Range identification for nonlinear parameterizable paracatadioptric systems |
| |
Authors: | Nitendra Nath [Author Vitae] Enver Tatlicioglu [Author Vitae] |
| |
Affiliation: | a Department of Electrical & Computer Engineering, Clemson University, Clemson, SC 29634-0915, United States b Department of Electrical & Electronics Engineering, Izmir Institute of Technology, Urla, Izmir, 35430, Turkey |
| |
Abstract: | In this paper, a new range identification technique for a calibrated paracatadioptric system mounted on a moving platform is developed to recover the range information and the three-dimensional (3D) Euclidean coordinates of a static object feature. The position of the moving platform is assumed to be measurable. To identify the unknown range, first, a function of the projected pixel coordinates is related to the unknown 3D Euclidean coordinates of an object feature. This function is nonlinearly parameterized (i.e., the unknown parameters appear nonlinearly in the parameterized model). An adaptive estimator based on a min-max algorithm is then designed to estimate the unknown 3D Euclidean coordinates of an object feature relative to a fixed reference frame which facilitates the identification of range. A Lyapunov-type stability analysis is used to show that the developed estimator provides an estimation of the unknown parameters within a desired precision. Numerical simulation results are presented to illustrate the effectiveness of the proposed range estimation technique. |
| |
Keywords: | Nonlinear parameterization Range identification Paracatadioptric systems Lyapunov methods Vision-based estimation min-max algorithm |
本文献已被 ScienceDirect 等数据库收录! |
|