Navigation information fusion for an AUV in rivers

Author

Rao, Jinjun ; Chen, Jinbo ; Ding, Wei ; Gong, Zhenbang

Author_Institution

Dept. of Precision Mech. Eng., Shanghai Univ., Shanghai, China

fYear

2012

fDate

13-15 Sept. 2012

Firstpage

83

Lastpage

88

Abstract

Autonomous Underwater Vehicles (AUVs) present an enormous application potential, and the real time accurate position and attitude information is important for AUVs. In order to obtain comprehensive and accurate position and attitude data of AUVs, focusing on the common low cost sensors configuration, the data fusion problem of SINS/USBL/AHRS combination is presented and studied in this paper. Firstly, the error expressions of MEMS are researched and derived, and the data fusion model for Kalman Filter fusion algorithms is presented. The method is validated using a data set gathered for a Huangpu river inspection task. The comparison between original data and fusional data shows that SINS/USBL/AHRS data fusion system can promote accuracy of position and attitude markedly.

Keywords

Kalman filters; autonomous underwater vehicles; marine control; mobile robots; path planning; position control; sensor fusion; telerobotics; AUV; Huangpu river inspection; Kalman Filter fusion algorithms; MEMS; SINS/USBL/AHRS combination; attitude data; attitude information; autonomous underwater vehicles; navigation information fusion; position data; position information; Mathematical model; Micromechanical devices; Navigation; Rivers; Sensors; Silicon compounds; Vehicles; attitude and heading reference systems; autonomous underwater vehicles; information fusion; stapedown inertia navigation system; ultra-short base line;

fLanguage

English

Publisher

ieee

Conference_Titel

Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on

Conference_Location

Hamburg

Print_ISBN

978-1-4673-2510-3

Electronic_ISBN

978-1-4673-2511-0

Type

conf

DOI

10.1109/MFI.2012.6343038

Filename

6343038