Efficient visual homing based on Fourier transformed panoramic images ?
We present a fast and efficient homing algorithm based on Fourier transformed panoramic images. By continuously comparing Fourier coefficients calculated from the current view with coefficients representing the goal location, a mobile robot is able to find its way back to known locations. No prior knowledge about the orientation with respect to the goal location is required, since the Fourier phase is used for a fast sub-pixel orientation estimation. We present homing runs performed by an autonomous mobile robot in an office environment. In a more comprehensive investigation the algorithm is tested on an image data base recorded by a small mobile robot in a toy house arena. Catchment areas for the proposed algorithm are calculated and compared to results of a homing scheme described in [M. Franz, B. Schlkopf, H. Mallot, H. Blthoff, Where did I take that snapshot? Scene based homing by image matching, Biological Cybernetics 79 (1998) 191202] and a simple homing strategy using neighbouring views. The results show that a small number of coefficients is sufficient to achieve a good homing performance. Also, a coarse-to-fine homing strategy is proposed in order to achieve both a large catchment area and a high homing accuracy: the number of Fourier coefficients used is increased during the homing run.
visual homing fourier transformation panoramic images orientation estimation