Architecture, Abstractions, and Algorithms for Controlling Large Teams of Robots: Experimental Testbed and Results

  • Nathan Michael
  • Jonathan Fink
  • Savvas Loizou
  • Vijay Kumar
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 66)


We describe the architecture, algorithms, and experimental testbed for the deployment of large numbers of cooperating robots, and applications to tasks like manipulation and transportation. The coordination between robots is completely decentralized to enable scaling up to large numbers of robots. There is no labeling or identification of robots and all robots (and their software) are identical allowing robustness to failures, ease of programming, and modularity enabling the addition or deletion of robots from the team. Our approach requires minimal communication and sensing and the proposed controllers are based only on local information. Moreover, our architecture facilitates asymmetric communication from one or more supervisory agents that can broadcast information to all robots and close the loop by acquiring abstract, high level information related to the supervised robots. We discuss the hardware and software implementation, the architecture, and present recent experimental results.


Abstract Space Large Team Navigation Function Robot Team Ellipsoidal Approximation 
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 2010

Authors and Affiliations

  • Nathan Michael
    • 1
  • Jonathan Fink
    • 1
  • Savvas Loizou
    • 1
  • Vijay Kumar
    • 1
  1. 1.University of PennsylvaniaPhiladelphia

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