Evolutionary fuzzy control of three robots cooperatively carrying an object for wall following through the fusion of continuous ACO and PSO

Min Ge Lai, Chia Feng Juang*, I. Fang Chung

*Corresponding author for this work

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

2 Scopus citations

Abstract

This paper proposes evolutionary fuzzy control of three robots cooperatively carrying an object in executing a convex wall following behavior. The object is not connected to the robots and may fall off for a failed control. Evolutionary fuzzy control of a single robot for wall following is first performed. Then, evolutionary fuzzy control of two robots cooperatively carrying a long strip object along the wall is performed. For the carry of a larger object for wall following, a third robot is included to cooperate with the two successfully controlled robots. Fuzzy controller of the third robot is also learned through a data-driven evolutionary learning approach. To improve learning efficiency of the FC, the swarm intelligence algorithm of adaptive fusion of continuous ant colony optimization and particle swarm optimization (AF-CACPSO) is employed. Simulations show the effectiveness of the evolutionary fuzzy control approach for the three cooperative object-carrying robots.

Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence - 8th International Conference, ICSI 2017, Proceedings
EditorsBen Niu, Hideyuki Takagi, Yuhui Shi, Ying Tan
PublisherSpringer Verlag
Pages225-232
Number of pages8
ISBN (Print)9783319618326
DOIs
StatePublished - 2017
Event8th International Conference on Swarm Intelligence, ICSI 2017 - Fukuoka, Japan
Duration: 27 Jul 20171 Aug 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10386 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Swarm Intelligence, ICSI 2017
Country/TerritoryJapan
CityFukuoka
Period27/07/171/08/17

Keywords

  • Ant colony optimization
  • Control
  • Evolutionary fuzzy systems
  • Evolutionary robots
  • Fuzzy
  • Optimization
  • Particle
  • Swarm

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