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Formation Control Optimization for Odor Localization

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Recent Advances on Soft Computing and Data Mining (SCDM 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 549))

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Abstract

This paper presents a swarm robots formation control by using a new hybrid algorithm Fuzzy-Kohonen Networks and Particle Swarm Optimization (FKN-PSO). The FKN-PSO approach is proposed, to overcome the formation control problem due to the loss of a source of odor, caused by the failure in sensor detection, fail in robot motion control and environmental uncertainty in odor localization. The experiments are conducted by using simple swarm robots in the real environment with on-board sensor and processor. The results are compared between FKN-PSO and Fuzzy-PSO to look at the performance of the swarm robots in the process of odor localization. As the results found that the propose algorithm produce fast response and efficiently process than Fuzzy-PSO, they are able to locate the source of odor in a short time and capable for keeping in formation to find the target.

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Acknowledgments

The Authors thank to The Ministry of Technology Research and Higher Education (Kemenristek-Dikti), Indonesia and Sriwijaya University (UNSRI) for their financial support in Competitive Grants Project.

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Authors and Affiliations

  1. Robotic and Control Lab, Computer Engineering Department, Universitas Sriwijaya, Jln. Raya Palembang-Prabumulih KM 32 Indralaya, Ogan Ilir, Indonesia

    Bambang Tutuko, Siti Nurmaini,  Rendyansyah, P. P. Aditya &  Saparudin

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  1. Bambang Tutuko
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  2. Siti Nurmaini
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  3. Rendyansyah
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  4. P. P. Aditya
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  5. Saparudin
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Correspondence to Bambang Tutuko .

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Editors and Affiliations

  1. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Rozaida Ghazali

  3. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Nazri Mohd Nawi

  4. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

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Tutuko, B., Nurmaini, S., Rendyansyah, Aditya, P.P., Saparudin (2017). Formation Control Optimization for Odor Localization. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-51281-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51279-2

  • Online ISBN: 978-3-319-51281-5

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