Kalman filters are optimal estimators used in robotics for tracking dynamic systems. The discussion centers on implementing a Kalman filter for tracking corner features in image frames, particularly when some features may disappear or move outside the frame. Key points include the need to establish linear or nonlinear equations of motion based on the robot's movement, which can include straight lines, rotations, or arcs. The filter can estimate velocity components even if they are not initially known, and while tracking a large number of points is feasible, tailored implementations are necessary for specific applications. Guidance on forming dynamic and measurement equations is essential for effective use of the Kalman filter in this context.