Designing path of collision avoidance for mobile manipulator in worker safety monitoring system using reinforcement learning

Jiwoong Lim, Jihyun Lee, Changjoo Lee, Gunwoo Kim, Younghoon Cha, Joonhyung Sim, Sungsoo Rhim

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

Abstract

Mobile manipulator is a robot for the next generation of processes. The mobile manipulator can increase process efficiency by being combined with the collaborative robot system. However, due to worker safety issues, simultaneous control of the mobile manipulator is still difficult. In this paper, we present the designing path of collision avoidance of a mobile manipulator for the safety of workers. By monitoring the position and velocity of a worker modeled as a cylinder, the mobile manipulator designs a path to avoid the worker using reinforcement learning. We learned the robot using simulation, and we checked the mobile and manipulator move to the destination by avoiding the worker.

Original languageEnglish
Title of host publicationISR 2021 - 2021 IEEE International Conference on Intelligence and Safety for Robotics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-97
Number of pages4
ISBN (Electronic)9781665438629
DOIs
Publication statusPublished - 4 Mar 2021
Event2nd IEEE International Conference on Intelligence and Safety for Robotics, ISR 2021 - Virtual, Nagoya, Japan
Duration: 4 Mar 20216 Mar 2021

Publication series

NameISR 2021 - 2021 IEEE International Conference on Intelligence and Safety for Robotics

Conference

Conference2nd IEEE International Conference on Intelligence and Safety for Robotics, ISR 2021
Country/TerritoryJapan
CityVirtual, Nagoya
Period4/03/216/03/21

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