MRNAV: 混雑環境における衝突・デッドロックのないマルチロボットナビゲーションのための計画・制御スタック
MRNAV: Multi-Robot Aware Planning and Control Stack for Collision and Deadlock-free Navigation in Cluttered Environments
静的・動的障害物のある混雑環境で複数のロボットが衝突やデッドロックなく動けるよう、短期・中期・長期の意思決定モジュールを階層的に組み合わせた計画・制御フレームワークを提案し、マルチクアッドロータのシミュレーションで有効性を示した。
著者: Baskın Şenbaşlar, Pilar Luiz, Wolfgang Hönig, Gaurav S. Sukhatme
分類: cs.RO, cs.MA
原文アブストラクト
Multi-robot collision-free and deadlock-free navigation in cluttered environments with static and dynamic obstacles is a fundamental problem for many applications. We introduce MRNAV, a framework for planning and control to effectively navigate in such environments. Our design utilizes short, medium, and long horizon decision making modules with qualitatively different properties, and defines the responsibilities of them. The decision making modules complement each other and provide the effective navigation capability. MRNAV is the first hierarchical approach combining these three levels of decision making modules and explicitly defining their responsibilities. We implement our design for simulated multi-quadrotor flight. In our evaluations, we show that all three modules are required for effective navigation in diverse situations. We show the long-term executability of our approach in an eight hour long wall time (six hour long simulation time) uninterrupted simulation without collisions or deadlocks.
