Intrinsic and environmental factors modulating autonomous robotic search under high uncertainty
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
Springer NatureFecha de edición
2021-12-31Cita
10.1038/s41598-021-03826-3
Scientific Reports 11.1 (2021): 24509
ISSN
2045-2322 (online)DOI
10.1038/s41598-021-03826-3Financiado por
This work was supported in part by Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER), under Grants PGC2018-095895-B-I00, TIN2017-84452-R, and PID2020-114867RB-I00Proyecto
Gobierno de España. PGC2018-095895-B-I00; Gobierno de España. TIN2017-84452-R; Gobierno de España. PID2020-114867RB-I00Versión del editor
https://doi.org/10.1038/s41598-021-03826-3Materias
InformáticaNota
The version of record of this article, first published in Scientific Reports, is available online at Publisher’s website: http://dx.doi.org/10.1038/s41598-021-03826-3Derechos
© The author(s)Resumen
Autonomous robotic search problems deal with different levels of uncertainty. When uncertainty is low, deterministic strategies employing available knowledge result in most effective searches. However, there are domains where uncertainty is always high since information about robot location, environment boundaries or precise reference points is unattainable, e.g., in cave, deep ocean, planetary exploration, or upon sensor or communications impairment. Furthermore, latency regarding when search targets move, appear or disappear add to uncertainty sources. Here we study intrinsic and environmental factors that affect low-informed robotic search based on diffusive Brownian, naive ballistic, and superdiffusive strategies (Lévy walks), and in particular, the effectiveness of their random exploration. Representative strategies were evaluated considering both intrinsic (motion drift, energy or memory limitations) and extrinsic factors (obstacles and search boundaries). Our results point towards minimum-knowledge based modulation approaches that can adjust distinct spatial and temporal aspects of random exploration to lead to effective autonomous search under uncertainty
Lista de ficheros
Google Scholar:Garcia-Saura, Carlos
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Serrano Jerez, Eduardo
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Rodríguez Ortiz, Francisco Borja
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Varona Martínez, Pablo
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