Omnidirectional Vision and Inertial Clues for Robot Navigation

The structural features inherent in the visual motion field of a mobile robot contain useful clues about its navigation. The combination of these visual clues and additional inertial sensor information may allow reliable detection of the navigation direction for a mobile robot and also the independent motion that might be present in the 3D scene. The motion field, which is the 2D projection of the 3D scene variations induced by the camera-robot system, is estimated through optical flow calculations. The singular points of the global optical flow field of omnidirectional image sequences indicate the translational direction of the robot as well as the deviation from its planned path. It is also possible to detect motion patterns of near obstacles or independently moving objects of the scene. In this paper, we introduce the analysis of the intrinsic features of the omnidirectional motion fields, in combination with gyroscopical information, and give some examples of this preliminary analysis. © 2004 Wiley Periodicals, Inc.

[1]  I. Stratmann Omnidirectional imaging and optical flow , 2002, Proceedings of the IEEE Workshop on Omnidirectional Vision 2002. Held in conjunction with ECCV'02.

[2]  David J. Fleet,et al.  Performance of optical flow techniques , 1994, International Journal of Computer Vision.

[3]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[4]  N. Franceschini,et al.  From insect vision to robot vision , 1992 .

[5]  J. Aloimonos,et al.  Finding motion parameters from spherical motion fields (or the advantages of having eyes in the back of your head) , 1988, Biological Cybernetics.

[6]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[7]  Yiannis Aloimonos Visual Navigation: From Biological Systems to Unmanned Ground Vehicles , 1996 .

[8]  A. Makadia,et al.  Image processing in catadioptric planes: spatiotemporal derivatives and optical flow computation , 2002, Proceedings of the IEEE Workshop on Omnidirectional Vision 2002. Held in conjunction with ECCV'02.

[9]  Giulio Sandini,et al.  Divergent stereo for robot navigation: learning from bees , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[10]  M. Srinivasan,et al.  Reflective surfaces for panoramic imaging. , 1997, Applied optics.