カルマンフィルタによるモーメント損失補償を備えたUAVの画像ベース視覚サーボのための終端拘束モデル予測制御
Terminal Constraint Model Predictive Control for Image-Based Visual Servoing of UAVs with Kalman Filter-Based Moment Loss Compensation
UAVの画像ベース視覚サーボにおいて、終端拘束を導入したモデル予測制御とカルマンフィルタによる視覚特徴の予測を組み合わせ、入力・状態制約下での安定性と視覚情報欠落時の制御継続性を実現した。
著者: X. Wang, Y. Cao, W. L. W. Leong, Y. R. Tan, S. Huang, S. H. R. Teo, C. Xiang
分類: cs.RO
原文アブストラクト
Image-Based Visual Servoing (IBVS) provides an efficient vision-guided control paradigm for unmanned aerial vehicles (UAVs) by directly regulating image-space errors. However, conventional IBVS controllers are vulnerable to two critical issues: loss of closed-loop stability near the target due to input and state constraints, and control failure caused by intermittent loss of moment-based visual features under aggressive motion. To address these challenges, this paper proposes a terminal-constraint model predictive control (TC-MPC) framework for IBVS, integrated with a Kalman filter (KF)-based state-prediction mechanism. The TC-MPC explicitly incorporates terminal-state constraints and a terminal cost into the IBVS error dynamics, ensuring recursive feasibility, improved convergence behavior, and closed-loop stability under control and state constraints. In parallel, the Kalman filter predicts the temporal evolution of image moments during short-term visual degradation, enabling the controller to preserve control continuity when moment measurements are partially unavailable. The proposed approach is validated through real-time UAV visual servoing experiments.