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Memorias de investigación
Artículos en revistas:
A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques
Año:2019
Áreas de investigación
  • Inteligencia artificial (redes neuronales, lógica borrosa, sistemas expertos, etc),
  • Robots aéreos,
  • Robots autónomos,
  • Visión por computador
Datos
Descripción
Search and Rescue (SAR) missions represent an important challenge in the robotics research field as they usually involve exceedingly variable-nature scenarios which require a high-level of autonomy and versatile decision-making capabilities. This challenge becomes even more relevant in the case of aerial robotic platforms owing to their limited payload and computational capabilities. In this paper, we present a fully-autonomous aerial robotic solution, for executing complex SAR missions in unstructured indoor environments. The proposed system is based on the combination of a complete hardware configuration and a flexible system architecture which allows the execution of high-level missions in a fully unsupervised manner (i.e. without human intervention). In order to obtain flexible and versatile behaviors from the proposed aerial robot, several learning-based capabilities have been integrated for target recognition and interaction. The target recognition capability includes a supervised learning classifier based on a computationally-efficient Convolutional Neural Network (CNN) model trained for target/background classification, while the capability to interact with the target for rescue operations introduces a novel Image-Based Visual Servoing (IBVS) algorithm which integrates a recent deep reinforcement learning method named Deep Deterministic Policy Gradients (DDPG). In order to train the aerial robot for performing IBVS tasks, a reinforcement learning framework has been developed, which integrates a deep reinforcement learning agent (e.g. DDPG) with a Gazebo-based simulator for aerial robotics. The proposed system has been validated in a wide range of simulation flights, using Gazebo and PX4 Software-In-The-Loop, and real flights in cluttered indoor environments, demonstrating the versatility of the proposed system in complex SAR missions
Internacional
Si
JCR del ISI
Si
Título de la revista
Journal of Intelligent & Robotic Systems
ISSN
0921-0296
Factor de impacto JCR
2,259
Información de impacto
Datos JCR del año 2019
Volumen
95
DOI
10.1007/s10846-018-0898-1
Número de revista
2
Desde la página
601
Hasta la página
627
Mes
JULIO
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Carlos Sampedro Perez (UPM)
  • Autor: Alejandro Rodriguez Ramos (UPM)
  • Autor: Hriday Bavle Milind (UPM)
  • Autor: Adrián Carrió Fernández (UPM)
  • Autor: Paloma de la Puente Yusty (UPM)
  • Autor: Pascual Campoy Cervera (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
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