Title :
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
fDate :
June 30 2010-July 2 2010
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;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5530872
