Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

A Differentiable Newton-Euler Algorithm for Real-World Robotics


Oct 24, 2021
Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters

* arXiv admin note: text overlap with arXiv:2011.01734 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A Robot Cluster for Reproducible Research in Dexterous Manipulation


Sep 22, 2021
Stefan Bauer, Felix Widmaier, Manuel Wüthrich, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Charles Schaff, Takahiro Maeda, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Annika Buchholz, Sebastian Stark, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bernhard Schölkopf


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Stochastic Control through Approximate Bayesian Input Inference


May 17, 2021
Joe Watson, Hany Abdulsamad, Rolf Findeisen, Jan Peters

* Submitted to Transactions on Automatic Control Special Issue: Learning and Control. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation


May 05, 2021
Niklas Funk, Charles Schaff, Rishabh Madan, Takuma Yoneda, Julen Urain De Jesus, Joe Watson, Ethan K. Gordon, Felix Widmaier, Stefan Bauer, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Matthew R. Walter, Jan Peters


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk


Mar 10, 2021
Joe Watson, Jan Peters

* American Control Conference (ACC) 2021 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning


Nov 03, 2020
Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A Differentiable Newton Euler Algorithm for Multi-body Model Learning


Oct 19, 2020
Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters

* ICML 2020 Workshop on Inductive Biases, Invariances and Generalization in Reinforcement Learning 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Active Inference or Control as Inference? A Unifying View


Oct 01, 2020
Joe Watson, Abraham Imohiosen, Jan Peters

* International Workshop on Active Inference 2020 (IWAI) 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Stochastic Optimal Control as Approximate Input Inference


Oct 07, 2019
Joe Watson, Hany Abdulsamad, Jan Peters

* Conference on Robot Learning (CoRL 2019) 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email