多目标遗传算法在水下机器人路径规划中的应用

Path Planning Based on Multi-Objective Genetic Algorithm for AUV on VCF Electronic Chart

  • 摘要: 依据VCF电子海图,提出了一种对水下机器人进行路径规划的多目标遗传算法,采用可变长的实数坐标编码、适应度函数评价了影响航路优劣的多个因素,设计了选择、交叉、变异、修补、删除等遗传算子以及种群置换方法。在生成初始种群和设计遗传算子时引入领域知识,使所生成路径尽量不穿越障碍区域,有效地提高了大范围路径规划算法的收敛速度。试验表明,采用该MOGA算法进行路径规划可提高算法的收敛速度和全局寻优能力。

     

    Abstract: A multi-objective genetic algorithm for AUV path planning based on Vector Chart Format electronic charts is presented in this paper.In this method,real-code of variable length is adopted,several factors concerned with path quality are evaluated through fitness functions,and genetic operators such as selection,crossover,mutation,repair,deletion,together with population replacement method are proposed.Domain knowledge is introduced during the initial population formation and genetic operator design,in order that the produced path intersects obstruction area as less as possible,therefore the algorithm converges more quickly in the case of large-scale path planning.Experiments show that this multi-objective genetic algorithm can effectively improve algorithm convergence rate and global optimization ability.

     

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