Physics-informed Neural Networks to Model and Control Robots: a Theoretical and Experimental Investigation

9 May 2023

Papers citing "Physics-informed Neural Networks to Model and Control Robots: a Theoretical and Experimental Investigation"

4 / 4 papers shown

Title
Learning Low-Dimensional Strain Models of Soft Robots by Looking at the Evolution of Their Shape with Application to Model-Based Control Ricardo Valadas Maximilian Stolzle Jingyue Liu Cosimo Della Santina 60 1 0 21 Feb 2025
Metamizer: a versatile neural optimizer for fast and accurate physics simulations Nils Wandel Stefan Schulz Reinhard Klein PINN AI4CE 46 0 0 10 Oct 2024
Neural Autoencoder-Based Structure-Preserving Model Order Reduction and Control Design for High-Dimensional Physical Systems Marco Lepri Davide Bacciu Cosimo Della Santina AI4CE 35 8 0 11 Dec 2023
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 33 39 0 05 Oct 2021