A method for stereo-vision-based tracking for robotic applications
Data(s) |
01/01/2010
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Resumo |
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).<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
Cambridge University Press |
Relação |
http://dro.deakin.edu.au/eserv/DU:30030389/pathirana-amethodforstereo-2010.pdf http://dx.doi.org/10.1017/S0263574709005827 |
Direitos |
2009, Cambridge University Press |
Palavras-Chave | #linear filtering #set-estimation #stereo vision #robust filtering #target tracking |
Tipo |
Journal Article |