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A Review of Mobile Robot Path Planning Based on Deep Reinforcement Learning Algorithm

Yanwei Zhao, Yinong Zhang, Shuying Wang

Year
2021
Citations
21
Access
Open access

Abstract

Abstract Path planning refers to that the mobile robot can obtain the surrounding environment information and its own state information through the sensor carried by itself, which can avoid obstacles and move towards the target point. Deep reinforcement learning consists of two parts: reinforcement learning and deep learning, mainly used to deal with perception and decision-making problems, has become an important research branch in the field of artificial intelligence. This paper first introduces the basic knowledge of deep learning and reinforcement learning. Then, the research status of deep reinforcement learning algorithm based on value function and strategy gradient in path planning is described, and the application research of deep reinforcement learning in computer game, video game and autonomous navigation is described. Finally, I made a brief summary and outlook on the algorithms and applications of deep reinforcement learning.

Keywords

Reinforcement learningArtificial intelligenceComputer scienceMotion planningDeep learningRobot learningPath (computing)Mobile robotLearning classifier systemRobot

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