Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics
Learning and Control

Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control

17 January 2024

Abdullah Altawaitan

Nikolay A. Atanasov

Papers citing "Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control"

10 / 10 papers shown

Title
Learned Perceptive Forward Dynamics Model for Safe and Platform-aware Robotic Navigation Pascal Roth Jonas Frey César Cadena Marco Hutter 28 0 0 27 Apr 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 72 1 0 15 Dec 2024
Optimal Potential Shaping on SE(3) via Neural ODEs on Lie Groups Yannik P. Wotte Federico Califano Stefano Stramigioli AI4CE 11 1 0 25 Jan 2024
Learning Interpretable Dynamics from Images of a Freely Rotating 3D Rigid Body J. Mason Christine Allen-Blanchette Nicholas Zolman Elizabeth Davison Naomi Ehrich Leonard 3DH AI4CE 21 8 0 23 Sep 2022
LEMURS: Learning Distributed Multi-Robot Interactions Eduardo Sebastián T. Duong Nikolay A. Atanasov Eduardo Montijano C. Sagüés 62 8 0 20 Sep 2022
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias Yupu Lu Shi-Min Lin Guanqi Chen Jia-Yu Pan 16 6 0 24 Jun 2022
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 27 38 0 05 Oct 2021
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 32 57 0 14 Sep 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 121 364 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 139 219 0 29 Sep 2019