Published September 2001 | Version Published
Journal Article Open

A macroscopic analytical model of collaboration in distributed robotic systems

  • 1. ROR icon University of Southern California
  • 2. ROR icon California Institute of Technology

Abstract

In this article, we present a macroscopic analytical model of collaboration in a group of reactive robots. The model consists of a series of coupled differential equations that describe the dynamics of group behavior. After presenting the general model, we analyze in detail a case study of collaboration, the stick-pulling experiment, studied experimentally and in simulation by Ijspeert et al. [Autonomous Robots, 11, 149-171]. The robots' task is to pull sticks out of their holes, and it can be successfully achieved only through the collaboration of two robots. There is no explicit communication or coordination between the robots. Unlike microscopic simulations (sensor-based or using a probabilistic numerical model), in which computational time scales with the robot group size, the macroscopic model is computationally efficient, because its solutions are independent of robot group size. Analysis reproduces several qualitative conclusions of Ijspeert et al.: namely, the different dynamical regimes for different values of the ratio of robots to sticks, the existence of optimal control parameters that maximize system performance as a function of group size, and the transition from superlinear to sublinear performance as the number of robots is increased.

Additional Information

© 2002 Massachusetts Institute of Technology. Posted Online March 11, 2006. This research was supported by the National Science Foundation under grant no. 0074790, in part by the Defense Advanced Research Projects Agency (DARPA) under contract number F30602-00-2-0573, and in part by the Center for Neuromorphic Systems Engineering at the California Institute of Technology as part of the National Science Foundation Engineering Research Center Program under grant EEC-9402726. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any of the above organizations or any person connected with them.

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Identifiers

Eprint ID
13704
Resolver ID
CaltechAUTHORS:LERal01

Funding

NSF
0074790
Defense Advanced Research Projects Agency (DARPA)
F30602-00-2-0573
Science Foundation Engineering Research Center Program
EEC-9402726

Dates

Created
2009-07-09
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Updated
2021-11-08
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