Edge-based Features from Omnidirectional Images for Robot Localization
نویسندگان
چکیده
We propose a method for extracting lowdimensional features from omnidirectional images to be used for robot localization and navigation. Edge detection is combined with thresholding to locate sharp edge pixels, the coordinates of which are fed into a Parzeii density estimator to compute the edge spatial density. The use of the Fast Fourier Transform makes this density estimate feasible in real-time, while Priricipal Component Analysis further drops the dimeiisionality of the resulting feature vector to a manageable number. We show experimental results from a Nomad XR4000 robot in an office environment.
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تاریخ انتشار 2001