Study of a multi-robot collaborative task through reinforcement learning

  • Authors:
  • Juan Pereda;Manuel Martín-Ortiz;Javier de Lope;Félix de la Paz

  • Affiliations:
  • ITRB Labs Research, Technology Development and Innovation, S.L;ITRB Labs Research, Technology Development and Innovation, S.L;Computational Cognitive Robotics, Universidad Politécnica de Madrid;Dept. Artificial Intelligence, UNED

  • Venue:
  • IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
  • Year:
  • 2011

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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.