Robot Localisation Using Natural Landmarks

This paper introduces an optimised method for extracting natural landmarks to improve localisation during RoboCup soccer matches. The method uses modified 1D SURF features extracted from pixels on the robot’s horizon. Consistent with the original SURF algorithm, the extracted features are robust to lighting changes, scale changes, and small changes in viewing angle or to the scene itself. Furthermore, we show that on a typical laptop 1D SURF runs more than one thousand times faster than SURF, achieving sub-millisecond performance. This makes the method suitable for visual navigation of resource constrained mobile robots. We demonstrate that by using just two stored images, it is possible to largely resolve the RoboCup SPL field end ambiguity.