基于CVRL的移动机器人导航控制

CVRL-BASED NAVIGATION CONTROL OF MOBILE ROBOT

  • 摘要: 针对移动机器人的导航问题,本文提出一种具有连续向量输出的再励学习算法(Reinforcement Learningwith Continuous Vectoroutput:CVRL).CVRL具有层次结构,低层是单元动作网络层,通过组合动作产生连续向量输出;高层是建立在组合单元动作空间上的Q学习单元,实现组合动作的选择.文中给出了CVRL导航控制器的具体实现,并通过仿真实验验证了其有效性

     

    Abstract: In this paper, a new reinforcement learning(CVRL) algorithm with continuous vector output is proposed as to the navigation problem of mobile robot. CVRL is hierarchically structured. The lower layer is composed with several groups of unit actions and real-valued vector output can be produced based on action combination. The higher layer is a Q-Learning unit defined on the space of combined action, its responsibility is the selection of a proper combined actions. The detailed implementation of the CVRL navigation controller is given, and the simulation results demonstrate its effectiveness.

     

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