Memory-based self-localization using omnidirectional images

This paper proposes a new self-localization method using an omnidirectional image sensor which can observe a surrounding environment with 360-degree of view. The method extracts information which is identical for the position of a sensor and invariant against the rotation of the sensor by generating an autocorrelation image from an observed omnidirectional image. The location of the sensor is estimated by evaluating the similarity among the autocorrelation image of an observed image and stored autocorrelation images. The similarity of autocorrelation images is evaluated in low dimensional eigenspaces generated with stored autocorrelation images. We have conducted experiments with real images and examined the performance of the proposed method. The results show that accurate and robust estimation of the sensor's position is possible with our method.