A GA based combinatorial auction algorithm for multi-robot cooperative hunting

Jianwei Gong*, Jianyong Qi, Guangming Xiong, Huiyan Chen, Wanning Huang

*Corresponding author for this work

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

28 Citations (Scopus)

Abstract

In order to improve the hunting efficiency of multi-robot cooperative hunting in complicated environment: multi-target and dynamic continues surrounding, a combinatorial auction model based on genetic algorithm (GACA) was presented in this paper. The model adopted genetic algorithm to solve the winner determination problem in combinatorial auction. We also compared the combinatorial auction model based task allocation method with the traditional single item auction model in solving dynamic and complex task allocation problem in multi-robot cooperation. The simulation experiments were conducted in a self-developed visible multi-robot simulation platform, OpenSim, and the results showed the whole process of hunting was very smooth, and the cost time cost by our algorithm was much shorter than the compared method.

Original languageEnglish
Title of host publicationProceedings - 2007 International Conference on Computational Intelligence and Security, CIS 2007
Pages137-141
Number of pages5
DOIs
Publication statusPublished - 2007
Event2007 International Conference on Computational Intelligence and Security, CIS'07 - Harbin, Heilongjiang, China
Duration: 15 Dec 200719 Dec 2007

Publication series

NameProceedings - 2007 International Conference on Computational Intelligence and Security, CIS 2007

Conference

Conference2007 International Conference on Computational Intelligence and Security, CIS'07
Country/TerritoryChina
CityHarbin, Heilongjiang
Period15/12/0719/12/07

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