A Flexible Collision-Free Trajectory Planning for Multiple Robot Arms by Combining Q-Learning and RRT

Tomoya Kawabe, Tatsushi Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose an approach for real-time collision-free trajectory planning of multiple robot manipulators in a common workspace. In recent years, robot arms are often introduced to factories in place of human beings, and it has become important how efficiently multiple robot arms can be operated in a small space. The problem of trajectory planning for multiple robot arms is often solved by graph search algorithms, however, it is difficult for the conventional approach to provide flexible trajectory planning to cope with unexpected situations such as robot arm failure. Therefore, we propose a combined method for Q-learning and RRT for the trajectory planning problem. The effectiveness of the proposed method is further verified using numerical experiments. The planned trajectories is able to guarantee a certain degree of optimality when the motion trajectory is generated by combining reinforcement learning than by using only the graph search algorithm. The results indicate that the time required to generate the motion trajectory is reduced by the proposed method.

Original languageEnglish
Title of host publication2022 IEEE 18th International Conference on Automation Science and Engineering, CASE 2022
PublisherIEEE Computer Society
Pages2363-2368
Number of pages6
ISBN (Electronic)9781665490429
DOIs
Publication statusPublished - 2022
Event18th IEEE International Conference on Automation Science and Engineering, CASE 2022 - Mexico City, Mexico
Duration: Aug 20 2022Aug 24 2022

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2022-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference18th IEEE International Conference on Automation Science and Engineering, CASE 2022
Country/TerritoryMexico
CityMexico City
Period8/20/228/24/22

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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