摘要
人员跟随作为人机交互的基础,在移动机器人领域具有很大的意义。该文提出一种基于人工势场的自适应步长随机树(AS-P-RRT*)算法的人员跟随系统,用于实现移动机器人在复杂环境中的自适应人员跟随功能。研究的主要目的是提高传统RRT算法在动态环境中对人员移动的响应速度与路径规划的效率,同时避免碰撞并保证跟随精度。该文通过在传统RRT*算法中引入自适应规划步长以及人工势场引导以改善规划算法的速度与精度,以满足人员跟随任务的需求。该文针对提出的算法进行仿真与实物实验,实验结果表明,AS-P-RRT*算法在规划速度、路径平滑度以及避免障碍物的能力上有显著提升,相比于其他的改进RRT算法能更有效地实现移动机器人对人员的精确跟随。
As the basis of human-computer interaction,human following is of great significance in the field of mobile robots.This paper proposes a person following system based on the Adaptive Step-size Parallel RRT(AS-P-RRT*)algorithm of artificial potential fields to realize the adaptive person following function of mobile robots in complex environments.The main purpose of the research is to improve the response speed and path planning efficiency of traditional RRT algorithms to people's movements in dynamic environments,while avoiding collisions and ensuring following accuracy.In this paper,adaptive planning step size and artificial potential field guidance are introduced into the traditional RRT*algorithm to improve the speed and accuracy of the planning algorithm to meet the needs of people to follow the task.In this paper,simulation and physical experiments are carried out on the proposed algorithm.Experimental results show that the AS-P-RRT*algorithm has significant improvements in planning speed,path smoothness and ability to avoid obstacles.Compared to other improved RRT algorithms,it is more effective to accurately follow people by the mobile robot.
作者
林骏杰
吴炜
LIN Junjie;WU Wei
出处
《科技创新与应用》
2025年第27期1-8,共8页
Technology Innovation and Application
基金
国家自然科学基金项目(61807016)。
关键词
路径规划
移动机器人
人员跟随
人机交互
快速扩展随机树算法
path planning
mobile robot
human following
human-computer interaction
rapidly expanding random tree algorithm
作者简介
第一作者:林骏杰(2000-),男,硕士研究生。研究方向为移动机器人。;通信作者:吴炜(1981-),男,博士,副教授。研究方向为无人驾驶及自主导航。
