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Motion Control and Trajectory Planning for Obstacle Avoidance of the Mobile Parallel Robot Driven by Three Tracked Vehicles

Published online by Cambridge University Press:  11 September 2020

Shuzhan Shentu ,
Fugui Xie Open the ORCID record for Fugui Xie [Opens in a new window] ,
Xin-Jun Liu  and
Zhao Gong
Shuzhan Shentu
Affiliation:
The State Key Laboratory of Tribology & Tsinghua University (DME)-Siemens Joint Research Center for Advanced Robotics, Department of Mechanical Engineering (DME), Tsinghua University, Beijing 100084, China. E-mails: stsz17@mails.tsinghua.edu.cn, gongzhao@126.com
Fugui Xie
Affiliation:
The State Key Laboratory of Tribology & Tsinghua University (DME)-Siemens Joint Research Center for Advanced Robotics, Department of Mechanical Engineering (DME), Tsinghua University, Beijing 100084, China. E-mails: stsz17@mails.tsinghua.edu.cn, gongzhao@126.com Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084, China. E-mail: xiefg@mail.tsinghua.edu.cn
Xin-Jun Liu*
Affiliation:
The State Key Laboratory of Tribology & Tsinghua University (DME)-Siemens Joint Research Center for Advanced Robotics, Department of Mechanical Engineering (DME), Tsinghua University, Beijing 100084, China. E-mails: stsz17@mails.tsinghua.edu.cn, gongzhao@126.com Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084, China. E-mail: xiefg@mail.tsinghua.edu.cn
Zhao Gong
Affiliation:
The State Key Laboratory of Tribology & Tsinghua University (DME)-Siemens Joint Research Center for Advanced Robotics, Department of Mechanical Engineering (DME), Tsinghua University, Beijing 100084, China. E-mails: stsz17@mails.tsinghua.edu.cn, gongzhao@126.com
*
*Corresponding author. E-mail: xinjunliu@mail.tsinghua.edu.cn
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Summary

This paper proposes a mobile parallel robot (MPR) and focuses on obstacle avoidance. When analyzing the collision-free trajectories, the coupling constraints caused by the parallel mechanism and the obstacle should be emphatically solved. The solution is to divide the problem into two steps. First, the genetic algorithm is employed to search and optimize the feasible trajectories under the mechanism constraint of the MPR. Then the trajectory tracking controller is designed to make the tracked vehicles move cooperatively and track a trajectory asymptotically. Finally, simulations and experiments are carried out to verify the effectiveness of the solution.

Keywords

Mobile parallel robotTrajectory trackingTrajectory planningGenetic algorithmObstacle avoidance
Type
Article
Information
Robotica , Volume 39 , Issue 6 , June 2021 , pp. 1037 - 1050
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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