4 accepted papers
We present the HD Ground Database, a comprehensive database for ground texture based localization. It contains sequences of a variety of textures, obtained using a downward facing camera. In contrast to existing databases of ground images, the HD Ground Database is larger, has a greater variety of t…
Ground texture based localization is a promising approach to achieve high-accuracy positioning of vehicles. We present a self-contained method that can be used for global localization as well as for subsequent local localization updates, i.e. it allows a robot to localize without any knowledge of it…
Localization using ground texture images recorded with a downward-facing camera is a promising approach to achieve reliable high-accuracy vehicle positioning. A common way to accomplish the task is to focus on prominent features of the ground texture such as stones and cracks. Our results indicate t…
Searching for objects and distinguishing task-relevant objects from others is a key requirement for service robots. We propose a reinforcement learning solution to the active visual object search problem. Our method successfully learns to explore the environment, to approach the target object, and t…