269 citations · 2k across the 61 of their papers we have counts for
5 papers · 1 filter
Multi-Task Learning with Sequence-Conditioned Transporter Networks
Michael H. Lim, Andy Zeng, Brian Ichter +5
Enabling robots to solve multiple manipulation tasks has a wide range of industrial applications. While learning-based approaches enjoy flexibility and generalizability, scaling th…
Scaling simulation-to-real transfer by learning composable robot skills
Ryan Julian, Eric Heiden, Zhanpeng He +5
We present a novel solution to the problem of simulation-to-real transfer, which builds on recent advances in robot skill decomposition. Rather than focusing on minimizing the simu…
Online Learning of a Memory for Learning Rates
Franziska Meier, Daniel Kappler, Stefan Schaal
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning ta…
Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers
Andreas Doerr, Duy Nguyen-Tuong, Alonso Marco +2
PID control architectures are widely used in industrial applications. Despite their low number of open parameters, tuning multiple, coupled PID controllers can become tedious in pr…
Local Gaussian Regression
Franziska Meier, Philipp Hennig, Stefan Schaal
Locally weighted regression was created as a nonparametric learning method that is computationally efficient, can learn from very large amounts of data and add data incrementally.…