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Swarm Intelligence-Based Approach for Macroscopic Scale Odor Source Localization Using Multi-robot System

Anh Quy Hoang and Minh Trien Pham (2016) Swarm Intelligence-Based Approach for Macroscopic Scale Odor Source Localization Using Multi-robot System. Advances in Information and Communication Technology, 538 . pp. 593-602. ISSN 2194-5357

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Official URL: http://www.springer.com/gp/book/9783319490724

Abstract

Odor source localization is a problem of great importance. Two mainstream methods among numerous proposed ones are probabilistic algorithms and bio-inspired algorithms. Compared to probabilistic algorithms, biomimetic approaches are much less intensive in term of computational cost. Thus, despite their slightly worse performance, biomimetic approaches have received much more attention. In this paper, a novel method based on a bio-inspired algorithm - Particle Swarm Optimization (PSO) - is proposed for a multi-robot system (MRS). The proposed algorithm makes use of wind information and immediate odor gradient to enhance the performance of the MRS. A mechanism based on Artificial Potential Field (APF) is utilized to ensure non-collision movement of the robots. This method is tested by simulation on Matlab. Data for the test scenarios, all in large scales, are generated using Fluent. Nearly 2000 runs are carried out and the simulation results confirm the proposed algorithm’s effectiveness.

Item Type:Article
Subjects:Electronics and Communications
Electronics and Communications > Electronics and Computer Engineering
Divisions:Faculty of Electronics and Telecommunications (FET)
ID Code:2247
Deposited By: Hoàng Anh Quý
Deposited On:25 Dec 2016 16:59
Last Modified:10 Jun 2017 12:01

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