Tube RRT*: 大規模障害物環境を通過する群ロボティクスのための効率的なホモトピーパスプランニング
Tube RRT*: Efficient Homotopic Path Planning for Swarm Robotics Passing-Through Large-Scale Obstacle Environments
群ロボティクスの大規模障害物環境でのナビゲーションに向け、RRTを改良しギャップ体積と経路長を考慮してホモトピーパスを生成するTube RRT*を提案し、シミュレーションと実験で有効性を検証した。
著者: Pengda Mao, Shuli Lv, Quan Quan
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
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 ranging of applications. However, it lacks an efficient homotopic path planning method in large-scale obstacle environments. This paper introduces Tube RRT*, an innovative homotopic path planning method that builds upon and improves the Rapidly-exploring Random Tree (RRT) algorithm. Tube RRT* is specifically designed to generate homotopic paths, strategically considering gap volume and path length to mitigate swarm congestion and ensure agile navigation. Through comprehensive simulations and experiments, the effectiveness of Tube RRT* is validated.
