Prediction-Informed Landing Window Planning for UAV Landing on USV in High Sea States

Key points

• Existing hierarchical landing methods often infer future USV motion only implicitly from short observation histories, which limits their ability to adapt to severe and rapidly changing sea conditions.1
• This paper presents a prediction-informed hierarchical control framework.1
• A pretrained model is developed to explicitly predict the USV attitude during high-level landing decisions.1
• The experiments demonstrate the feasibility of using explicit attitude prediction to improve landing-window selection and support timing-aware UAV landing planning in rapidly varying marine environments.1

Sources (1)

• [1]Prediction-Informed Landing Window Planning for UAV Landing on USV in High Sea States
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 9, 08:12 AM

  Autonomous landing of unmanned aerial vehicle (UAV) on unmanned surface vehicle (USV) is difficult in high sea states.

  Existing hierarchical landing methods often infer future USV motion only implicitly from short observation histories, which limits their ability to adapt to severe and rapidly changing sea conditions.

Extractive summary: sentences quoted from the sources.