Q-learning based Collision-free and Optimal Path Planning for Mobile Robot in Dynamic Environment

Jing Kai Lin, Shi Lin Ho, Kuan Yu Chou*, Yon Ping Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Mobile robots with artificial intelligence are more and more popular on the rescue and human-service in complex environment. Path planning techniques for robots become the important topic to achieve it. Recently, Q-learning becomes a popular topic since the property of model-free. In this paper, generating the collision-free and optimal path with Q-learning for an mobile robot is proposed. Q-learning is adopted to let the mobile robot achieve the destination successfully through designing the states, actions and reward function in this paper. The system structure is integrated by two parts. First, the Q-learning algorithm is applied to find the collision-free and optimal path for an mobile robot. Second, Robot Operation System (ROS) is used to be the data transmission system among the dynamic path planning system, global position system and mobile robot. In the simulation result, the dynamic path planning system generates the collision-free and optimal path for the mobile robot. In addition, the movable obstacles appear on the original path suddenly, then the dynamic path planning system would regenerate a new optimal path to achieve the goal successfully.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages427-428
Number of pages2
ISBN (Electronic)9781665470506
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan
Duration: 6 Jul 20228 Jul 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Conference

Conference2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Country/TerritoryTaiwan
CityTaipei
Period6/07/228/07/22

Keywords

  • Q-learning
  • dynamic path planning
  • mobile robot
  • optimal and collision-free path planning
  • tracking control

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