Using augmented state Kalman filter to localize multi autonomous underwater vehicles
Data(s) |
30/08/2016
30/08/2016
2007
|
---|---|
Resumo |
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. |
Identificador |
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. 0104-6500 |
Idioma(s) |
eng |
Direitos |
open access |
Palavras-Chave | #Multi-robots #Autonomous underwater vehicles #mosaics #Robotic localization |
Tipo |
article |