Adaptive supervision of moving objects for mobile robotics applications

One of the main tasks of mobile robotics is vision. Lighting independence, adaptivity and automated learning are still the main issues when it comes to applications. In this article, we present an image understanding system and its methods targeting automatic, lighting-independent and reliable color-based object recognition under real time conditions. Its application test bed is global vision robot soccer (i.e. FIRA MiroSot und RoboCup Small Size leagues) but it has many other applications in color-based supervision of moving objects. Under typical conditions, it learns the objects of recognition automatically, has zero setup time and tolerates environmental changes during run-time.