A method for stereo-vision-based tracking for robotic applications
Date
2010
Authors
Pathirana, Pubudu
Bishop, Adrian
Savkin, Andrey V
Ekanayake , Samitha W.
Black, Timothy J.
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Publisher
Cambridge University Press
Abstract
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).
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Keywords
Keywords: Cartesian coordinate; Converted measurement; Linear filtering; Linear filters; Linear measurement equation; Measurement conversion; Nonlinear measurement; Perspective projections; Practical experimentation; Robotic applications; Robotic manipulators; Robu Linear filtering; Robust filtering; Set-estimation; Stereo vision; Target tracking
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Source
Robotica
Type
Journal article
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Restricted until
2037-12-31
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