Resilient source seeking with robot swarms
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2024
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A. Acuaviva, J. Bautista, W. Yao, J. Jimenez and H. G. de Marina, "Resilient source seeking with robot swarms," 2024 IEEE 63rd Conference on Decision and Control (CDC), Milan, Italy, 2024, pp. 57-63, doi: 10.1109/CDC56724.2024.10886464.
Abstract
We present a solution for locating the source, or maximum, of an unknown scalar field using a swarm of mobile robots. Unlike relying on the traditional gradient information, the swarm determines an ascending direction to approach the source with arbitrary precision. The ascending direction is calculated from field strength measurements at the robot locations and their relative positions concerning the swarm centroid. Rather than focusing on individual robots, we focus the analysis on the density of robots per unit area to guarantee a more resilient swarm, i.e., the functionality remains even if individuals go missing or are misplaced during the mission. We reinforce the algorithm's robustness by providing sufficient conditions for the swarm shape so that the ascending direction is almost parallel to the gradient. The swarm can respond to an unexpected environment by morphing its shape and exploiting the existence of multiple ascending directions. Finally, we validate our approach numerically with hundreds of robots. The fact that a large number of robots with a generic formation always calculate an ascending direction compensates for the potential loss of individuals.
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Publicado en: Proceedings of the IEEE Conference on Decision & Control.
RYC2020-030090-I













