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Multi-objective Path Planning for Space Exploration Robot Based on Chaos Immune Particle Swarm Optimization Algorithm

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Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7003))

Abstract

Multi-objective path planning for mobile robot in complex environments is a challenging issue in space exploration. In order to improve the efficiency and quality of the multi-objective path planning, a chaos immune particle swarm optimization (CIPSO) algorithm is proposed in this paper, which combines chaos and PSO with immune network theory so as to enhance the searching speed of path planning for mobile robot and insure the safety of space exploration. Simulation results show that the CIPSO has well performance for path planning and obstacle avoidance.

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Author information

Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China

    Wei Hao & Shiyin Qin

Authors
  1. Wei Hao
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  2. Shiyin Qin
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Hao, W., Qin, S. (2011). Multi-objective Path Planning for Space Exploration Robot Based on Chaos Immune Particle Swarm Optimization Algorithm. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-23887-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23886-4

  • Online ISBN: 978-3-642-23887-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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