Rudolph's main research area are machine learning algorithms applied to mobile robotics tasks, in particular robot perception. He investigates probabilistic reasoning methods for object detection and recognition, and he works on efficient learning methods for classification applications which are particularly suited for mobile robots. Recently, his interests are focussed on unsupervised and online learning methods as well as their efficient implementation on real robotic systems.