A bio-inspired neural network based PSO method for robot path planning
A bio-inspired neural network based PSO method for robot path planning
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DOI：
10.1109/fskd.2017.8393137
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发表时间：
2017-07
期刊：
影响因子：
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通讯作者：
J. Ni;Zhitong Zhang;Baiyan Su;Xinnan Fan;Wei Liang
中科院分区：
文献类型：
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作者：
J. Ni;Zhitong Zhang;Baiyan Su;Xinnan Fan;Wei Liang
复杂未知环境下的机器人路径规划是一项具有挑战性的任务。针对这一问题，提出了一种基于仿生神经网络的改进PSO方法，其中利用仿生神经网络来优化基于PSO的方法的适应度函数。引入动态环境建模方法来实现未知环境下的路径规划。最后，对各种环境进行了一些模拟实验。结果表明了该方法的有效性。
Robot path planning in complex and unknown environment is a challenging task. To deal with this problem, an improved PSO method based on bio-inspired neural network is proposed, where a bio-inspired neural network is used to optimize the fitness function of the PSO based method. A dynamic environment modeling method is introduced to realize the path planning in unknown environment. Finally, some simulation experiments on various environments are conducted. The results show the efficiency of the proposed method.