アグレッシブなクアッドロータ飛行のためのグラフ探索と軌道最適化の交互実行
Interleaving Graph Search and Trajectory Optimization for Aggressive Quadrotor Flight
軌道最適化と離散グラフ探索を交互に組み合わせ、狭い隙間など厳しい姿勢制約下でも動的限界を活かしたクアッドロータのアグレッシブ飛行軌道を生成する手法を提案した。
著者: Ramkumar Natarajan, Howie Choset, Maxim Likhachev
分類: cs.RO
原文アブストラクト
Quadrotors can achieve aggressive flight by tracking complex maneuvers and rapidly changing directions. Planning for aggressive flight with trajectory optimization could be incredibly fast, even in higher dimensions, and can account for dynamics of the quadrotor, however, only provides a locally optimal solution. On the other hand, planning with discrete graph search can handle non-convex spaces to guarantee optimality but suffers from exponential complexity with the dimension of search. We introduce a framework for aggressive quadrotor trajectory generation with global reasoning capabilities that combines the best of trajectory optimization and discrete graph search. Specifically, we develop a novel algorithmic framework that interleaves these two methods to complement each other and generate trajectories with provable guarantees on completeness up to discretization. We demonstrate and quantitatively analyze the performance of our algorithm in challenging simulation environments with narrow gaps that create severe attitude constraints and push the dynamic capabilities of the quadrotor. Experiments show the benefits of the proposed algorithmic framework over standalone trajectory optimization and graph search-based planning techniques for aggressive quadrotor flight.
