Range estimation from a moving camera: An Immersion and Invariance approach

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2009, Pages 2810-2815

  Morbidi, Fabio ^a   Prattichizzo, Domenico ^a  

^a UNIVERSITY OF SIENA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EXTENSIVE SIMULATIONS; IMAGE PLANE; JACOBIANS; MOVING CAMERAS; NON-LINEAR OBSERVER; NONLINEAR OBSERVABILITY; PIN-HOLE CAMERAS; RANGE ESTIMATION; RANGE ESTIMATORS; RANGE IDENTIFICATION; STATIC POINT;

CAMERAS; DYNAMICAL SYSTEMS; THREE DIMENSIONAL;

ROBOTICS;

EID: 70350389372     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2009.5152615     Document Type: Conference Paper

References (19)

1. R. Abdursul, H. Inaba, and B.K. Ghosh. Nonlinear observers for perspective time-invariant linear systems. Automatica, 40(3):481-490, 2004.
2. B.K. Ghosh, M. Jankovic, and Y.T. Wu. Perspective problems in system theory and its application to machine vision. J. Math. Syst., Estim., Contr., 4(1):3-38, 1994.
3. B.K. Ghosh and E. Loucks. A perspective theory for motion and shape estimation in machine vision. SIAM J. Contr. Optim., 33(5):1530- 1559, 1995.
4. S. Soatto, R. Frezza, and P. Perona. Motion estimation via dynamic vision. IEEE Trans. Automat. Contr., 41(3):393-413, 1996.
5. L. Matthies, T. Kanade, and R. Szeliski. Kalman filter-based algorithms for estimating depth from image sequences. Int. J. Comput. Vis., 3(3):209-236, 1989.
6. B. Sridhar, R. Soursa, and B. Hussein. Passive range estimation for rotorcraft low-attitude flight. Mach. Vis. Appl., 6(1):10-24, 1993.
7. X. Chen and H. Kano. A New State Observer for Perspective Systems. IEEE Trans. Automat. Contr., 47(4):658-663, 2002.
8. W.E. Dixon, Y. Fang, D.M. Dawson, and T.J. Flynn. Range Identification for Perspective Vision Systems. IEEE Trans. Automat. Contr., 48(12):2232-2238, 2003.
9. A. Astolfi and R. Ortega. Immersion and Invariance: A New Tool for Stabilization and Adaptive Control of Nonlinear Systems. IEEE Trans. Automat. Contr., 48(4):590-606, 2003.
10. D. Karagiannis and A. Astolfi. Nonlinear observer design using invariant manifolds and applications. In Proc. 44th IEEE Conf. Dec. Contr., pages 7775-7780, 2005.
11. D. Karagiannis and A. Astolfi. A New Solution to the Problem of Range Identification in Perspective Vision Systems. IEEE Trans. Automat. Contr., 50(12):2074-2077, 2005.
12. D. Carnevale, D. Karagiannis, and A. Astolfi. Reduced-order observer design for nonlinear systems. In Proc. European Contr. Conf., pages 559-564, 2007.
13. A. De Luca, G. Oriolo, and P. Robuffo Giordano. On-Line Estimation of Feature Depth for Image-Based Visual Servoing Schemes. In Proc. IEEE Int. Conf. Robot. Automat., pages 2823-2828, 2007. (Pubitemid 350140611)
14. A. De Luca, G. Oriolo, and P. Robuffo Giordano. Feature Depth Observation for Image-based Visual Servoing: Theory and Experiments. Int. J. Robot. Res., 27(10):1093-1116, 2008.
15. M. Jankovic and B.K. Ghosh. Visually guided ranging from observations of points, lines and curves via an identifier based nonlinear observer. Syst. Contr. Lett., 25(1):63-73, 1995.
16. G.L. Mariottini, G.J. Pappas, D. Prattichizzo, and K. Daniilidis. Vision-based Localization of Leader-Follower Formations. In Proc. 44th IEEE Conf. Dec. Contr., pages 635-640, 2005.
17. R. Hermann and A. Krener. Nonlinear controllability and observability. IEEE Trans. Automat. Contr., AC-22(5):728-740, 1977.
18. J. L. Casti. Recent developments and future perspectives in nonlinear system theory. SIAM Rev., 24(3):301-331, 1982.
19. G.L. Mariottini and D. Prattichizzo. EGT for multiple view geometry and visual servoing: robotics vision with pinhole and panoramic cameras. IEEE Robot. Autom. Mag., 12(4):26-39, 2005.