Memorias de investigación
Communications at congresses:
Decentralized multi-agent deep reinforcement learning in swarms of drones for flood monitoring
Year:2019

Research Areas
  • Sensor networks

Information
Abstract
Multi-Agent Deep Reinforcement Learning is becoming a promising approach to the problem of coordination of swarms of drones in dynamic systems. In particular, the use of autonomous aircraft for flood monitoring is now regarded as an economically viable option and it can benefit from this kind of automation: swarms of unmanned aerial vehicles could autonomously generate nearly real-time inundation maps that could improve relief work planning. In this work, we study the use of Deep Q-Networks (DQN) as the optimization strategy for the trajectory planning that is required for monitoring floods, we train agents over simulated floods in procedurally generated terrain and demonstrate good performance with two different reward schemes.
International
Si
Congress
2019 27th European Signal Processing Conference (EUSIPCO)
970
Place
A Coruña
Reviewers
Si
ISBN/ISSN
978-9-0827-9703-9
10.23919/EUSIPCO.2019.8903067
Start Date
02/09/2019
End Date
06/09/2019
From page
1
To page
5
2019 27th European Signal Processing Conference (EUSIPCO)
Participants

Research Group, Departaments and Institutes related
  • Creador: Centro o Instituto I+D+i: Centro de I+d+i en Procesado de la Información y Telecomunicaciones
  • Grupo de Investigación: Grupo de Aplicaciones del Procesado de Señal (GAPS)
  • Departamento: Señales, Sistemas y Radiocomunicaciones