Immune Optimization of Path Planning for Coal Mine Rescue Robot

نویسندگان

  • Peng Li
  • Hua Zhu
چکیده

In order to further improve the ability of global path planning of coal mine rescue robot in the complex environment, a bacterial foraging algorithm-based polyclonal selection algorithm (BFA-PSA) is proposed. In order to verify the superiority of the BFA-PSA, the proposed algorithm is tested by traveling salesman problem (TSP) and compared with genetic algorithm (GA) and clonal selection algorithm (CSA). Finally, on the basis of grid environment model, the BFA-PSA is used in the optimization of path planning for coal mine rescue robot. The optimization results of the TSP show that the searching ability and efficiency of the BFA-PSA are improved. And the optimization results of path planning for coal mine rescue robot in the grid environment model show the better robustness and validity of the BFA-PSA.

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تاریخ انتشار 2016