Study of a Multi-Robot Collaborative Task through Reinforcement Learning

  • Juan Pereda
  • Manuel Martín-Ortiz
  • Javier de Lope
  • Félix de la Paz
Conference paper

DOI: 10.1007/978-3-642-21344-1_20

Volume 6686 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Pereda J., Martín-Ortiz M., de Lope J., de la Paz F. (2011) Study of a Multi-Robot Collaborative Task through Reinforcement Learning. In: Ferrández J.M., Álvarez Sánchez J.R., de la Paz F., Toledo F.J. (eds) Foundations on Natural and Artificial Computation. IWINAC 2011. Lecture Notes in Computer Science, vol 6686. Springer, Berlin, Heidelberg

Abstract

A open issue in multi-robots systems is coordinating the collaboration between several agents to obtain a common goal. The most popular solutions use complex systems, several types of sensors and complicated controls systems. This paper describes a general approach for coordinating the movement of objects by using reinforcement learning. Thus, the method proposes a framework in which two robots are able to work together in order to achieve a common goal. We use simple robots without any kind of internal sensors and they only obtain information from a central camera. The main objective of this paper is to define and to verify a method based on reinforcement learning for multi-robot systems, which learn to coordinate their actions for achieving common goal.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Juan Pereda
    • 1
  • Manuel Martín-Ortiz
    • 1
  • Javier de Lope
    • 2
  • Félix de la Paz
    • 3
  1. 1.ITRB Labs ResearchTechnology Development and Innovation, S.L.
  2. 2.Computational Cognitive RoboticsUniversidad Politécnica de Madrid
  3. 3.Dept. Artificial IntelligenceUNED