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Global optimal path planning for mobile robots based on hybrid approach with high diversity and memorization

  • Yun Qian Miao*
  • , Alaa Khamis
  • , Fakhreddine O. Karray
  • , Mohamed S. Kamel
  • *Corresponding author for this work

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

3 Scopus citations

Abstract

This paper presents a hybrid approach to the path planning problem of autonomous robots that combines potential field (PF) method and genetic algorithm (GA). The proposed PF+GA approach takes the strength of both potential field and genetic algorithm to find global optimal collision-free paths. In this integrated frame, the PF is designed as gradient-based searching strategy to exploit local optimal, and the GA is used to explore over the whole problem space. Different implementation strategies are examined through simulations in 2D scenarios. The conducted experiments show that global optimal path can be achieved effectively using the proposed approach with a strategy of high diversity and memorization.

Original languageEnglish
Title of host publicationAutonomous and Intelligent Systems - Second International Conference, AIS 2011, Proceedings
Pages1-10
Number of pages10
DOIs
StatePublished - 2011
Externally publishedYes
Event2nd International Conference on Autonomous and Intelligent Systems, AIS 2011 - Burnaby, BC, Canada
Duration: 22 Jun 201124 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6752 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Autonomous and Intelligent Systems, AIS 2011
Country/TerritoryCanada
CityBurnaby, BC
Period22/06/1124/06/11

Keywords

  • genetic algorithm
  • hybrid approach
  • path planning
  • potential field

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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