障碍物
机器人学
群机器人
比例(比率)
人工智能
运动规划
群体行为
路径(计算)
避障
管(容器)
计算机科学
机器人
工程类
机械工程
地理
移动机器人
地图学
操作系统
考古
作者
Pengda Mao,Shuli Lv,Quan Quan
标识
DOI:10.1109/lra.2025.3531151
摘要
Recently, the concept of homotopic trajectory planning has emerged as a novel solution to navigation in large-scale obstacle environments for swarm robotics, offering a wide range of applications. However, it lacks an efficient homotopic path planning method in large-scale obstacle environments. This letter introduces Tube RRT*, an innovative homotopic path planning method that builds upon and improves the Rapidly-exploring Random Tree (RRT) algorithm. Tube RRT* is designed to efficiently generate homotopic paths belonging to the same homotopy class and simultaneously considers gap volume and path length to mitigate swarm congestion and enable agile navigation. Through comprehensive simulations and experiments, the effectiveness of Tube RRT* is validated.
科研通智能强力驱动
Strongly Powered by AbleSci AI