Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911643290566656 |
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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 |