Impact force minimization algorithm for collaborative robots using impact force prediction model

Tae Jung Kim, Ji Hoon Kim, Kuk Hyun Ahn, Jae Bok Song

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

Abstract

Recently, the demand for collaborative robots is increasing in the industrial field. However, as the collaborative robots share the same workspace with human workers, there is a high possibility of collision between the robot and the worker. A possible method to ensure the safety of a human worker is to restrict the impact force that the robot exerts on the worker during a collision. That is, if the impact force can be predicted, the robot motion that causes excessive impact force can be detected and handled properly before the actual robot motion. To this end, an algorithm for predicting the impact force generated by a collision is proposed, and a method for ensuring the human safety, by modifying the trajectory of the robot when the excessive impact is predicted with current motion, is investigated. To establish the impact force prediction model, collision experiments were performed with a 6-DOF collaborative robot and a dummy. Moreover, an algorithm for minimizing the impact force, by reducing the end-effector velocity of the robot when excessive impact is predicted from the established model, is proposed to ensure the human safety. The performance of the algorithm was verified through various experiments.

Original languageEnglish
Title of host publication2020 20th International Conference on Control, Automation and Systems, ICCAS 2020
PublisherIEEE Computer Society
Pages869-872
Number of pages4
ISBN (Electronic)9788993215205
DOIs
Publication statusPublished - 2020 Oct 13
Event20th International Conference on Control, Automation and Systems, ICCAS 2020 - Busan, Korea, Republic of
Duration: 2020 Oct 132020 Oct 16

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2020-October
ISSN (Print)1598-7833

Conference

Conference20th International Conference on Control, Automation and Systems, ICCAS 2020
CountryKorea, Republic of
CityBusan
Period20/10/1320/10/16

Keywords

  • Collaborative robot
  • Collision safety
  • Impact

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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