Vision and control techniques for robotic visual tracking

Algorithms for robotic real-time visual tracking of arbitrary 3-D objects traveling at unknown velocities in a 2-D space are presented. The problem of visual tracking is formulated as a problem of combining control with computer vision. A mathematical formulation that is general enough to be extended to the problem of tracking 3-D objects in 3-D space is presented. The authors propose the use of sum-of-squared differences (SSD) optical flow for the computation of the vector of discrete displacements each instant of time. These displacements can be fed either directly to a PI controller, a pole assignment controller, or a discrete steady-state Kalman filter. In the latter case, the Kalman filter calculates the estimated values of the system's states and exogenous disturbances, and a discrete LQG controller computes the desired motion of the robotic system. The outputs of the controllers are sent to a Cartesian robotic controller that drives the robot.