Adaptive Inter-Robot Trust for Robust Multi-Robot Sensor Coverage

Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 114)


This paper proposes a new approach to both characterize inter-robot trust in multi-robot systems and adapt trust online in response to the relative performance of the robots. The approach is applied to a multi-robot coverage control scenario, in which a team of robots must spread out over an environment to provide sensing coverage. A decentralized algorithm is designed to control the positions of the robots, while simultaneously adapting their trust weightings. Robots with higher quality sensors take charge of a larger region in the environment, while robots with lower quality sensors have their regions reduced. Using a Lyapunov-type proof, it is proven that the robots converge to locally optimal positions for sensing that are as good as if the robots’ sensor qualities were known beforehand. The algorithm is demonstrated in Matlab simulations.


Cost Function Voronoi Cell Adaptive Weighting Trust Weighting Coverage Control 
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.



This work was supported in part by ONR grant N00014-12-1-1000, and by a Clare Boothe Luce Fellowship. We are grateful for this financial support.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Boston UniversityBostonUSA
  2. 2.Stanford UniversityStanfordUSA

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