Learning Contact Dynamics using Physically Structured Neural Networks

Learning Contact Dynamics using Physically Structured Neural Networks

22 February 2021

Andreas Hochlehnert

Alexander Terenin

Steindór Sæmundsson

Papers citing "Learning Contact Dynamics using Physically Structured Neural Networks"

12 / 12 papers shown

Title
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics Katharina Friedl Noémie Jaquier Jens Lundell Tamim Asfour Danica Kragic AI4CE 60 0 0 24 Oct 2024
DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control V. M. Alvarez R. Rosca Cristian G. Falcutescu 27 10 0 09 Sep 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 160 426 0 10 Mar 2020
Variational Integrator Networks for Physically Structured Embeddings Steindór Sæmundsson Alexander Terenin Katja Hofmann M. Deisenroth GNN AI4CE 35 49 0 21 Oct 2019
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M. Lutter Christian Ritter Jan Peters PINN AI4CE 27 374 0 10 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 39 876 0 04 Jun 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 166 5,024 0 19 Jun 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 79 748 0 20 Jan 2018
Learning a Structured Neural Network Policy for a Hopping Task Julian Viereck Jules Kozolinsky Alexander Herzog Ludovic Righetti 45 12 0 29 Sep 2017
Unsupervised Contact Learning for Humanoid Estimation and Control Nicholas Rotella S. Schaal Ludovic Righetti 22 23 0 21 Sep 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 52 722 0 09 May 2017
Gaussian Processes for Data-Efficient Learning in Robotics and Control M. Deisenroth Dieter Fox C. Rasmussen 62 688 0 10 Feb 2015