Conferência

Ship, Guide My Landing! A Binocular Extended Kalman Filter for Maritime UAV Landing Operations

OCEANS 2024 - Halifax

Bruno Damas; Nuno Pessanha Santos; Matilde Correia Vieira2024IEEE

Informações chave

Autores:

Bruno Damas (Bruno Duarte Damas); Nuno Pessanha Santos (Nuno Alexandre Antunes Martins Pessanha Santos); Matilde Correia Vieira

Publicado em

25/11/2024

Resumo

Unmanned Aerial Vehicles (UAVs) are continuously being explored as important means of decreasing human intervention and improving system reliability. The more challenging tasks when operating with UAVs are take-off and landing. Most low-size UAVs can have their take-off performed by hand, but the capacity to perform autonomous landing is essential. The autonomous landing environment is usually challenging since we are considering a moving platform, and the system must be able to deal with Global Position System (GPS)-denied environments. The proposed system is based on a ground-based stereoscopic vision system with temporal filtering based on an Extended Kalman Filter (EKF) to track the position of a rotary-wing UAV during landing. The obtained position detects and guides the rotary-wing UAV during landing. The initial results indicate that this setup has the potential to track with low error, demonstrating its suitability for exploration and further improvements.

Detalhes da publicação

Versão da publicação

VoR - Versão publicada

Editora

IEEE

Ligação para a versão da editora

https://ieeexplore.ieee.org/document/10753980

Título do contentor da publicação

OCEANS 2024 - Halifax

Domínio Científico (FOS)

electrical-engineering-electronic-engineering-information-engineering - Engenharia Eletrotécnica, Eletrónica e Informática

Palavras-chave

  • Unmanned Aerial Vehicles
  • Computer Vision
  • Motion Estimation
  • Kalman Filters
  • Landing Maneuver
  • Maritime Robotics
  • Three-dimensional displays
  • Stereo image processing

Idioma da publicação (código ISO)

eng - Inglês

Acesso à publicação:

Acesso Aberto