Resilient source seeking with robot swarms

dc.conference.date16-19 Dic 2024
dc.conference.placeMilán, Italia
dc.conference.titleIEEE 63rd Conference on Decision and Control (CDC)
dc.contributor.authorAcuaviva, Antonio
dc.contributor.authorJesús Lidón, Juan Bautista
dc.contributor.authorYao, Weijia
dc.contributor.authorJiménez Castellanos, Juan Francisco
dc.contributor.authorGarcía De Marina Peinado, Héctor Jesús
dc.date.accessioned2026-01-11T21:17:15Z
dc.date.available2026-01-11T21:17:15Z
dc.date.issued2024
dc.descriptionPublicado en: Proceedings of the IEEE Conference on Decision & Control. RYC2020-030090-I
dc.description.abstractWe 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.
dc.description.departmentDepto. de Arquitectura de Computadores y Automática
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipEuropean Commission
dc.description.sponsorshipMinisterio de Ciencia e Innovación (España)
dc.description.sponsorshipAgencia Estatal de Investigación (España)
dc.description.statuspub
dc.identifier.citationA. 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.
dc.identifier.doi10.1109/CDC56724.2024.10886464
dc.identifier.essn2576-2370
dc.identifier.isbn979-8-3503-1632-2
dc.identifier.issn0743-1546
dc.identifier.officialurlhttps://doi.org/10.1109/CDC56724.2024.10886464
dc.identifier.relatedurlhttps://ieeexplore.ieee.org/document/10886464
dc.identifier.relatedurlhttps://dx.doi.org/10.48550/arXiv.2309.02937
dc.identifier.urihttps://hdl.handle.net/20.500.14352/129827
dc.language.isoeng
dc.page.final63
dc.page.initial57
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/HE/101076091
dc.rights.accessRightsopen access
dc.subject.cdu004
dc.subject.keywordSufficient conditions
dc.subject.keywordShape
dc.subject.keywordFocusing
dc.subject.keywordPosition measurement
dc.subject.keywordRobustness
dc.subject.keywordMobile robots
dc.subject.keywordRobots
dc.subject.ucmRobótica
dc.subject.unesco33 Ciencias Tecnológicas
dc.titleResilient source seeking with robot swarms
dc.typeconference paper
dc.type.hasVersionAO
dspace.entity.typePublication
relation.isAuthorOfPublication0a29de71-0dab-4210-a941-b958bf71d9dc
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relation.isAuthorOfPublication.latestForDiscoverybf65781a-9242-4227-b413-adf7c55935e6

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