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Memorias de investigación
Artículos en revistas:
Vision-Based Multirotor Following Using Synthetic Learning Techniques
Año:2019
Áreas de investigación
  • Automática
Datos
Descripción
Deep- and reinforcement-learning techniques have increasingly required large sets of real data to achieve stable convergence and generalization, in the context of image-recognition, object-detection or motion-control strategies. On this subject, the research community lacks robust approaches to overcome unavailable real-world extensive data by means of realistic synthetic-information and domain-adaptation techniques. In this work, synthetic-learning strategies have been used for the vision-based autonomous following of a noncooperative multirotor. The complete maneuver was learned with synthetic images and high-dimensional low-level continuous robot states, with deep- and reinforcement-learning techniques for object detection and motion control, respectively. A novel motion-control strategy for object following is introduced where the camera gimbal movement is coupled with the multirotor motion during the multirotor following. Results confirm that our present framework can be used to deploy a vision-based task in real flight using synthetic data. It was extensively validated in both simulated and real-flight scenarios, providing proper results (following a multirotor up to 1.3 m/s in simulation and 0.3 m/s in real flights).
Internacional
Si
JCR del ISI
Si
Título de la revista
Sensors, volume 19,
ISSN
1424-8220
Factor de impacto JCR
3,275
Información de impacto
Volumen
19
DOI
10.3390/s19214794
Número de revista
Desde la página
0
Hasta la página
20
Mes
NOVIEMBRE
Ranking
Instruments and Instrumentation 5/64 (Q1) Engineering, Electrical & Electronic 77/266 (Q2) SiteScore (SCOPUS) in 2019: 5.0 Ranking: Instrumentation 17/139 (Q1) Electrical & Electronic Engineering 147/670 (Q2)
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Alejandro Rodriguez Ramos (UPM)
  • Autor: Hriday Bavle Milind (UPM)
  • Autor: Adrian Alvarez
  • Autor: Pascual Campoy Cervera (UPM)
  • Autor: Jonathan P How,
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Visión por Computador y Robótica Aérea
  • Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
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