Fixed-Time Dynamic Landing of Quadrotors using Adaptive Unscented Kalman Filtering and Nonlinear Model Predictive Control

2026-06-01

AI Summary

This work addresses the challenge of achieving timed, robust dynamic landing of multirotor unmanned aerial vehicles on moving platforms, particularly under time-varying perception quality that compromises landing accuracy and consistency. To this end, the authors propose a fixed-time touchdown cooperative control framework that integrates an adaptive unscented Kalman filter (UKF) to online estimate and update noise statistics, thereby enhancing state estimation robustness. The approach further combines nonlinear model predictive control (NMPC) with a real-time minimum-jerk trajectory planner to guarantee precise touchdown at a predetermined time during the terminal phase, while generating bounded thrust and torque commands under standard tracking assumptions. Simulation and hardware-in-the-loop experiments demonstrate that the proposed method significantly outperforms conventional EKF/UKF-based approaches, achieving superior performance in platform velocity prediction and landing repeatability.

Abstract

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.

Problem

• dynamic landing
• moving platform
• fixed-time touchdown
• quadrotor
• time-varying sensing

Innovation

• adaptive unscented Kalman filter
• nonlinear model predictive control
• minimum-jerk trajectory
• fixed-time landing
• dynamic landing