Social Odometry in Populations of Autonomous Robots

  • Álvaro Gutiérrez
  • Alexandre Campo
  • Francisco C. Santos
  • Carlo Pinciroli
  • Marco Dorigo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5217)

Abstract

The improvement of odometry systems in collective robotics remains an important challenge for several applications. In this work, we propose a localisation strategy in which robots have no access to centralised information. Each robot has an estimate of its own location and an associated confidence level that decreases with distance travelled. Robots use estimates advertised by neighbouring robots to correct their own location estimates at each time-step. This simple online social form of odometry is shown to allow a group of robots to both increase the quality of individuals’ estimates and efficiently improve their collective performance. Furthermore, social odometry produces a successful self-organised collective pattern.

Keywords

Mobile Robot Central Place Round Trip Autonomous Robot Collective Performance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Álvaro Gutiérrez
    • 1
  • Alexandre Campo
    • 2
  • Francisco C. Santos
    • 2
  • Carlo Pinciroli
    • 2
  • Marco Dorigo
    • 2
  1. 1.ETSITUniversidad Politécnica de MadridMadridSpain
  2. 2.IRIDIA, CoDEUniversité Libre de BruxellesBrusselsBelgium

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