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Memorias de investigación
Ponencias en congresos:
Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles
Año:2014
Áreas de investigación
  • Percepción visual,
  • Robots aéreos,
  • Robots autónomos,
  • Robots de inspección,
  • Percepción,
  • Control visual,
  • Inspección visual,
  • Visión en tiempo-real
Datos
Descripción
Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.
Internacional
Si
Nombre congreso
International Conference on Unmanned Aircraft Systems (ICUAS)
Tipo de participación
960
Lugar del congreso
Orlando, FL
Revisores
Si
ISBN o ISSN
978-1-4799-2376-2
DOI
10.1109/ICUAS.2014.6842309
Fecha inicio congreso
27/05/2014
Fecha fin congreso
30/05/2014
Desde la página
649
Hasta la página
655
Título de las actas
Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Changhong Fu (UPM)
  • Autor: Adrián Carrió Fernández (UPM)
  • Autor: Miguel Ángel Olivares Mendez (UPM)
  • Autor: Pascual Campoy Cervera (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
  • Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
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