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A method for stereo-vision-based tracking for robotic applications

Pathirana, Pubudu N., Bishop, Adrian N., Savkin, Andrey V., Ekanayake, Samitha W. and Black,Timothy J. 2010, A method for stereo-vision-based tracking for robotic applications, Robotica, vol. 28, no. 4, pp. 517-524.

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Title A method for stereo-vision-based tracking for robotic applications
Author(s) Pathirana, Pubudu N.
Bishop, Adrian N.
Savkin, Andrey V.
Ekanayake, Samitha W.
Black,Timothy J.
Journal name Robotica
Volume number 28
Issue number 4
Start page 517
End page 524
Total pages 8
Publisher Cambridge University Press
Place of publication Cambridge, England
Publication date 2010
ISSN 0263-5747
1469-8668
Keyword(s) linear filtering
set-estimation
stereo vision
robust filtering
target tracking
Summary Vision-based tracking of an object using perspective projection inherently results in non-linear measurement equations in the Cartesian coordinates. The underlying object kinematics can be modelled by a linear system. In this paper we introduce a measurement conversion technique that analytically transforms the non-linear measurement equations obtained from a stereo-vision system into a system of linear measurement equations.We then design a robust linear filter around the converted measurement system. The state estimation error of the proposed filter is bounded and we provide a rigorous theoretical analysis of this result. The performance of the robust filter developed in this paper is demonstrated via computer simulation and via practical experimentation using a robotic manipulator as a target. The proposed filter is shown to outperform the extended Kalman filter (EKF).
Notes First published online: June 9, 2009
Language eng
Field of Research 090602 Control Systems, Robotics and Automation
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2010
Copyright notice ©2009, Cambridge University Press
Persistent URL http://hdl.handle.net/10536/DRO/DU:30030389

Document type: Journal Article
Collections: School of Engineering and Information Technology
School of Engineering
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