From Cognitive Representation to Technical Synthesis of Manual Action

What insights can we gain from psychological measurements of biomechanical parameters and subjective judgements of manual actions (like object grasping) about the structures of the underlying cognitive representations? In this project, we will bring together statistical methods (like structure dimensional and principal components analysis) with connectionist approaches employing artificial neural networks to test different hypotheses about the cognitive structure of manual actions. A major goal will be to emulate and control grasping behavior for a broad range of objects in kinematic simulations and - as a longer term objective - in real physics on a robot platform.