Paper Info
Title
Synchronous And Asynchronous Application Of A Filtering Method For Underwater Robot Localization
Abstract
This paper reports a method that fuses multiple sensor measurements for location estimation of an underwater robot. Synchronous and asynchronous (AS) implementation of the method are also proposed. Extended Kalman filter (EKF) is used to fuse four types of measurements: linear velocity by Doppler velocity log (DVL), angular velocity by gyroscope, ranges to acoustic beacons, and depth. The EKF approach is implemented in three ways to deal with asynchrony in measurements in correction step. The three implementation methods are synchronous collective (SC), synchronous individual (SI), and AS application. These methods are verified and compared through simulation and test tank experiments. The test reveals that the application methods need to be selected depending on the measurement properties: dependency between the measurements and degree of asynchrony. The distinctive features proposed in this study are three application methods together with derivation of an EKF approach to sensor fusion for underwater navigation.
Year
DOI
Venue
2016
10.1142/S0219843615500383
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
Keywords
Field
DocType
Synchronous collective, synchronous individual, asynchronous, extended Kalman filter, localization, underwater robot, sensor fusion
Constant linear velocity,Computer vision,Asynchronous communication,Gyroscope,Extended Kalman filter,Angular velocity,Computer science,Simulation,Filter (signal processing),Sensor fusion,Artificial intelligence,Fuse (electrical)
Journal
Volume
Issue
ISSN
13
2
0219-8436
Citations 
PageRank 
References 
0
0.34
10
Authors
3
Name
Order
Citations
PageRank
Nak Yong Ko13712.59
Tae Gyun Kim232.25
h t choi300.34