首页|期刊导航|东华大学学报（英文版）|Navigation Method Based on Improved Rapid Exploration Random Tree Star-Smart (RRT--Smart) and Deep Reinforcement Learning
东华大学学报（英文版）2022，Vol.39Issue(5)：490-495,6.DOI:10.19884/j.1672-5220.202202458
Navigation Method Based on Improved Rapid Exploration Random Tree Star-Smart (RRT--Smart) and Deep Reinforcement Learning
Navigation Method Based on Improved Rapid Exploration Random Tree Star-Smart (RRT?-Smart) and Deep Reinforcement Learning
摘要
Abstract
A large number of logistics operations are needed to transport fabric rolls and dye barrels to different positions in printing and dyeing plants, and increasing labor cost is making it difficult for plants to recruit workers to complete manual operations. Artificial intelligence and robotics, which are rapidly evolving, offer potential solutions to this problem. In this paper, a navigation method dedicated to solving the issues of the inability to pass smoothly at corners in practice and local obstacle avoidance is presented. In the system, a Gaussian fitting smoothing rapid exploration random tree star-smart (GFS RRT?-Smart) algorithm is proposed for global path planning and enhances the performance when the robot makes a sharp turn around corners. In local obstacle avoidance, a deep reinforcement learning determiner mixed actor critic (MAC) algorithm is used for obstacle avoidance decisions. The navigation system is implemented in a scaled-down simulation factory.关键词
rapid exploration random tree star smart (RRT∗-Smart)/Gaussian fitting/deep reinforcement learning (DRL)/mixed actor critic (MAC)Key words
rapid exploration random tree star smart (RRT∗-Smart)/Gaussian fitting/deep reinforcement learning (DRL)/mixed actor critic (MAC)分类
信息技术与安全科学引用本文复制引用
ZHANG Jue,LI Xiangjian,LIU Xiaoyan,LI Nan,YANG Kaiqiang,ZHU Heng..Navigation Method Based on Improved Rapid Exploration Random Tree Star-Smart (RRT--Smart) and Deep Reinforcement Learning[J].东华大学学报（英文版）,2022,39(5):490-495,6.基金项目
National Natural Science Foundation of China(No.61903078) （No.61903078）
