The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

The authors present algorithms for robotic (eye-in-hand configuration) real-time visual tracking of arbitrary 3D objects traveling at unknown velocities in a 2D space (depth is given as known). Visual tracking is formulated as a problem of combining control with computer vision. A mathematical formulation of the control problem that includes information from a novel feedback vision sensor and represents everything with respect to the camera frame is presented. The sum-of-squared differences (SSD) optical flow is used to compute the vector of discrete displacements each instant of time. These displacements can be fed either directly to a PI (proportional-integral) controller or to a pole assignment controller or discrete steady-state Kalman filter. In the latter case, the Kalman filter calculates the estimated values of the system's states and the exogenous disturbances, and a discrete LQG (linear-quadratic Gaussian) controller computes the desired motion of the robotic system. The outputs of the controllers are sent to the Cartesian robotic controller. Performance results are presented.

Notes

Text Reference

N. Papanikolopoulos, Pradeep Khosla, and Takeo Kanade, "Visual Tracking of a Moving Target by a Camera Mounted on a Robot: A Combination of Control and Vision," IEEE Transactions on Robotics and Automation, Vol. 9, No. 1, February, 1993, pp. 14-35.

BibTeX Reference

@article{Khosla_1993_1337,
   author = "N. Papanikolopoulos and Pradeep Khosla and Takeo Kanade",
   title = "Visual Tracking of a Moving Target by a Camera Mounted on a Robot: A Combination of Control and Vision",
   journal = "IEEE Transactions on Robotics and Automation",
   pages = "14-35",
   month = "February",
   year = "1993",
   volume = "9",
   number = "1",
}

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