Apply PSO Algorithm with Searching Space Improvements on a 5 Degrees of Freedom Robot

Thanh Trung Nguyen, Ngoc Linh Tao, Van Tinh Nguyen, Ngoc Tam Bui, V. H. Nguyen, Dai Watanabe

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

Abstract

In this research, Particle Swarm Optimization (PSO) algorithm has been applied to solve the Inverse Kinematic (IK) problem for redundant serial manipulator robots. The new point of the study is to consider the continuity of the joints' variable. By noting this problem, the process of solving the Inverse Kinematic problem for the robots by the optimal algorithm has been significantly improved in terms of accuracy, execution time, and standard deviation (STD) as well as the number of iterations needed. The algorithm has been applied to solve the Inverse Kinematic problem on the 5-Degree of Freedom 5R robot model. The results show that just using the PSO algorithm with the above search domain limit has improved the quality of IK process.

Original languageEnglish
Title of host publicationIRCE 2020 - 2020 3rd International Conference on Intelligent Robotics and Control Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages75-80
Number of pages6
ISBN (Electronic)9781728189727
DOIs
Publication statusPublished - 2020 Aug
Event3rd International Conference on Intelligent Robotics and Control Engineering, IRCE 2020 - Virtual, Oxford, United Kingdom
Duration: 2020 Aug 102020 Aug 12

Publication series

NameIRCE 2020 - 2020 3rd International Conference on Intelligent Robotics and Control Engineering

Conference

Conference3rd International Conference on Intelligent Robotics and Control Engineering, IRCE 2020
CountryUnited Kingdom
CityVirtual, Oxford
Period20/8/1020/8/12

Keywords

  • Degree of Freedom (DOF)
  • Inverse Kinematic (IK)
  • Particle Swarm Optimization (PSO)
  • redundant robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Control and Optimization

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