, goal_x, goal_y):
        # 创建目标点
        goal = MoveBaseGoal()
        goal.target_pose.header.frame_id = "map"
        goal.target_pose.header.stamp = rospy.Time.now()
        goal.target_pose.pose.position.x = goal_x
        goal.target_pose.pose.position.y = goal_y
        goal.target_pose.pose.orientation.w = 1.0
        
        # 发送目标点给移动机器人的客户端
        self.move_base_client.send_goal(goal)
        
        # 等待机器人移动到目标点
        self.move_base_client.wait_for_result()
        
    def pid_control(self, error, prev_error, integral, Kp, Ki, Kd):
        # 计算PID控制器的输出
        pid_output = Kp * error + Ki * integral + Kd * (error - prev_error)
        
        # 更新误差累积项和上一次误差
        integral += error
        prev_error = error
        
        return pid_output, integral, prev_error
        
    def smooth_velocity(self, linear_speed, angular_speed):
        # 设置PID控制器的参数
        Kp_linear = 1.0
        Ki_linear = 0.1
        Kd_linear = 0.05
        Kp_angular = 1.0
        Ki_angular = 0.1
        Kd_angular = 0.05
        
        # 计算线速度和角速度的误差
        linear_error = linear_speed - self.linear_speed
        angular_error = angular_speed - self.angular_speed
        
        # 计算PID控制器的输出
        linear_output, self.linear_integral, self.prev_linear_error = self.pid_control(linear_error, self.prev_linear_error, self.linear_integral, Kp_linear, Ki_linear, Kd_linear)
        angular_output, self.angular_integral, self.prev_angular_error = self.pid_control(angular_error, self.prev_angular_error, self.angular_integral, Kp_angular, Ki_angular, Kd_angular)
        
        # 发布平滑后的机器人速度控制消息
        self.vel_msg.linear.x = self.linear_speed + linear_output
        self.vel_msg.angular.z = self.angular_speed + angular_output
        self.vel_pub.publish(self.vel_msg)
        
    def stop_robot(self):
        # 停止机器人移动
        self.move_base_client.cancel_all_goals()
        self.vel_msg.linear.x = 0
        self.vel_msg.angular.z = 0
        self.vel_pub.publish(self.vel_msg)
        
if __name__ == '__main__':
    try:
        # 创建机器人控制器对象
        controller = RobotController()
        
        # 移动机器人到指定位置
        controller.move_to_goal(1.0, 1.0)
        
        # 平滑控制机器人向左旋转
        controller.smooth_velocity(0, 0.5)
        rospy.sleep(2)
        controller.stop_robot()
        
    except rospy.ROSInterruptException:
        pass

以上代码仅供参考，具体的速度平滑算法需要根据机器人的具体情况进行调整和优化。