[en] A data-driven, probabilistic, computational framework will be developed that provides a deformable solid with the sense of 'touch', so that it can detect the shape and mechanical behaviour of its environment. The framework will rely on three modules: a mechanical model to simulate the contact between the deformable solid and its environment, a machine learning module to rapidly emulate the mechanical simulations, and a probabilistic framework to identify the shape and mechanical behaviour of the solid’s environment.
Disciplines :
Materials science & engineering
Author, co-author :
Hurtado Cathalifaud, Diego Rene ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
External co-authors :
no
Language :
English
Title :
A data-driven computational framework to provide deformable solids with the sense of touch
Publication date :
21 May 2021
Number of pages :
A1
Event name :
DTU DRIVEN Colloquium
Event organizer :
Andreas Zilian
Event place :
Esch-sur-Alzette, Luxembourg
Event date :
21-05-2021
Audience :
International
Focus Area :
Computational Sciences
FnR Project :
FNR12252781 - Data-driven Computational Modelling And Applications, 2017 (01/09/2018-28/02/2025) - Andreas Zilian
