applied differential geometry

We address the problem of planning robot motions in constrained configuration spaces where the constraints change throughout the motion.

We consider the problem of learning representations of constraints from demonstrations with a deep neural network, which we call Equality Constraint Manifold Neural Network (ECoMaNN).