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A method for stereo-vision based tracking for robotic applications
Version 2 2024-06-03, 12:03Version 2 2024-06-03, 12:03
Version 1 2023-01-27, 04:12Version 1 2023-01-27, 04:12
conference contribution
posted on 2023-01-27, 04:12 authored by Pubudu PathiranaPubudu Pathirana, A N Bishop, A V Savkin, S W Ekanayake, T J BlackVision based tracking of an object using the ideas of perspective projection inherently consists of nonlinearly modelled measurements although the underlying dynamic system that encompasses the object and the vision sensors can be linear. Based on a necessary stereo vision setting, we introduce an appropriate measurement conversion techniques which subsequently facilitate using a linear filter. Linear filter together with the aforementioned measurement conversion approach conforms a robust linear filter that is based on the set values state estimation ideas; a particularly rich area in the robust control literature. We provide a rigorously theoretical analysis to ensure bounded state estimation errors formulated in terms of an ellipsoidal set in which the actual state is guaranteed to be included to an arbitrary high probability. Using computer simulations as well as a practical implementation consisting of a robotic manipulator, we demonstrate our linear robust filter significantly outperforms the traditionally used extended Kalman filter under this stereo vision scenario. © 2008 IEEE.
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1298 - 1303Publisher DOI
ISSN
0743-1546eISSN
2576-2370ISBN-13
9781424431243Publication classification
E1.1 Full written paper - refereedTitle of proceedings
Proceedings of the IEEE Conference on Decision and ControlUsage metrics
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