A learning framework for generic sensory-motor maps

We present a new approach to cope with unknown redundant systems. For this we present i) an online algorithm that learns general input-output restrictions and, ii) a method that, given a partial set of input-output variables, provides an estimate of the remaining ones, using the learned restrictions. We show applications of the algorithm using examples of direct and inverse robot kinematics.