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Self-organized aggregation without computation

Gauci, M., Chen, J., Li, W., DODD, Tony and Gross, R. (2014) Self-organized aggregation without computation. International Journal of Robotics Research, 33 (8). pp. 1145-1161. ISSN 0278-3649

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Abstract or description

This paper presents a solution to the problem of self-organized aggregation of embodied robots that requires no arithmetic computation. The robots have no memory and are equipped with one binary sensor, which informs them whether or not there is another robot in their line of sight. It is proven that the sensor needs to have a sufficiently long range; otherwise aggregation cannot be guaranteed, irrespective of the controller used. The optimal controller is found by performing a grid search over the space of all possible controllers. With this controller, robots rotate on the spot when they perceive another robot, and move backwards along a circular trajectory otherwise. This controller is proven to always aggregate two simultaneously moving robots in finite time, an upper bound for which is provided. Simulations show that the controller also aggregates at least 1000 robots into a single cluster consistently. Moreover, in 30 experiments with 40 physical e-puck robots, 98.6% of the robots aggregated into one cluster. The results obtained have profound implications for the implementation of multi-robot systems at scales where conventional approaches to sensing and information processing are no longer applicable.

Item Type: Article
Additional Information: Melvin Gauci, Jianing Chen, Wei Li, Tony J. Dodd, and Roderich Groß, Self-organized aggregation without computation, The International Journal of Robotics ResearchVol 33, Issue 8, pp. 1145 - 1161. Copyright © 2014 SAGE Publications. Reprinted by permission of SAGE Publications.
Uncontrolled Keywords: Aggregation; line-of-sight sensor; minimal information processing; mobile and distributed robotics; swarm intelligence
Faculty: School of Creative Arts and Engineering > Engineering
Depositing User: Library STORE team
Date Deposited: 15 Jul 2020 15:11
Last Modified: 15 Dec 2020 16:47
Related URLs:
URI: http://eprints.staffs.ac.uk/id/eprint/6245

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