Landing a UAV in Harsh Winds and Turbulent Open Waters
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Abstract (arXiv)
Landing an unmanned aerial vehicle unmanned aerial vehicle (UAV) on top of an unmanned surface vehicle (USV) in harsh open waters is a challenging problem, owing to forces that can damage the UAV due to a severe roll and/or pitch angle of the USV during touchdown. To tackle this, we propose a novel model predictive control (MPC) approach enabling a UAV to land autonomously on a USV in these harsh conditions. The MPC employs a novel objective function and an online decomposition of the oscillatory motion of the vessel to predict, attempt, and accomplish the landing during near-zero tilt of the landing platform. The nonlinear prediction of the motion of the vessel is performed using visual data from an onboard camera. Therefore, the system does not require any communication with the USV or a control station. The proposed method was analyzed in numerous robotics simulations in harsh and extreme conditions and further validated in various real-world scenarios.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Dec 2022.
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Citing papers per year: 2026: 3.
3 papers.
- 2026WaveLander: A Generalizable Hierarchical Control Framework for UAV Landing on Wave-Disturbed Platforms via Reinforcement Learningcited by 2
- 2026Barrier-Shaped Recurrent Reinforcement Learning for Autonomous Landing on a Heaving Ship Deckcited by 0
- 2026Prediction-Informed Landing Window Planning for UAV Landing on USV in High Sea Statescited by 0
- 2026Prediction-Informed Landing Window Planning for UAV Landing on USV in High Sea States9 Oct 2026
- 2026Barrier-Shaped Recurrent Reinforcement Learning for Autonomous Landing on a Heaving Ship Deck2 Oct 2026
- 2026WaveLander: A Generalizable Hierarchical Control Framework for UAV Landing on Wave-Disturbed Platforms via Reinforcement Learning1 Jul 2026