Memorias de investigación
Research Publications in journals:
A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques
Year:2019

Research Areas
  • Artificial intelligence (neuronal nets, expert systems, etc),
  • Aerial robots,
  • Autonomic robots,
  • Computer vision

Information
Abstract
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
International
Si
JCR
Si
Title
Journal of Intelligent & Robotic Systems
ISBN
0921-0296
Impact factor JCR
2,02
Impact info
Datos JCR del año 2018
Volume
95
10.1007/s10846-018-0898-1
Journal number
2
From page
601
To page
627
Month
SIN MES
Ranking
Participants

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Control Inteligente
  • 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