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Intelligent guidance of autonomous mobile robots based on adaptive dynamic programming

机译:基于自适应动态规划的自主移动机器人智能制导

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This paper discussed the guidance problem of autonomous mobile robots with multiple constraints: target tracking, synchronization, and obstacle avoidance. The guidance strategy is proposed according to the structure of adaptive dynamic programming to enable the online learning and optimization. An action neural network and a critic neural network are designed to estimate the guidance strategy and cost function, respectively. Then, an optimal intelligent guidance law is obtained according to the designed weight updating rules of neural networks. Finally, the validity of the intelligent guidance scheme is demonstrated with a simulation of five autonomous mobile robots tracking a dynamic target in the obstacle environment.
机译:本文讨论了具有多个约束条件的自主移动机器人的制导问题:目标跟踪,同步和避障。根据自适应动态规划的结构提出了指导策略,以实现在线学习和优化。设计了行动神经网络和评论者神经网络来分别估计制导策略和成本函数。然后,根据设计的神经网络权重更新规则,获得最优的智能制导律。最后,通过对五个自主移动机器人在障碍物环境中跟踪动态目标的仿真,证明了智能制导方案的有效性。

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