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) tha

Highlights

  • Technological advances in embedded systems, such as component miniaturization and improved efficiency of sensors and actuators, are enabling the deployment of very largescale robot systems, i.e., swarms of robots

  • Berman et al [2] present an expose of optimization methods that can be used to obtain optimal transition rates for a homogenous robot swarm that is required to converge to a desired distribution

  • We present a method that distributes a swarm of heterogeneous robots among a set of tasks with the goal of satisfying a desired distribution of robot capabilities among those tasks

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Summary

Introduction

Technological advances in embedded systems, such as component miniaturization and improved efficiency of sensors and actuators, are enabling the deployment of very largescale robot systems, i.e., swarms of robots. Our objective is to distribute a swarm of heterogeneous robots as quickly and efficiently as possible among a set of tasks that require specialized competences. This objective is part of a larger vision to develop control and coordination strategies for teams of heterogeneous robots with specific capabilities. We could consider the limited payload of aerial robots: If a given task requires rich sensory feedback, multiple heterogeneous aerial robots can complement each other by carrying distinct sensors, altogether more than a single one could carry on its own. Instances of information gathering lend themselves naturally to this problem formulation, with applications to surveillance, environmental monitoring, and situational awareness [3, 7, 20]

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