Deep Lagrangian Networks for end-to-end learning of energy-based control
for under-actuated systems

Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

10 July 2019

Kim D. Listmann

Jan Peters

Papers citing "Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems"

18 / 18 papers shown

Title
Geometric Fault-Tolerant Neural Network Tracking Control of Unknown Systems on Matrix Lie Groups Robin Chhabra Farzaneh Abdollahi 41 0 0 07 May 2025
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control T. Duong Abdullah Altawaitan Jason Stanley Nikolay Atanasov 54 10 0 17 Jan 2024
Discovering interpretable Lagrangian of dynamical systems from data Tapas Tripura S. Chakraborty 27 4 0 09 Feb 2023
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems Valentin Duruisseaux T. Duong Melvin Leok Nikolay Atanasov DRL AI4CE 31 12 0 29 Nov 2022
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control Moritz Reuss Niels van Duijkeren R. Krug P. Becker Vaisakh Shaj Gerhard Neumann 9 5 0 27 May 2022
Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning Saul Santos Monica Ekal R. Ventura 32 5 0 20 Jan 2022
Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics Zhichao Li T. Duong Nikolay Atanasov 32 2 0 09 Dec 2021
A Differentiable Newton-Euler Algorithm for Real-World Robotics M. Lutter Vallijah Subasri Joe Watson Frank Rudzicz 29 7 0 24 Oct 2021
Continuous-Time Fitted Value Iteration for Robust Policies M. Lutter Boris Belousov Shie Mannor Dieter Fox Animesh Garg Jan Peters 10 9 0 05 Oct 2021
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 43 39 0 05 Oct 2021
Learning Dynamics Models for Model Predictive Agents M. Lutter Leonard Hasenclever Arunkumar Byravan Gabriel Dulac-Arnold Piotr Trochim N. Heess J. Merel Yuval Tassa AI4CE 57 26 0 29 Sep 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty 52 35 0 12 Feb 2021
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning M. Lutter Johannes Silberbauer Joe Watson Jan Peters OffRL 29 33 0 03 Nov 2020
A Differentiable Newton Euler Algorithm for Multi-body Model Learning M. Lutter Johannes Silberbauer Joe Watson Jan Peters 21 11 0 19 Oct 2020
Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics Manuel A. Roehrl Thomas Runkler Veronika Brandtstetter Michel Tokic Stefan Obermayer PINN 24 77 0 29 May 2020
Structured Mechanical Models for Robot Learning and Control Jayesh K. Gupta Kunal Menda Zachary Manchester Mykel J. Kochenderfer DRL 26 34 0 21 Apr 2020
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints M. Lutter Boris Belousov Kim D. Listmann Debora Clever Jan Peters 11 22 0 13 Sep 2019
Wasserstein Robust Reinforcement Learning Mohammed Abdullah Hang Ren Haitham Bou-Ammar Vladimir Milenkovic Rui Luo Mingtian Zhang Jun Wang 32 75 0 30 Jul 2019