• DocumentCode
    2226585
  • Title

    Deriving minimal sensory configurations for evolved cooperative robot teams

  • Author

    Watson, James ; Nitschke, Geoff

  • Author_Institution
    Department of Computer Science, University of Cape Town, Cape Town, South Africa
  • fYear
    2015
  • fDate
    25-28 May 2015
  • Firstpage
    3065
  • Lastpage
    3071
  • Abstract
    This paper presents a study on the impact of different robot sensory configurations (morphologies) in simulated robot teams that must accomplish a collective (cooperative) behavior task. The study´s objective was to investigate if effective collective behaviors could be efficiently evolved given minimal morphological complexity of individual robots in an homogenous team. A range of sensory configurations are tested in company with evolved controllers for a collective construction task. Results indicate that a minimal sensory configuration yields the highest task performance, and increasing the complexity of the sensory configuration does not yield an increased task performance.
  • Keywords
    Artificial neural networks; Collision avoidance; Morphology; Robot kinematics; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2015 IEEE Congress on
  • Conference_Location
    Sendai, Japan
  • Type

    conf

  • DOI
    10.1109/CEC.2015.7257271
  • Filename
    7257271