Bio-inspired Decentralized Self-coordination Algorithms for Multi-heterogeneous Specialized Tasks Distribution in Multi-Robot Systems

  • Yadira Quiñonez
  • Javier de Lope
  • Darío Maravall
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6686)

Abstract

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots, as opposed to the usual multi-tasks allocation problem in multi-robot systems in which an external controller distributes the existing tasks among the individual robots. We are rather interested on decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we establish an experimental scenario and we propose a bio-inspired solution based on threshold models to solve the corresponding multi-tasks distribution problem. The paper ends with a critical discussion of the experimental results.

Keywords

Multi-robot systems bio-inspired threshold models multi-tasks distribution self-coordination of multiple robots multi-heterogeneous specialized tasks distribution 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yadira Quiñonez
    • 1
  • Javier de Lope
    • 1
  • Darío Maravall
    • 1
  1. 1.Computational Cognitive Robotics, Dept. Artificial IntelligenceUniversidad Politécnica de MadridSpain

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