線形二次最小時間制御を用いた探索ベースのクアッドロータ運動計画
Search-based Motion Planning for Quadrotors using Linear Quadratic Minimum Time Control
LQMT最適制御の解を利用した短時間運動プリミティブで状態空間を格子化し、障害物環境での滑らかな最小時間軌道をグラフ探索でオンライン再計画する手法を提案した。
著者: Sikang Liu, Nikolay Atanasov, Kartik Mohta, Vijay Kumar
分類: cs.RO
原文アブストラクト
In this work, we propose a search-based planning method to compute dynamically feasible trajectories for a quadrotor flying in an obstacle-cluttered environment. Our approach searches for smooth, minimum-time trajectories by exploring the map using a set of short-duration motion primitives. The primitives are generated by solving an optimal control problem and induce a finite lattice discretization on the state space which can be explored using a graph-search algorithm. The proposed approach is able to generate resolution-complete (i.e., optimal in the discretized space), safe, dynamically feasibility trajectories efficiently by exploiting the explicit solution of a Linear Quadratic Minimum Time problem. It does not assume a hovering initial condition and, hence, is suitable for fast online re-planning while the robot is moving. Quadrotor navigation with online re-planning is demonstrated using the proposed approach in simulation and physical experiments and comparisons with trajectory generation based on state-of-art quadratic programming are presented.
