Spatial reasoning for robot navigation using the Helmholtz-Hodge decomposition of omnidirectional optical flow

The Helmholtz-Hodge decomposition separates a vector filed into translation, rotation, and divergent vector fields. In this paper, using the Helmholtz-Hodge decomposition of omnidirectional optical flow field, we develop geometric algorithms for the detection of free space and navigation direction. For free space direction and navigation, we use catadioptric image sequences and spherical image sequence, respectively.

[1]  Mrinal K. Mandal,et al.  Efficient Hodge-Helmholtz decomposition of motion fields , 2005, Pattern Recognit. Lett..

[2]  Giulio Sandini,et al.  Uncalibrated obstacle detection using normal flow , 1996 .

[3]  Gang Liu,et al.  Cardiac video analysis using Hodge-Helmholtz field decomposition , 2006, Comput. Biol. Medicine.

[4]  Roland Siegwart,et al.  Robot Navigation by Panoramic Vision and Attention Guided Fetaures , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[5]  Tomás Svoboda,et al.  Epipolar Geometry of Panoramic Cameras , 1998, ECCV.

[6]  José Santos-Victor,et al.  Vision-based navigation and environmental representations with an omnidirectional camera , 2000, IEEE Trans. Robotics Autom..

[7]  J. Gaspar,et al.  Omni-directional vision for robot navigation , 2000, Proceedings IEEE Workshop on Omnidirectional Vision (Cat. No.PR00704).

[8]  Shree K. Nayar,et al.  Catadioptric omnidirectional camera , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Atsushi Imiya,et al.  Featureless robot navigation using optical flow , 2005, Connect. Sci..

[10]  Holger G. Krapp,et al.  Insect-Inspired Estimation of Egomotion , 2004, Neural Computation.

[11]  Andrew Vardy,et al.  Biologically plausible visual homing methods based on optical flow techniques , 2005, Connect. Sci..

[12]  C. Laugier,et al.  Real-time moving obstacle detection using optical flow models , 2006, 2006 IEEE Intelligent Vehicles Symposium.