A data fusion method applied in an autonomous robot

Author

Qingmei, Yang ; Jianmin, Sun

Author_Institution

Coll. of Autom., Beijing Union Univ., Beijing

fYear

2008

fDate

16-18 July 2008

Firstpage

361

Lastpage

364

Abstract

In order to improve the accuracy and reliability of the measurement system, data fusion is frequently used in an autonomous robot to fuse multi-sensor information of measurement system. Several kinds of methods of multi-sensor data fusion are analyzed. Kalman filter is applied in an underwater autonomous robot to fuse redundant information. The autonomous robot is designed to dig hole in the mud underwater in sunken wreck salvage along the planed trajectory. Location system of move-in-mud robot is designed in the paper and location principle of move-in-mud robot is analyzed. The fusion method in location system of move-in-mud robot is simulated with Matlab software. The simulation results of the data fusion method show that Kalman filter can improve location accuracy efficiently.

Keywords

Kalman filters; mobile robots; remotely operated vehicles; sensor fusion; underwater vehicles; Kalman filter; data fusion; move-in-mud robot; multisensor information; underwater autonomous robot; Bayesian methods; Coordinate measuring machines; Fuses; Kalman filters; Mechanical variables measurement; Robotics and automation; Robots; Sensor fusion; Sensor systems; Sun; Data Fusion; Kalman Filter; Measurement System; Mobile Robot;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2008. CCC 2008. 27th Chinese

Conference_Location

Kunming

Print_ISBN

978-7-900719-70-6

Electronic_ISBN

978-7-900719-70-6

Type

conf

DOI

10.1109/CHICC.2008.4605358

Filename

4605358