• DocumentCode
    248987
  • Title

    Trust modeling in multi-robot patrolling

  • Author

    Pippin, Charles ; Christensen, Helen

  • Author_Institution
    Georgia Inst. of Technol., Georgia Tech Res. Inst., Atlanta, GA, USA
  • fYear
    2014
  • fDate
    May 31 2014-June 7 2014
  • Firstpage
    59
  • Lastpage
    66
  • Abstract
    On typical multi-robot teams, there is an implicit assumption that robots can be trusted to effectively perform assigned tasks. The multi-robot patrolling task is an example of a domain that is particularly sensitive to reliability and performance of robots. Yet reliable performance of team members may not always be a valid assumption even within homogeneous teams. For instance, a robot´s performance may deteriorate over time or a robot may not estimate tasks correctly. Robots that can identify poorly performing team members as performance deteriorates, can dynamically adjust the task assignment strategy. This paper investigates the use of an observation based trust model for detecting unreliable robot team members. Robots can reason over this model to perform dynamic task reassignment to trusted team members. Experiments were performed in simulation and using a team of indoor robots in a patrolling task to demonstrate both centralized and decentralized approaches to task reassignment. The results clearly demonstrate that the use of a trust model can improve performance in the multi-robot patrolling task.
  • Keywords
    centralised control; decentralised control; multi-robot systems; centralized approaches; decentralized approaches; dynamic task reassignment; homogeneous teams; indoor robots; multirobot patrolling task; multirobot teams; observation based trust model; patrolling task; poorly performing team members; unreliable robot team members; Measurement; Monitoring; Navigation; Reliability; Robot kinematics; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2014 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Type

    conf

  • DOI
    10.1109/ICRA.2014.6906590
  • Filename
    6906590