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Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013 pp 329–337Cite as

An Efficient and Improved Particle Swarm Optimization Algorithm for Swarm Robots System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 212))

Abstract

In recent years, the number of researches in which swarm intelligence shown by individual communication in swarm robots is increasing. As one of the representative algorithms in swarm intelligence, particle swarm optimization has been applied to many fields because of its simple concept, easy realizing and good optimization characteristics. However, it still has some disadvantages such as easy falling in the local best situation and solving the discrete optimization problems poor. In this paper, genetic algorithm has been integrated with particle swarm optimization to improve the performance of the algorithm; the simple particle swarm optimization algorithm has been simulated in the Player/Stage and compared with the particle swarm optimization. The simulation shows that the algorithm is faster and more efficient.

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Acknowledgments

This work is jointly supported by NSFC under Grant No. 60903067, 61170117. Beijing Natural Science Foundation under Grant No. 4122049, Funding Project for Beijing Excellent Talents Training under Grant No. 2011D009006000004, and the Fundamental Research Funds for the Central Universities(FRF-JX-12-002, FRF-TP-12-083A).

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, People’s Republic of China

    Zhiguo Shi, Xiaomeng Zhang, Jun Tu & Zhiyong Yang

Authors
  1. Zhiguo Shi
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  2. Xiaomeng Zhang
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  3. Jun Tu
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  4. Zhiyong Yang
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Corresponding author

Correspondence to Zhiguo Shi .

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Editors and Affiliations

  1. School of Science, Anhui University of Science & Technology, Huainan, China

    Zhixiang Yin

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. Anhui University of Science & Technology, Huainan, China

    Xianwen Fang

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© 2013 Springer-Verlag Berlin Heidelberg

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Shi, Z., Zhang, X., Tu, J., Yang, Z. (2013). An Efficient and Improved Particle Swarm Optimization Algorithm for Swarm Robots System. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_40

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  • DOI: https://doi.org/10.1007/978-3-642-37502-6_40

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37501-9

  • Online ISBN: 978-3-642-37502-6

  • eBook Packages: EngineeringEngineering (R0)

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