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A Comparative Study of Biology-Inspired Algorithms Applied to Swarm Robots Target Searching

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Advances in Swarm Intelligence (ICSI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9713))

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Abstract

In this study, the mechanisms of some creatures’ behaviors collaborated in swarm are applied to the coordination of swarm robots, especially for them to search target. Three typical biology-inspired algorithms, i.e., Particle Swarm Optimization, Ant Colony Optimization and Genetic Algorithms, are thus compared, systematically. Corresponding tasks and mathematical models are set up. Based on the experimental work within MATLAB, the performances of the concerned algorithms on the difficulty of task mapping, adaptability for various terrains, as well as convergence and stability are elaborately analyzed and verified, which is helpful for designing real physical swarm robotic systems.

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Acknowledgements

This research is supported by the Fundamental Research Funds for the Central Universities (No. 2014KJ032, 20153683), by Shanghai Pujiang Program (No. 15PJ1408400) and the Key Basic Research Project of ‘Shanghai Science and Technology Innovation Plan’ (No. 15JC1403300). Meanwhile, this work is also partially supported by the State Key Laboratory of Robotics and Systems (Harbin Institute of Technology) (No. SKLRS-2015-ZD-03), and the National Science Foundation of China (No. 51579053). All these supports are highly appreciated.

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Authors and Affiliations

  1. Laboratroy of Robotics and Multibody System, School of Mechanical Engineering, Tongji University, No.4800, Cao An Rd., Shanghai, 201804, China

    Qirong Tang, Lu Ding & Fangchao Yu

  2. Department of Mechanical Engineering of Tsinghua University, Graduate School at Shenzhen, Shenzhen, 518055, China

    Lei Zhang

  3. Department of Mechanical Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569, Stuttgart, Germany

    Wei Luo

  4. Institute of Advanced Manufacturing, School of Mechanical Engineering, Tongji University, No.4800, Cao An Rd., Shanghai, 201804, China

    Jian Zhang

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  1. Qirong Tang
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  2. Lei Zhang
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  3. Wei Luo
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  4. Lu Ding
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  5. Fangchao Yu
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  6. Jian Zhang
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Corresponding author

Correspondence to Jian Zhang .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzen University, Shenzhen, China

    Li Li

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Tang, Q., Zhang, L., Luo, W., Ding, L., Yu, F., Zhang, J. (2016). A Comparative Study of Biology-Inspired Algorithms Applied to Swarm Robots Target Searching. In: Tan, Y., Shi, Y., Li, L. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9713. Springer, Cham. https://doi.org/10.1007/978-3-319-41009-8_52

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  • DOI: https://doi.org/10.1007/978-3-319-41009-8_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41008-1

  • Online ISBN: 978-3-319-41009-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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