forcetracking

Forcetracking is a term used in multiple disciplines to describe tracking methods that involve actively applying constraints or inputs to influence the trajectory, state, or estimate of a target. In dynamical systems, forcing refers to time-dependent inputs that drive the evolution of the system; forcetracking describes strategies that maintain alignment with a target by accounting for such forcing terms when estimating or predicting behavior.

In control theory and signal processing, forcetracking may refer to estimation and control techniques that incorporate a forcing function or external influence, in order to reduce tracking error under disturbances. This can include constrained state estimation, model predictive control with forcing terms, or observers designed to track a moving target despite noise.

In computer vision and robotics, forcetracking can describe algorithms that enforce priors or geometric constraints to keep a tracker locked on a target when features are obscured or the scene changes, effectively applying a "force" to maintain continuity of the track. The term is not tied to a single canonical algorithm but denotes the general idea of combining modeling, measurement, and external input to sustain robust tracking.

Common related concepts include state estimation, Kalman filtering with forcing terms, particle filtering, and constraint-based tracking. The applicability of forcetracking spans surveillance, navigation, robotics, and experimental physics, among others.