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C. Ackerman, L. Itti, Robot Steering With Spectral Image Information, IEEE Transactions on Robotics, Vol. 21, No. 2, pp. 247-251, Apr 2005. [2003 impact factor: 2.103] (Cited by 44)
Abstract: We introduce a method for rapidly classifying visual scenes, globally along a small number of navigationally relevant dimensions: depth of scene, presence of obstacles, path vs. non-path, and orientation of path. We show that the algorithm reliably classifies scenes in terms of these high-level features, based on global or coarsely localized spectral analysis analogous to early-stage biological vision. We use this analysis to implement a real-time visual navigational system on a mobile robot, trained online by a human operator. We demonstrate successful training and subsequent autonomous path following for two different out-door environments, a running track and a concrete trail. Our success with this technique suggests a general applicability to autonomous robot navigation in a variety of environments.
Keywords: autonomous robot ; Fourier transform ; vision ; path following ; navigation ; gist of a scene
Themes: Beobots, Computer Vision, Scene Understanding
Copyright © 2000-2007 by the University of Southern California, iLab and Prof. Laurent Itti.
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