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Mobile Robot Navigation Using Particle Swarm Optimization and Adaptive NN

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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  • 42 Citations

Abstract

This paper presents a novel design for mobile robot using particle swarm optimization (PSO) and adaptive NN control. The adaptive NN control strategy guarantees that robot with nonholonomic constraints can follow smooth trajectories. Based on this property, a PSO algorithm for path planning is proposed. The path planning generates smooth path with low computational cost to avoid obstacles, so that robot can use smooth control strategy to track the trajectory.

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References

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Author information

Authors and Affiliations

  1. Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Av. Padre Tomás Pereira S.J., Taipa, Macao SAR, P.R. China

    Yangmin Li & Xin Chen

Authors
  1. Yangmin Li
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  2. Xin Chen
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Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, Y., Chen, X. (2005). Mobile Robot Navigation Using Particle Swarm Optimization and Adaptive NN. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_76

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