Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms

Fuente: arXiv
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Autores principales: Antal, Péter, Carron, Andrea, Zeilinger, Melanie, Tóth, Roland, Péni, Tamás
Formato: Preprint
Publicado: 2026
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author Antal, Péter
Carron, Andrea
Zeilinger, Melanie
Tóth, Roland
Péni, Tamás
author_facet Antal, Péter
Carron, Andrea
Zeilinger, Melanie
Tóth, Roland
Péni, Tamás
contents This paper presents a novel model predictive control (MPC) approach for autonomous pick-and-place between moving platforms with a hook-equipped aerial manipulator. First, for accurate and rapid modeling of the complex dynamics, a digital twin model of the quadcopter equipped with a hook-based gripper, implemented in MuJoCo, is constructed and used as the predictive model for the MPC. To handle uncertainties of the predictive model (e.g. due to aerodynamics and uncertain payloads), a robust adaptive MPC approach is proposed. By systematic integration of zero-order robust optimization (zoRO) based uncertainty propagation and an extended Kalman filter (EKF) for parameter estimation, the MPC algorithm ensures robust constraint satisfaction, high performance, and computational efficiency. The effectiveness of the proposed method is evaluated in complex simulated scenarios and in real-world flight experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2605_02370
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms
Antal, Péter
Carron, Andrea
Zeilinger, Melanie
Tóth, Roland
Péni, Tamás
Robotics
Systems and Control
This paper presents a novel model predictive control (MPC) approach for autonomous pick-and-place between moving platforms with a hook-equipped aerial manipulator. First, for accurate and rapid modeling of the complex dynamics, a digital twin model of the quadcopter equipped with a hook-based gripper, implemented in MuJoCo, is constructed and used as the predictive model for the MPC. To handle uncertainties of the predictive model (e.g. due to aerodynamics and uncertain payloads), a robust adaptive MPC approach is proposed. By systematic integration of zero-order robust optimization (zoRO) based uncertainty propagation and an extended Kalman filter (EKF) for parameter estimation, the MPC algorithm ensures robust constraint satisfaction, high performance, and computational efficiency. The effectiveness of the proposed method is evaluated in complex simulated scenarios and in real-world flight experiments.
title Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms
topic Robotics
Systems and Control
url https://arxiv.org/abs/2605.02370