Range identification for perspective vision systems

Abstract

In this note, a new observer is developed to determine range information (and, hence, the three-dimensional (3-D) coordinates) of an object feature moving with affine motion dynamics (or the more general Ricatti 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 observer designs. The analysis demonstrates that the 3-D task-space coordinates of the feature point can be asymptotically identified. Simulation results are provided that illustrate the performance of the observer in the presence of noise.