The goal of this thesis is to combine a frame-based scene segmentation approach (based on depth and color) and a tracking-based approach (based on coherent motion of SIFT features) to yield more robust tracking results.
“Scaffolding” is a powerful principle taken from psychology for organizing and optimizing the progress of a learner. The goal in this project is to combine this powerful structuring of a learning process with recent advances in deep and hierarchical reinforcement learning in order to make learning of an artificial agent more efficient and feasible when interaction data is much more limited than considered in current studies.
The human fingernail turns out to be very important when it comes to picking coins, scratching off stickers, or simply probing surfaces. To endow robots with similar capabilities, in this project, we are developing a sensorized fingernail for mechanical hands, i.e. robotic or prostetic hands, capable of measuring vibratory and static contact forces. High sensitivity combined with robustness for daily use are the key features describing our proposed design.
Clothing provides a challenging test domain for research in the field of cognitive robotics. On the one hand, robots have to make use of commonsense knowledge to be able to understand the socially constructed meaning and function of garments. On the other hand, the variance resulting from deformations and differences between individual items of clothing calls for implicit representations which have to be learned from experience. Our robot uses topological, geometric, and subsymbolic knowledge representations for the manipulation of clothes with its anthropomorphic hands. read more »
The tactile-sensitive poking stick has mounted our Shadow Hand's tactile finger tip on a rigid stick and allows for evaluation of the finger tip itself, but also of tactile-based control algorithms - without involving the complexity of the Shadow Hands themselves.
Clothing provides a challenging test domain for research in the field of cognitive robotics. On the one hand, robots have to make use of commonsense knowledge to be able to understand the socially constructed meaning and function of garments. On the other hand, the variance resulting from deformations and differences between individual items of clothing calls for implicit representations which have to be learned from experience. Our robot uses topological, geometric, and subsymbolic knowledge representations for the manipulation of clothes with its anthropomorphic hands. 
The tactile-sensitive poking stick has mounted our