Manifold Learning

Guess Factor based methods generalize well, based on priori knowledge about robots moving in circles & max escape angle. Better methods such as precise max escape angle helps greatly. However given enough samples, I wonder whether some deep enough model can learn the shape of escape envelop, as well as precise max escape angle, etc. And generalize even better.