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Structured learning of rigid-body dynamics: A survey and unified view
  from a robotics perspective
v1v2 (latest)

Structured learning of rigid-body dynamics: A survey and unified view from a robotics perspective

11 December 2020
A. R. Geist
Sebastian Trimpe
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Structured learning of rigid-body dynamics: A survey and unified view from a robotics perspective"

9 / 9 papers shown
Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes
Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes
Jan-Hendrik Ewering
Robin E. Herrmann
Niklas Wahlström
Thomas B. Schon
Thomas Seel
PINNAI4CE
152
1
0
07 Nov 2025
PaiP: An Operational Aware Interactive Planner for Unknown Cabinet Environments
PaiP: An Operational Aware Interactive Planner for Unknown Cabinet Environments
Chengjin Wang
Zheng Yan
Yanmin Zhou
Runjie Shen
Zhipeng Wang
Bin Cheng
Bin He
284
0
0
15 Sep 2025
Bayesian Inference and Learning in Nonlinear Dynamical Systems: A Framework for Incorporating Explicit and Implicit Prior Knowledge
Bayesian Inference and Learning in Nonlinear Dynamical Systems: A Framework for Incorporating Explicit and Implicit Prior Knowledge
Björn Volkmann
Jan-Hendrik Ewering
Michael Meindl
Simon F. G. Ehlers
Thomas Seel
236
2
0
21 Aug 2025
Learning Lagrangian Interaction Dynamics with Sampling-Based Model Order Reduction
Learning Lagrangian Interaction Dynamics with Sampling-Based Model Order Reduction
Hrishikesh Viswanath
Yue Chang
Julius Berner
Julius Berner
Peter Yichen Chen
Aniket Bera
AI4CE
644
4
0
04 Jul 2024
Physically Consistent Online Inertial Adaptation for Humanoid
  Loco-manipulation
Physically Consistent Online Inertial Adaptation for Humanoid Loco-manipulationIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2024
James Foster
Stephen McCrory
Christian DeBuys
Sylvain Bertrand
Robert Griffin
280
3
0
13 May 2024
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and
  Compliant Impedance Control
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
198
8
0
27 May 2022
Gradient-Based Trajectory Optimization With Learned Dynamics
Gradient-Based Trajectory Optimization With Learned DynamicsIEEE International Conference on Robotics and Automation (ICRA), 2022
Bhavya Sukhija
Nathanael Kohler
Miguel Zamora
Simon Zimmermann
Sebastian Curi
Andreas Krause
Stelian Coros
373
16
0
09 Apr 2022
A Differentiable Newton-Euler Algorithm for Real-World Robotics
A Differentiable Newton-Euler Algorithm for Real-World Robotics
M. Lutter
Vallijah Subasri
Joe Watson
Frank Rudzicz
261
7
0
24 Oct 2021
Combining Physics and Deep Learning to learn Continuous-Time Dynamics
  Models
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models
M. Lutter
Jan Peters
PINNAI4CE
387
81
0
05 Oct 2021
1
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