现代信息科技2024，Vol.8Issue(16)：60-63,68,5.DOI:10.19850/j.cnki.2096-4706.2024.16.013
基于深度强化学习的移动机器人路径规划研究
Research on Path Planning of Mobile Robots Based on Deep Reinforcement Learning
摘要
Abstract
Given the problem of slow convergence speed when using Deep Reinforcement Learning algorithms for mobile robot path planning,an improved algorithm is proposed.It designs the learning potential score of samples in the experience replay mechanism,prioritizes the samples based on the learning potential score,and samples them according to the score.It applies improved algorithms to robot path planning tasks and designs reward functions,obstacle avoidance parameters,and path planning experimental environments.Through experimental comparison with comparative algorithms,the convergence speed of the improved algorithm and its effectiveness in path planning tasks are verified.关键词
深度强化学习/路径规划/移动机器人Key words
Deep Reinforcement Learning/path planning/mobile robot分类
信息技术与安全科学引用本文复制引用
荣垂霆,朱恒伟,张宾,刘聪..基于深度强化学习的移动机器人路径规划研究[J].现代信息科技,2024,8(16):60-63,68,5.
