机构学及机器人

基于主从任务转化的闭环控制避障算法*

  • 张建华 ,
  • 胡平 ,
  • 张小俊 ,
  • 刘进长 ,
  • 刘璇
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  • 1. 河北工业大学机械工程学院 天津 300130;
    2.科技部高技术研究发展中心 北京 100044
张建华,男,1979年出生,副教授。主要研究方向为智能机器人技术。E-mail:jhzhang@hebut.edu.cn刘进长(通信作者),男,1964年出生,研究员。主要研究方向为智能机器人技术。E-mail:liujc@htrdc.com

网络出版日期: 2017-01-05

基金资助

* 国家自然科学基金(E51575157)、机器人学国家重点实验室基金(2015002)和河北省自然科学基金重点(E2016202342)资助项目; 20160531收到初稿,20161011收到修改稿;

Closed Loop Control Algorithm for Obstacle Avoidance Based on the Transformation of Master and Slave Tasks

  • ZHANG Jianhua ,
  • HU Ping ,
  • ZHANG Xiaojun ,
  • LIU Jinchang ,
  • LIU Xuan
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  • 1. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130;
    2. High Technology Center of Ministry of Science and Technology, Beijing 100044

Online published: 2017-01-05

摘要

冗余度机械臂避障算法研究一直是机器人领域的研究热点之一。针对传统算法的不足提出一种基于主从任务转化的闭环控制避障算法。主从任务转化通过监测机械臂各杆件与障碍物之间的最小距离变化实现避障任务和期望轨迹跟踪任务的主从切换,从而解决当障碍物位于机械臂末端期望轨迹上时避障运动和期望轨迹跟踪运动存在的相互冲突问题。考虑到机械臂避障时其末端跟踪精度差的问题,引入对冗余度机器臂末端期望位置和实际位置的误差控制,使得机械臂末端跟踪精度显著提高。同时,该算法还适用于多障碍物避障和动态避障且具有计算量小和躲避速度变化连续等优点。通过三自由度平面冗余度机器臂的仿真试验,验证了该算法的正确性。仿真结果表明,该算法能够有效解决当障碍物位于机械臂末端期望轨迹上时存在的冲突问题,而且机械臂在避障的同时也能够高精度跟踪末端期望轨迹,且能够完成多障碍物避障和动态避障。

本文引用格式

张建华 , 胡平 , 张小俊 , 刘进长 , 刘璇 . 基于主从任务转化的闭环控制避障算法*[J]. 机械工程学报, 2017 , 53(1) : 21 -27 . DOI: 10.3901/JME.2017.01.021

Abstract

The research on obstacle avoidance algorithm of redundant manipulator has always been one of the hotspots in the field of robot. A closed loop control algorithm for obstacle avoidance based on the transformation of master and slave tasks is proposed aiming at the shortcomings of the traditional algorithm. It achieves the switch of the task of obstacle avoidance and the task of the desired trajectory tracking by monitoring the minimum distance between the mechanical arm and the obstacle, thus it can solve the conflict between obstacle avoidance and desired trajectory tracking. When mechanical arms avoid obstacle, the end tracking accuracy is poor, based on this, the error control between the desired and actual end effector locations is introduced which makes the tracking accuracy significantly improved. In addition, the algorithm also has the advantages of small amount of computation and continuous variation of the velocity of escape and it can also be applied to collision avoidance of many obstacles and dynamic obstacle. The algorithm is verified by the simulation experiment of planar redundant robot with three degrees of freedom. The results show that the algorithm can effectively solve the conflict when the obstacle is on the desired tracking and the accuracy is high. It can also finish the obstacle avoidance of many obstacles and dynamic obstacle.

 

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