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dc.contributor.author Botelho, Silvia Silva da Costa
dc.contributor.author Neves, Renato Silva das
dc.contributor.author Taddei, Lorenzo
dc.contributor.author Oliveira, Vinícius Menezes de
dc.date.accessioned 2016-08-30T23:55:42Z
dc.date.available 2016-08-30T23:55:42Z
dc.date.issued 2007
dc.identifier.citation BOTELHO, Silvia Silva da Costa et al. Using augmented state Kalman filter to localize multi autonomous underwater vehicles. J. Braz. Comp. Soc., v. 13, n. 2, 2007. Disponível em: <http://www.scielo.br/scielo.php?pid=S0104-65002007000200006&script=sci_arttext>. Acesso em: 11 mar. 2015. pt_BR
dc.identifier.issn 0104-6500
dc.identifier.uri http://repositorio.furg.br/handle/1/6442
dc.description.abstract The present paper describes a system for the construction of visual maps ("mosaics") and motion estimation for a set of AUVs (Autonomous Underwater Vehicles). Robots are equipped with down-looking camera which is used to estimate their motion with respect to the seafloor and built an online mosaic. As the mosaic increases in size, a systematic bias is introduced in its alignment, resulting in an erroneous output. The theoretical concepts associated with the use of an Augmented State Kalman Filter (ASKF) were applied to optimally estimate both visual map and the fleet position. pt_BR
dc.language.iso eng pt_BR
dc.rights open access pt_BR
dc.subject Multi-robots pt_BR
dc.subject Autonomous underwater vehicles pt_BR
dc.subject mosaics pt_BR
dc.subject Robotic localization pt_BR
dc.title Using augmented state Kalman filter to localize multi autonomous underwater vehicles pt_BR
dc.type article pt_BR
dc.identifier.doi http://dx.doi.org/10.1007/BF03192410 pt_BR


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