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Mobile Robot Path Tracking in Unknown Dynamic Environment

机译:未知动态环境中的移动机器人路径跟踪

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The paper proposes a cooperative system of fuzzy neural networks (FNN) and fuzzy logic control (FLC). And this system is used to on-line path tracking of a mobile robot in unknown dynamic environment, instead of the commonly used FLC to research on this problem. Firstly, the application of FNN based on the kinematics models of mobile robot is described in detail, moreover, it uses an improved back propagation (BP) algorithm to complete the network learning and training. Secondly, it utilizes FLC to fulfill the real-time avoiding obstacles. The simulation results show that the proposed cooperative system is effective and robust, meanwhile possesses better abilities of path tracking and real-time avoiding obstacles in unknown dynamic environment.
机译:提出了模糊神经网络(FNN)和模糊逻辑控制(FLC)的协同系统。并且该系统用于在未知动态环境中对移动机器人进行在线路径跟踪,而不是常用的FLC对此问题进行研究。首先,详细介绍了基于移动机器人运动学模型的神经网络的应用,并使用改进的BP算法完成网络学习和训练。其次,它利用FLC来实现实时回避障碍。仿真结果表明,所提出的协同系统有效,鲁棒,同时在未知动态环境下具有较好的路径跟踪能力和实时避障能力。

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