Comparison between heterogeneous ant colony optimization algorithm and Genetic Algorithm for global path planning of mobile robot

Joon Woo Lee, Byoung Suk Choi, Kyoung Taik Park, Ju Jang Lee

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

5 Scopus citations

Abstract

We proposed a novel ACO algorithm to solve the global path planning problems in the previous paper, called Heterogeneous ACO (HACO) algorithm. In this paper, we compare the performance of HACO algorithm with the modified Genetic Algorithm (GA) for global path planning. The HACO algorithm differs from the Conventional ACO (CACO) algorithm for the path planning in three respects. First, we proposed modified Transition Probability Function (TPF) and Pheromone Update Rule (PUR). Second, we newly introduced the Path Crossover (PC) in the PUR. Finally, we also proposed the first introduction of the heterogeneous ants in the ACO algorithm. We apply the proposed HACO algorithm and modified GA to the general global path planning problems and compare the performance of these through the computer simulation.

Original languageEnglish
Title of host publicationProceedings - ISIE 2011
Subtitle of host publication2011 IEEE International Symposium on Industrial Electronics
Pages881-886
Number of pages6
DOIs
StatePublished - 2011
Event2011 IEEE International Symposium on Industrial Electronics, ISIE 2011 - Gdansk, Poland
Duration: 27 Jun 201130 Jun 2011

Publication series

NameProceedings - ISIE 2011: 2011 IEEE International Symposium on Industrial Electronics

Conference

Conference2011 IEEE International Symposium on Industrial Electronics, ISIE 2011
Country/TerritoryPoland
CityGdansk
Period27/06/1130/06/11

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