Adaptive formation behaviors of multi-robot for cooperative exploration

Yutaka Yasuda, Naoyuki Kubota, Yuichiro Toda

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

7 Citations (Scopus)

Abstract

This paper proposes a method for constituting the formation of a multi-robot system according to dynamically changing environments. First, we apply a method of multi-objective behavior coordination for integrating behavior outputs from the fuzzy control for collision avoidance and target tracing. Second, we apply a spring model to calculate the temporary target position of each robot for the formation behavior. Third, we discuss multi-robot behaviors based on the concept of coupling. The tight coupling is realized by the spring model while the loose coupling is realized by the individual decision making based on connection and disconnection with other robots. Furthermore, the proposed method is applied to the exploration in unknown environments. Finally, we discuss the effectiveness of the proposed method through several simulation results.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
DOIs
Publication statusPublished - Oct 23 2012
Externally publishedYes
Event2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 - Brisbane, QLD, Australia
Duration: Jun 10 2012Jun 15 2012

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Other

Other2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
CountryAustralia
CityBrisbane, QLD
Period6/10/126/15/12

Keywords

  • exploration
  • formation
  • fuzzy control
  • monitoring
  • multi-agent system

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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  • Cite this

    Yasuda, Y., Kubota, N., & Toda, Y. (2012). Adaptive formation behaviors of multi-robot for cooperative exploration. In 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 [6251150] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZ-IEEE.2012.6251150