DSpace
 

Researchspace >
General science, engineering & technology >
General science, engineering & technology >
General science, engineering & technology >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/2774

Title: Modeling the kinematics of an autonomous underwater vehicle for range-bearing Simultaneous Localization and Mapping
Authors: Matsebe, O
Holtzhausen, S
Kumile, CM
Tlale, NS
Keywords: Automatic guided vehicle (AGV)
Simultaneous localization and mapping (SLAM)
Kalman Filter
Issue Date: Dec-2008
Citation: Matsebe, O, Holtshausen, S, Kumile, CM et al. 2008. Modeling the kinematics of an autonomous underwater vehicle for range-bearing Simultaneous Localization and Mapping. 15th International Conference on Mechatronics and Machine Vision in Practice. Auckland, New Zealand, 2-4 December 2008. pp 6
Abstract: The “solution” of the Simultaneous Localisation and Mapping (SLAM) problem has been one of the notable successes of the robotics community. SLAM has been formulated and solved as a theoretical problem in a number of different forms. SLAM has also been implemented in a number of different domains from indoor robots to outdoor, underwater, and airborne systems. At a theoretical and conceptual level, SLAM can now be considered a solved problem. However, substantial issues remain in practically realizing more general SLAM solutions and notably in building and using perceptually rich maps as part of a SLAM algorithm. This paper describes the Autonomous Underwater Vehicle (AUV) kinematic and sensor models, it overviews the basic theoretical solution to the Extended Kalman Filter (EKF) SLAM problem, it also describes the way-point guidance based on Line of Sight (LOS). In this paper, it has been shown through Matlab simulation that the vehicle is able to localize its position using features that it observes in the environment and at the same time map those features. The vehicle is expected to follow a pre-defined sinusoidal path.
Description: 15th International Conference on Mechatronics and Machine Vision in Practice. Auckland, New Zealand, 2-4 December 2008.
URI: http://hdl.handle.net/10204/2774
ISBN: 9780473135324
Appears in Collections:Manufacturing science and technology
General science, engineering & technology

Files in This Item:

File Description SizeFormat
Matsebe_2008.pdf71.94 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback