The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

In this paper, a modified LQG technique is proposed for the solution of the robotic visual tracking problem (eye-in-hand configuration). The problem of robotic visual tracking is formulated as a problem of combining control with computer vision. A cross-correlation method provides the object's motion measurements which are used to update the system's measurement vector. These measurements are fed to a discrete steady state Kalman filter that calculates the estimated values of the system's states and of the exogenous disturbances. Then, a discrete LQG controller computes the desired motion of the robotic system. Experimental results are presented to show the effectiveness of the approach.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Text Reference

N.P. Papanikolopoulos and Pradeep Khosla, "Real-Time LQG Robotic Visual Tracking," Presented at the 1991 European Robotics and Intelligent Systems Conference ( EURISCON '91), June, 1991.

BibTeX Reference

@inproceedings{Khosla_1991_4214,
   author = "N.P. Papanikolopoulos and Pradeep Khosla",
   title = "Real-Time LQG Robotic Visual Tracking",
   booktitle = "Presented at the 1991 European Robotics and Intelligent Systems Conference ( EURISCON '91)",
   month = "June",
   year = "1991",
}

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