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Cooperative Coevolutionary Adaptive Genetic Algorithm in Path Planning of Cooperative Multi-Mobile Robot Systems

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Abstract

In this paper, path planning of cooperative multi-mobile robot systems, an example of multi-agent systems, is discussed with the proposal of a novel Cooperative Coevolutionary Adaptive Genetic Algorithm (CCAGA). At the same time, for such genetic algorithms based path planning, a novel fixed-length decimal encoding mechanism for paths of each mobile robot is also proposed. Such cooperative coevolutionary adaptive genetic algorithm is suitable for parallel computation, which is convenient to solve complicated problems. Meanwhile, simulation results show that this algorithm has the property of robust convergency.

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References

  1. Fleury, G., Goujou, J.-Y., Gourgand, M., and Lacomme, P.: Multi-agent approach and stochastic optimization: Random events in manufacturing systems, J. Intelligent Manufacturing 10(1) (1999), 81–101.

    Google Scholar 

  2. Srinivas, M. and Pootraik, L. M.: Genetic algorithms: A survey, IEEE Computer (1994), 17–26.

  3. Sugiara, K. and Smith, J.: Genetic algorithms for adaptive planning of path and trajectory of a mobile robot in 2D terrains, IEICE Trans. Inf. Syst. E82-D(1) (1999), 309–316.

    Google Scholar 

  4. Nearchou, A. C.: Path planning of a mobile robot using genetic heuristics, Robotica 16 (1998), 575–588.

    Google Scholar 

  5. Potter, M. A. and De Jong, K. A.: A cooperative coevolutionary approach to function optimization, in: Y. Davidor, H.-P. Schwefel, and R. Manner (eds), Parallel Problem Solving form Nature - PPSNIII, Lecture Notes in Comput. Sci. 866, Springer-Verlag, Berlin, 1994, pp. 249–257.

    Google Scholar 

  6. Sakawa, M. and Yauchi, K.: Coevolutionary genetic algorithms for nonconvex nonlinear programming problems: Revised genocop III, Cybernet. Systems 29 (1998), 885–899.

    Google Scholar 

  7. Srinivas, M. and Pootraik, L. M.: Adaptive probabilities of crossover and mutation in genetic algorithms, IEEE Trans. Systems Man Cybernet. 24(4) (1994), 656–667.

    Google Scholar 

  8. II-Kwon Jeong and Ju-Jang Lee: A self-organizing genetic algorithm for multimodal function optimization, Artificial Life Robotics 2 (1998), 48–52.

    Google Scholar 

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Cai, Z., Peng, Z. Cooperative Coevolutionary Adaptive Genetic Algorithm in Path Planning of Cooperative Multi-Mobile Robot Systems. Journal of Intelligent and Robotic Systems 33, 61–71 (2002). https://doi.org/10.1023/A:1014463014150

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  • DOI: https://doi.org/10.1023/A:1014463014150

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