Learning from Demonstration using a Curvature Regularized Variational Auto-Encoder (CurvVAE)
Travers Rhodes,Tapomayukh Bhattacharjee,Daniel D. Lee,Travers Rhodes,Tapomayukh Bhattacharjee,Daniel D. Lee
Learning intricate manipulation skills from human demonstrations requires good sample efficiency. We introduce a novel learning algorithm, the Curvature-regularized Variational Auto-Encoder (CurvVAE), to achieve this goal. The CurvVAE is able to model the natural variations in human-demonstrated trajectory data without overfitting. It does so by regularizing the curvature of the learned manifold. ...
