Distributed sequential task allocation in foraging swarms

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

When designing a practical swarm robotics system, self-organized task allocation is key to make best use of resources. Current research in this area focuses on task allocation which is either distributed (tasks must be performed at different locations) or sequential (tasks are complex and must be split into simpler sub-tasks and processed in order). In practice, however, swarms will need to deal with tasks which are both distributed and sequential. In this paper, a classic foraging problem is extended to incorporate both distributed and sequential tasks. The problem is analysed theoretically, absolute limits on performance are derived, and a set of conditions for a successful algorithm are established. It is shown empirically that an algorithm which meets these conditions, by causing emergent cooperation between robots can achieve consistently high performance under a wide range of settings without the need for communication.

Original languageEnglish
Title of host publicationSASO: 2013 IEEE 7th international conference on Self-Adaptive and Self-Organizing Systems
PublisherIEEE
Pages149-158
Number of pages10
ISBN (Print)978-0-7695-5129-6
DOIs
Publication statusPublished - 11 Sep 2013
Event7th International Conference on Self-Adaptive and Self-Organizing Systems - Philadelphia, PA, United States
Duration: 9 Sep 201313 Sep 2013

Publication series

Name
ISSN (Print)1949-3673

Conference

Conference7th International Conference on Self-Adaptive and Self-Organizing Systems
Abbreviated titleSASO 2013
CountryUnited States
CityPhiladelphia, PA
Period9/09/1313/09/13

Bibliographical note

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Keywords

  • self-organizing systems
  • evolutionary computing
  • resource allocation
  • swarm intelligence

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