Hoang, Anh Quy and Pham, Minh Trien (2017) Swarm Intelligence-Based Approach for Macroscopic Scale Odor Source Localization Using Multi-robot System. In: International Conference on Advances in Information and Communication Technology, 12-13, Dec., 2016, Vietnam.
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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: | Conference or Workshop Item (Lecture) |
|---|---|
| Subjects: | Electronics and Communications Electronics and Communications > Electronics and Computer Engineering |
| Divisions: | Faculty of Electronics and Telecommunications (FET) |
| Depositing User: | Hoàng Anh Quý |
| Date Deposited: | 25 Dec 2016 16:59 |
| Last Modified: | 21 Dec 2017 23:05 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/2247 |
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