Range identification for perspective vision systems

In this paper, a new continuous observer is developed to determine range information (and hence the 3-dimensional (3D) coordinates) of an object feature moving with affine motion dynamics (or the more general Riccati motion dynamics) with known motion parameters. The unmeasurable range information is determined from a single camera provided an observability condition is satisfied that has physical significance. To develop the observer, the perspective system is expressed in terms of the nonlinear feature dynamics. The structure of the proposed observer is inspired by recent disturbance observer results. The proposed technique facilitates a Lyapunov-based analysis that is less complex than the sliding-mode based analysis derived for recent discontinuous observer designs. The analysis demonstrates that the 3D task-space coordinates of the feature point can be asymptotically identified.