Dosieah, G.Y., Özdemir, A., Gauci, M. et al. (1 more author) (2022) Moving mixtures of active and passive elements with robots that do not compute. In: Dorigo, M., Hamann, H., López-Ibáñez, M., García-Nieto, J., Engelbrecht, A., Pinciroli, C., Strobel, V. and Camacho-Villalón, C., (eds.) Swarm Intelligence: 13th International Conference, ANTS 2022, Málaga, Spain, November 2–4, 2022, Proceedings. 13th International Conference on Swarm Intelligence, ANTS 2022, 02-04 Nov 2022, Malaga, Spain. Lecture Notes in Computer Science . Springer Nature , pp. 183-195. ISBN 9783031201752
Abstract
This paper investigates the problem of moving a mixture of active and passive elements to a desired location using a swarm of wheeled robots that require only two bits of sensory input. It examines memory-less control strategies that map a robot’s sensory input to the respective wheel velocities. Results from embodied simulations show that the problem can be solved without robots having (i) to discriminate between active and passive elements or (ii) sense other robots. Strategies optimized for moving passive elements, or mixtures of active and passive elements, performed robustly when changing the mixture of elements, or scaling up the number of robots (up to 25) or elements (up to 100). All strategies demonstrated to be fairly robust to noise and adaptable to active elements of different dynamics. Given the simplicity of the robot capabilities and strategies, our findings could be relevant in scenarios where microscopic swarm robots need to manipulate mixtures of elements of unknown dynamics, with potential applications in nanomedicine.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2022 Springer Nature Switzerland AG. This is an author-produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 13 Jul 2022 10:03 |
Last Modified: | 29 Oct 2023 00:13 |
Status: | Published |
Publisher: | Springer Nature |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-031-20176-9_15 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188810 |