Nonlinear observer for structure estimation using a paracatadioptric camera

Author

Dani, A.P. ; Fischer, N.R. ; Zhen Kan ; Dixon, W.E.

Author_Institution

Dept. of Mech. & Aerosp. Eng., Univ. of Florida, Gainesville, FL, USA

fYear

2010

fDate

June 30 2010-July 2 2010

Firstpage

3487

Lastpage

3492

Abstract

Estimation of the three-dimensional (3D) Euclidean coordinates of points on an object using two-dimensional (2D) image data is required by many robotics and surveillance applications. This paper develops a nonlinear observer to estimate relative Euclidean coordinates of an object viewed by a moving paracatadioptric camera with known motion. The observer exponentially estimates the structure of an object (i.e. Euclidean coordinates of different points on an object) provided sufficient observability conditions are satisfied. Observer gain conditions are derived based on a Lyapunov-analysis, which guarantees convergence, and simulation results illustrate the performance of the observer in the presence of image noise.

Keywords

Lyapunov methods; cameras; computational geometry; convergence of numerical methods; image recognition; motion estimation; observers; Euclidean coordinate; Lyapunov-analysis; image noise; nonlinear observer; observer gain; paracatadioptric camera; structure estimation; Cameras; Convergence; Feedback; Layout; Mirrors; Motion estimation; Observers; Robot kinematics; Robot vision systems; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2010

Conference_Location

Baltimore, MD

ISSN

0743-1619

Print_ISBN

978-1-4244-7426-4

Type

conf

DOI

10.1109/ACC.2010.5530872

Filename

5530872