Hierarchical localization by matching vertical lines in omnidirectional images

In this paper we propose a new vision based method for robot localization using an omnidirectional camera. The method has three steps efficiently combined to deal with big reference image sets, each step evaluates less images than the previous but is more complex and accurate. Given the current uncalibrated image seen by the robot, the hierarchical algorithm gives the possibility of obtaining appearance-based (topological) and metric localization. Compared to other similar vision-based localization methods, the one proposed here has the advantage that it gets accurate metric localization based on a minimal reference image set, using the 1D three view geometry. Moreover, thanks to the linear wide baseline features used, the method is insensitive to illumination changes and occlusions, while keeping the computational load small. The simplicity of the radial line feature used speeds up the process while it keeps acceptable accuracy. We show experiments with two omnidirectional image data-sets to evaluate performance of the method.