ADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS

Amanda Prorok, M. Ani Hsieh, Vijay Kumar

Abstract


We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.

Keywords


heterogeneous multi-robot systems; swarm robotics; stochastic systems; task allocation

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This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN 1210-2709 (Print)
ISSN 1805-2363 (Online)
Published by the Czech Technical University in Prague