GARTHIM. Remote Reinforcement Learning for Mobile Robots Connected to Internet

ByJuan Antonio Fernández Madrigal

This project addresses the execution of the cognitive processes of learning and decision making in mobile robots with low on-board computational power, in particular by running the processes in remote stations.

The project officially begins in November the 15th, 2019, and lasts for 2 years.

REFERENCE: UMA18-FEDERJA-113
TITLE: GARTHIM. REMOTE REINFORCEMENT LEARNING FOR MOBILE ROBOTS CONNECTED TO INTERNET
PRINCIPAL RESEARCHER: JUAN-ANTONIO FERNÁNDEZ-MADRIGAL
INSTITUTION: JUNTA DE ANDALUCÍA (Regional Government) / UNIVERSITY OF MÁLAGA
DEPARTMENT: SYSTEM ENGINEERING AND AUTOMATION
DATES: 15/11/19 to 15/11/21 EXTENDED: On March 2, 2021, it was extended till 14/06/22

Team:

  • Dr. Juan-Antonio Fernández-Madrigal (PI)
  • Dr. Alfonso García-Cerezo (researcher)
  • Dr. Ana Cruz-Martín (researcher)
  • Dr. Vicente Arévalo-Espejo (researcher)
  • Dr. Manuel Castellano Quero (collaborator)
  • Mario Rueda Castro (sw/AI engineer)
  • Benjamín Vega Herrera (former sw/AI engineer)

Institutional information (in Spanish): Proyecto de Investigación en el marco del operativo FEDER Andalucía 2014-2020, convocatoria 2018, código UMA18-FEDERJA-113; evaluado con 80 sobre 100; concedido por Resolución definitiva de 10 de octubre de 2019 del Rector de la Universidad de Málaga; con dotación de 63.353,98 € a ejecutar en 2 años.

In this link you can access the RL software framework developed in C++ for ROS during this project.

Publications

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