A method for stereo-vision-based tracking for robotic applications
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Pathirana, Pubudu; Bishop, Adrian; Savkin, Andrey V; Ekanayake , Samitha W.; Black, Timothy J.
Description
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...[Show more]
dc.contributor.author | Pathirana, Pubudu | |
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dc.contributor.author | Bishop, Adrian | |
dc.contributor.author | Savkin, Andrey V | |
dc.contributor.author | Ekanayake , Samitha W. | |
dc.contributor.author | Black, Timothy J. | |
dc.date.accessioned | 2015-12-13T22:43:46Z | |
dc.identifier.issn | 0263-5747 | |
dc.identifier.uri | http://hdl.handle.net/1885/79349 | |
dc.description.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). | |
dc.publisher | Cambridge University Press | |
dc.source | Robotica | |
dc.subject | 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 | |
dc.title | A method for stereo-vision-based tracking for robotic applications | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 28 | |
dc.date.issued | 2010 | |
local.identifier.absfor | 080100 - ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING | |
local.identifier.ariespublication | f5625xPUB7810 | |
local.type.status | Published Version | |
local.contributor.affiliation | Pathirana, Pubudu, Deakin University | |
local.contributor.affiliation | Bishop, Adrian, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Savkin, Andrey V, University of New South Wales | |
local.contributor.affiliation | Ekanayake , Samitha W., Deakin University | |
local.contributor.affiliation | Black, Timothy J., Deakin University | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.issue | 4 | |
local.bibliographicCitation.startpage | 517 | |
local.bibliographicCitation.lastpage | 524 | |
local.identifier.doi | 10.1017/S0263574709005827 | |
dc.date.updated | 2016-02-24T09:37:24Z | |
local.identifier.scopusID | 2-s2.0-77954541516 | |
Collections | ANU Research Publications |
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