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

Authors:
Pubudu n. Pathirana;Adrian n. Bishop;Andrey v. Savkin;Samitha w. Ekanayake;Timothy j. Black
Affiliations:
School of engineering and it, deakin university, australia;School of engineering and it, deakin university, australia;School of electrical engineering and telecommunications, university of new south wales, australia;School of engineering and it, deakin university, australia;School of engineering and it, deakin university, australia
Venue:
Robotica
Year:
2010

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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).