From cognitive representation to technical synthesis of manual action

The human hand is one of the most complex extremities that we find in nature and many tasks require our hands to operate in a coordinated fashion to successfully interact with our environment. Thus, the way in which we can act manually is directly influenced by how actions and possibility there of are represented in the brain. The first step of this project will elucidate how psychologically measured structures of the representation of manual actions (like object grasping) and their biomechanical parameters (e.g. kinematics) interdepend and relate to each other. For this part we will employ statistical methods like Structure Dimensional Analysis – Motoric (SDAM) and Principal Components Analysis (PCA). In a second step we will construct an artificial neural network drawing on the results of these psychological and biomechanical analyses. Connected to a kinematic simulation of a human hand this network will be able to emulate and control grasping behavior adequate for a broad range of objects. A long-term objective includes the implementation of the system on a robotic platform.[view:groupmembers==208]