Encoding Physical Constraints in Differentiable Newton-Euler Algorithm

Encoding Physical Constraints in Differentiable Newton-Euler Algorithm

24 January 2020

Giovanni Sutanto

Mustafa Mukadam

Gaurav Sukhatme

Franziska Meier

Papers citing "Encoding Physical Constraints in Differentiable Newton-Euler Algorithm"

9 / 9 papers shown

Title
Learning Object Properties Using Robot Proprioception via Differentiable Robot-Object Interaction Julius Berner Chao Liu Pingchuan Ma John Eastman Daniela Rus Dylan Randle Yuri Ivanov Wojciech Matusik 71 0 0 04 Oct 2024
Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization Benjamin Alt Claudius Kienle Darko Katic Rainer Jäkel Michael Beetz 72 1 0 13 Sep 2024
Structured Mechanical Models for Robot Learning and Control Jayesh K. Gupta Kunal Menda Zachary Manchester Mykel J. Kochenderfer DRL 54 35 0 21 Apr 2020
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M. Lutter Christian Ritter Jan Peters PINN AI4CE 58 378 0 10 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 118 894 0 04 Jun 2019
A General Framework for Structured Learning of Mechanical Systems Jayesh K. Gupta Kunal Menda Zachary Manchester Mykel J. Kochenderfer AI4CE 53 35 0 22 Feb 2019
A New Data Source for Inverse Dynamics Learning Daniel Kappler Franziska Meier Nathan D. Ratliff S. Schaal 49 19 0 06 Oct 2017
Linear Matrix Inequalities for Physically-Consistent Inertial Parameter Identification: A Statistical Perspective on the Mass Distribution Patrick M. Wensing Sangbae Kim Jean-Jacques E. Slotine 65 122 0 16 Jan 2017
Identification of Fully Physical Consistent Inertial Parameters using Optimization on Manifolds Silvio Traversaro Stanislas Brossette Adrien Escande F. Nori 66 60 0 27 Oct 2016

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