Sage Journals: Discover world-class research

Abstract

This paper presents an image-based visual servoing strategy for the autonomous navigation of a mobile holonomic robot from a current towards a desired pose, specified only through a current and a desired image acquired by the on-board central catadioptric camera. This kind of vision sensor combines lenses and mirrors to enlarge the field of view. The proposed visual servoing does not require any metrical information about the three-dimensional viewed scene and is mainly based on a novel geometrical property, the auto-epipolar condition, which occurs when two catadioptric views (current and desired) undergo a pure translation. This condition can be detected in real time in the image domain by observing when a set of so-called disparity conics have a common intersection. The auto-epipolar condition and the pixel distances between the current and target image features are used to design the image-based control law. Lyapunov-based stability analysis and simulation results demonstrate the parametric robustness of the proposed method. Experimental results are presented to show the applicability of our visual servoing in a real context.

Keywords

visual servoing computer vision sensing and perception

Get full access to this article

View all access options for this article.

References

Abdelkader, H.H. , Mezouar, Y. , Andreff, H. and Martinet, P. (2005). Image-based control of mobile robot with central catadioptric cameras. Proceedings IEEE International Conference on Robotics and Automation, pp. 3522—3527.

Baker, S. and Nayar, S.K. (1997). Catadioptric image formation. Proceedings of the DARPA Image Understanding Workshop, pp. 1431—1437.

Baker, S. and Nayar, S.K. (1999). A theory of single-viewpoint catadioptric image formation. International Journal of Computer Vision, 35(2): 175—196.

Barreto, J.P. and Araujo,H. (2005). Geometric properties of central catadioptric line images and their application in calibration. IEEE Transactions on Pattern Analysis and Machine Intelligience, 27(8): 1327—1333.

Barreto, J.P. , Martin, F. and Horaud, R. (2002). Visual servoing/tracking using central catadioptric images. Proceedings of the 8th International Symposium on Eperimental Robotics, pp. 863—869.

Benhimane, S. and Malis, E. (2003). Vision-based control with respect to planar and non-planar objects using a zooming camera. Proceedings IEEE International Conference on Advanced Robotics, pp. 863—869.

Chaumette, F. (2004). Image moments: a general and useful set of features for visual servoing. IEEE Transactions on Robotics, 20(4): 713—723.

Chesi, G. , Hashimoto, K. , Prattichizzo, D. and Vicino, A. (2004). Keeping features in the field of view in eye-in-hand visual servoing: a switching approach. IEEE Transactions on Robotics, 20(5): 908—914.

Conticelli, F. , Allotta, B. and Khosla, P.K. (1999). Image-based visual servoing of nonholonomic mobile robots. Proceedings of the 38th IEEE Conference on Decision and Control, Phoenix, AZ, 7—10 December 1999, pp. 3496— 3501.

10.

Cowan, N. , Weingarten, J. and Koditshek, D. (2002). Visual servoing via navigation functions. IEEE Transctions on Robotics and Automation, 18(4): 521—533.

11.

Elliot, M. , Morris, W. and Xiao, J. (2006). City-climber, a new generation of wall-climbing robots. Video Proceedings of the 2006 IEEE International Conference on Robotics and Automation, pp. 3522—3527.

12.

Fang, Y. , Dixon, W.E. , Dawson, D.M. and Chawda, P. (2005). Homography-based visual servo regulation of mobile robots. IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, 35(5): 1041—1050.

13.

Faugeras, O. (1993). 3-D Computer Vision, A Geometric Viewpoint. Cambridge, MA, MIT Press.

14.

Gaspar, J. , Winters, N. and Santos-Victor, J. (2000). Vision-based navigation and environmental representations with an omnidirectional camera. IEEE Transactions on Robotics and Automation, 16(6): 890—898.

15.

Geyer, C. and Daniilidis, K. (2000). An unifying theory for central panoramic systems and practical implications. Proceedings of the 6th European Conference on Computer Vision, pp. 445—462.

16.

Geyer, C. and Daniilidis, K. (2001). Catadioptric projective geometry. International Journal of Computer Vision, 45(3): 223—243.

17.

Geyer, C. and Daniilidis, K. (2002). Paracatadioptric camera calibration. Pattern Analysis and Machine Intelligence, 24(5): 687—695.

18.

Geyer, C. and Daniilidis, K. (2003). Mirrors in motion: epipolar geometry and motion estimation. Proceedings 9th IEEE International Conference on Computer Vision, vol. 2, pp. 766—773.

19.

Hartley, R. and Zisserman, A. (2000). Multiple View Geometry in Computer Vision. Cambridge, Cambridge University Press.

20.

Hutchinson, S.A. , Hager, G.D. and Corke, P.I. (1996). A tutorial on visual servo control. IEEE Transactions on Robotics and Automation, 12(5): 651—670.

21.

Ma, Y. , Soatto, S. , Košecká, J. and Sastry, S.S. (2003). An Invitation to 3-D Vision: From Images to Geometric Models. Berlin, Springer.

22.

Makadia, A. , Geyer, C. and Daniilidis, K. (2007). Correspondence tree from motion. International Journal of Computer Vision, 75(3): 311—327.

23.

Malis, E. , Chaumette, F. and Boudet, S. (1998). 2D 1/2 visual servoing stability analysis with respect to camera calibration errors. Proceedings 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems, Victoria, BC, 13—17 October 1998, pp. 691—697.

24.

Malis, E. , Chaumette, F. and Boudet, S. (1999). 2-1/2-D visual servoing. IEEE Transactions on Robotics and Automation, 15(2): 238—250.

25.

Mariottini, G.L. , Alunno, E. , Piazzi, J. and Prattichizzo, D. (2005). Epipole-based visual servoing with central catadioptric camera. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pp. 3516— 3521.

26.

Mariottini, G.L. , Oriolo, G. and Prattichizzo, D. (2007). Image-based visual servoing for nonholonomic mobile robots using epipolar geometry. IEEE Transactions on Robotics, 23(1): 87—100.

27.

Mariottini, G.L. and Prattichizzo, D. (2005). EGT for multiple view geometry and visual servoing. Robotics and Automation Magazine, 12(4): 26—39.

28.

Mezouar, Y. , Abdelkader, H.H. , Martinet, P. and Chaumette, F. (2004). Central catadioptric visual servoing from 3d straight lines. Proceedings 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 343— 349.

29.

Nayar, S.K. (1997). Catadioptric omnidirectional camera. Proceedings of the International Conference on Computer Vision and Pattern Recognition, pp. 482—488.

30.

Oriolo, G. and Vendittelli, M. (2005). A framework for the stabilization of general nonholonomic systems with an application to the plate—ball mechanism. IEEE Transactions on Robotics, 21(2): 162—175.

31.

Pajdla, T. and Hlaváč, V. (1999). Zero phase representation of panoramic images for image based localization. Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns, pp. 550—557.

32.

Usher, K. , Ridley, P. and Corke, P. (2003). Visual servoing for a car-like vehicle—an application of omnidirectional vision. Proceedings IEEE International Conference on Robotics and Automation, pp. 4288—4293.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB