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A probability particle swarm optimizer with information-sharing mechanism for odor source localization

conference contribution
posted on 2017-12-06, 00:00 authored by Qiang Lu, Qing-Long Han
This paper deals with the problem of odor source localization using a multi-robot system. Taking limited communication networks among the multi-robot system into account, a new cooperative search algorithm, namely, a probability particle swarm optimizer with information-sharing mechanism, is proposed and independently executed by each robot, by which the team of robots can be efficiently coordinated to locate a stationary odor source. In order to develop the proposed algorithm, an information-sharing matrix, which is used to store information by learning from the position information of robots, is designed. Based on the matrix, the probable position of the odor source as the new position of the robot is produced by following three simple steps. Finally, the effectiveness of the proposed algorithm is illustrated in the problem of odor source localization.


Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)


Parent Title

Preprints of the 18th International Federation of Automatic Control World Congress (IFAC 2011), Milano, Italy, 28 August-2 September 2011.

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Milano, Italy


Published for IFAC by Pergamon

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Peer Reviewed

  • Yes

Open Access

  • Yes

External Author Affiliations

Centre for Intelligent and Networked Systems (CINS); Institute for Resource Industries and Sustainability (IRIS);

Era Eligible

  • Yes

Name of Conference

International Federation of Automatic Control. World Congress