Robotica

Table of Contents - 2010 - Volume 28, Issue 04  

Article

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

Pubudu N. Pathiranaa1 c1, Adrian N. Bishopa1, Andrey V. Savkina2, Samitha W. Ekanayakea1 and Timothy J. Blacka1

a1 School of Engineering and IT, Deakin University, Australia

a2 School of Electrical Engineering and Telecommunications, University of New South Wales, Australia

SUMMARY

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).

(Received April 27 2009)

(Online publication June 09 2009)

KEYWORDS:

  • Linear filtering;
  • Set-estimation;
  • Stereo vision;
  • Robust filtering;
  • Target tracking

Correspondence:

c1 Corresponding author. E-mail: pubudu@deakin.edu.au