Tube RRT*: Efficient Homotopic Path Planning for Swarm Robotics Passing-Through Large-Scale Obstacle Environments

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.