Autonomous Perceptive Systems
The research group Autonomous Perceptive Systems aims at understanding the mechanisms that enable autonomous systems to produce adequate responses when confronted with a complex, time-variant environment. The research addresses three facets: perception, learning and control. The paradigmatic example problems concern classification of images and other sensory patterns, learning of complicated tasks using minimal training information and adaptive control in robotic systems. Major methods are (deep) neural networks, reinforcement learning, adaptive control and explicit biophysical modeling of sensor systems.