Özdemir, A., Gauci, M. and Groß, R. orcid.org/0000-0003-1826-1375 (2018) Shepherding with robots that do not compute. In: ECAL 2017: The Fourteenth European Conference on Artificial Life. European Conference on Artificial Life, ECAL 2017, 04-08 Sep 2017, Lyon, France. MIT Press , Cambridge, MA , pp. 332-339. ISBN 9780262346337
Abstract
We examine the problem solving capabilities of swarms of computation- and memory-free agents. Each agent has a single line-of-sight sensor providing two bits of information. The agent maps this information directly onto constant motor commands. In previous work, we showed that such simplistic agents can solve tasks requiring them to organize spatially (multi-robot aggregation and circle formation) and manipulate passive objects (clustering). In the present work, we address the shepherding problem, where the computation- and memory-free agents—the shepherds—are tasked to gather and move a group of dynamic agents—the sheep—towards a pre-defined goal. The shepherds and sheep are modelled as e-puck robots using computer simulations. Our findings show that the shepherding problem does not fundamentally require arithmetic computation or memory to be solved. The obtained controller solution is robust with respect to sensory noise, and copes well with changes in the number of sheep.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Massachusetts Institute of Technology. Article available under the Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | swarm robotics; minimal information processing; shepherding; line-of-sight sensing |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 Jul 2017 14:49 |
Last Modified: | 23 Jun 2020 12:41 |
Status: | Published |
Publisher: | MIT Press |
Refereed: | Yes |
Identification Number: | 10.7551/ecal_a_056 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:118675 |