제어로봇시스템학회:학술대회논문집
- 2005.06a
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- Pages.480-485
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- 2005
A Note on State Estimation Problems for Perspective Linear Systems Corrupted by Noises
- Kondo, Ryota (Department of Information Sciences, Tokyo Denki University) ;
- Abdursul, Rixat (The 21st Century COE Project, Tokyo Denki University) ;
- Inaba, Hiroshi (Department of Information Sciences, Tokyo Denki University)
- Published : 2005.06.02
Abstract
Perspective dynamical systems arise in machine vision problems, in which only perspective observation is available. This paper considers the state estimation problem for a rigid body moving in three dimensional spaces using the image data obtained by a CCD camera or some other means. Because the motion of the rigid body and the observed data are generally corrupted by noises, it is necessary to seek a state estimation method to reduce the influence of the noises. In this paper, by means of computer simulations for a simple example, we examine the sensitivity to the noises of the nonlinear observer developed in the recent paper ([1] R. Abdursul, H. Inaba and B. Ghosh, Nonlinear observers for perspective time-invariant linear systems, Automatica, vol. 40, Issue 3, pp. 481-490, 2004) and the effectiveness of the Extended Kalman Filter.
Keywords
- Perspective system;
- Nonlinear observer;
- Luenberger-type observer;
- Extended Kalman Filter;
- Machine vision