融合A^(*)与TEB算法的机器人多任务导航调度研究  

Research on multi-task navigation and scheduling for robots by fusing A^(*) and TEB algorithms

作　　者：郭烈[1,2] 齐国栋 赵一兵 黄亮[1] GUO Lie;QI Guodong;ZHAO Yibing;HUANG Liang(School of Automotive Engineering,Dalian University of Technology,Dalian 116024,Liaoning China;Ningbo Institute of Dalian University of Technology,Ningbo 315016,Zhejiang China)

机构地区：[1]大连理工大学汽车工程学院,辽宁大连116024 [2]大连理工大学宁波研究院,浙江宁波315016

出　　处：《华中科技大学学报（自然科学版）》2023年第2期82-88,共7页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(51975089,51975088,52175078);辽宁省自然科学基金资助项目(2021-MS-127)。

摘　　要：为提高机器人工作效率,提出一种基于A^(*)与时间弹性带算法(time eletic band,TEB)的多任务导航调度算法.通过提高障碍物邻接栅格点的代价值,增大A^(*)算法所规划路径与障碍物之间的距离,完成路径的平滑处理;将局部规划算法输出的控制指令进行PID (proportional-integral-differential)控制,提出一种融合PID控制的TEB算法,减小了指令的波动范围;通过人机交互操作获得目标点数量和位置,按照由近及远的原则实现机器人的多目标任务调度与导航.实验证明:改进后的A^(*)算法规避了穿越障碍物的现象,将邻接路径点转角控制在45°之内,改进后的TEB算法使机器人的速度和角速度方差分别减小47.1%和18.2%,多任务导航调度算法能够实现自主输入导航目标点数量与位置坐标功能的正常运转,机器人能够停止在距离目标点0.2 m的预设范围之内.To enhance the efficiency of robots,a multi-task navigation path planning algorithm based on A^(*)and time eletic band(TEB) was proposed.By increasing the cost value of the adjacent grid points of the obstacles,the distance between the path planned by the A^(*)algorithm and the obstacles can be increased and the smoothing of the path was completed. By subjecting the control commands output using the local planning algorithm with proportional-integral-differential(PID) control,a TEB algorithm that integrated PID was proposed to reduce the fluctuation range of the commands. The number and position of target points can be achieved through human-computer interaction,and the multi-target task scheduling and navigation of the robot was realized according to the principle of near-to-far.Experiments show that the improved A^(*) algorithm can avoid the phenomenon of crossing obstacles and control the turning angle of adjacent path points within 45°.The improved TEB algorithm reduces the robot’s velocity and angular velocity variance by 47.1% and 18.2%,respectively.The multi-task navigation scheduling algorithm can automatically input the number of navigation target points and the normal operation of the position coordinate function. The robot can stop at a distance of 0.2 m from the target point.

关 键 词：机器人 路径规划 PID控制 时间弹性带算法 多任务导航 

分 类 号：TH181[机械工程—机械制造及自动化]