RT Conference Proceedings
T1 Resilient source seeking with robot swarms
A1 Acuaviva, Antonio
A1 Jesús Lidón, Juan Bautista
A1 Yao, Weijia
A1 Jiménez Castellanos, Juan Francisco
A1 García De Marina Peinado, Héctor Jesús
AB 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.
SN 979-8-3503-1632-2
SN 0743-1546
YR 2024
FD 2024
LK https://hdl.handle.net/20.500.14352/129827
UL https://hdl.handle.net/20.500.14352/129827
LA eng
NO 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.
NO Publicado en: Proceedings of the IEEE Conference on Decision & Control.RYC2020-030090-I
NO European Commission
NO Ministerio de Ciencia e Innovación (España)
NO Agencia Estatal de Investigación (España)
DS Docta Complutense
RD 25 feb 2026