適応アンセンテッドカルマンフィルタと非線形モデル予測制御を用いたクアッドローターの固定時間動的着陸
Fixed-Time Dynamic Landing of Quadrotors using Adaptive Unscented Kalman Filtering and Nonlinear Model Predictive Control
移動プラットフォームへのドローン動的着陸を、非線形モデル予測制御と最小ジャーク軌道計画、適応UKFを統合して実現し、着陸時刻を固定しつつロバスト性を向上させた。
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著者: Mohammadreza Izadi, Zeinab Shayan, Steven Waslander, Reza Faieghi
分類: cs.RO
原文アブストラクト
This paper introduces an estimation and control framework for dynamic landing of multi-rotor uncrewed aerial vehicles on moving platforms. The proposed method integrates nonlinear model predictive control with a real-time minimum-jerk trajectory planner that enforces a prescribed touchdown time, enabling consistent timing during the terminal descent. To enhance robustness in the presence of time-varying sensing quality, we utilize an adaptive unscented kalman filter that updates the process and measurement noise statistics online. In addition, we provide a reference feasibility analysis showing that minimum-jerk references induce bounded thrust and torque commands under standard tracking hypotheses. The proposed framework is evaluated in simulation and hardware experiments, and it is shown to achieve repeatable landings and improved platform velocity prediction accuracy relative to EKF/UKF-based methods.
