モデル予測制御に基づく移動船上へのUAVの俊敏な着陸のための軌道生成
Model predictive control-based trajectory generation for agile landing of unmanned aerial vehicle on a moving boat
荒天下で移動する無人艇のデッキにマルチロータUAVを高精度に着陸させるため、モデル予測制御を用いて艇の状態予測を考慮した軌道を生成する手法を提案し、シミュレーションと実機実験で有効性を示した。
著者: Ondřej Procházka, Filip Novák, Tomáš Báča, Parakh M. Gupta, Robert Pěnička, Martin Saska
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
This paper proposes a novel trajectory generation method based on Model Predictive Control (MPC) for agile landing of an Unmanned Aerial Vehicle (UAV) onto an Unmanned Surface Vehicle (USV)'s deck in harsh conditions. The trajectory generation exploits the state predictions of the USV to create periodically updated trajectories for a multirotor UAV to precisely land on the deck of a moving USV even in cases where the deck's inclination is continuously changing. We use an MPC-based scheme to create trajectories that consider both the UAV dynamics and the predicted states of the USV up to the first derivative of position and orientation. Compared to existing approaches, our method dynamically modifies the penalization matrices to precisely follow the corresponding states with respect to the flight phase. Especially during the landing maneuver, the UAV synchronizes attitude with the USV's, allowing for fast landing on a tilted deck. Simulations show the method's reliability in various sea conditions up to Rough sea (wave height 4 m), outperforming state-of-the-art methods in landing speed and accuracy, with twice the precision on average. Finally, real-world experiments validate the simulation results, demonstrating robust landings on a moving USV, while all computations are performed in real-time onboard the UAV.
