Localization results.

<p>Percentage of correct localizations when (a) occlusions are present in the test images (b) noise is considered, (c) simultaneous occlusions and noise are considered and (d) the robot presents any orientation in the test position and also simultaneous occlusions and noise.</p

Results of the side detection algorithm.

<p>Percentage of test images that have been classified on the correct side of the trajectory versus <i>α</i> and <i>c</i>_<i>Th</i>.</p

Processing time of the side detection algorithm.

<p>The figure shows the necessary time to detect the side versus <i>α</i>.</p

Phase only correlation.

<p>Result of the POC operation between two RT descriptors <b><i>r</i></b>₁ and <b><i>r</i></b>₂. The original images <i>f</i>₁ and <i>f</i>₂ were captured on the same point of the floor plane with orientations <i>θ</i>₁ and <i>θ</i>₂ respectively. The RT descriptors of these images are <b><i>r</i></b>₁ and <b><i>r</i></b>₂ respectively. The result of the POC operation between <b><i>r</i></b>₁ and <b><i>r</i></b>₂ is the matrix , whose elements take values between 0 and 1. These values are shown in a colour scale. The maximum value in is a measure of similitude between <b><i>r</i></b>₁ and <b><i>r</i></b>₂ (the higher value the maximum component takes, the most similar both matrices are) and it is independent on the change of orientation. The position of the maximum value permits estimating the relative orientation of the robot when capturing both initial images <i>θ</i>₂₁ = <i>θ</i>₂ − <i>θ</i>₁.</p

Radon Transform of an omnidirectional image.

<p>(a) sample omnidirectional image , (b) Radon Transform of the sample image and (c) final RT descriptor of the sample image .</p

Distance measures.

<p>Distance measures.</p

Orientation estimation results.

<p>Average orientation error obtained with method 1 and <i>cityblock</i> distance and with method 3. Simultaneous occlusions and noise are considered in the test images.</p

Set of images.

<p>Trajectory followed by the robot to capture the whole set of images. The capture points are shown as green dots. Some sample omnidirectional images are shown.</p

Computation time of the position estimation process.

<p>Computation time of the position estimation process.</p

Occlusions and noise on the test images.

<p>(a) Original sample test image with (b), (c), (d) different increasing levels of partial occlusion; (e), (f), (g) increasing levels of Gaussian noise and (h), (i), (j) increasing levels of simultaneous occlusion and noise.</p