Panoramic representation for route recognition by a mobile robot
International Journal of Computer Vision - Special issue on machine vision research at Osaka University
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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This paper presents a localization method using circular correlation of omni-directional image. Mobile robot localization, especially in indoor conditions, is a key component in the development of service robots. Though stereo vision is widely used to find location, the performance is limited due to computational complexity and its view angle. To compensate for this, we utilize a single omni-directional camera which can capture 360( panoramic images around a robot at one time. Position of a mobile robot can be estimated by the correlation between CHL (Circular Horizontal Line) of the landmark image and CHL of image captured at the robot position. To accelerate computation, correlation values are calculated based on FFT (Fast Fourier Transform) and to increase reliability, CHLs are warped and correlation values are recalculated. Experimental results and performance in the real home environment show the feasibility of the method.