Mobile Robot Path Planning Based on Hierarchical Reinforcement Learning in Unknown Dynamic Environment

Abstract

A path-planning algorithm based on hierarchical reinforcement learning is presented.Since the reinforcement learning approach is introduced,the algorithm is provided with the capability of learning without environment model.The hierarchical reinforcement learning method is mainly employed for updating local strategies.So,this algorithm can eliminate its dependence on the static information of the global environment or the moving information of the dynamic obstacles. Simulation experiment shows the feasibility of the algorithm.Although there is no obvious advantage in planning speed,the learning ability of the algorithm in unknown dynamic environment is unique.