Friction driven synthesis of 3D surfaces

The goal of this project will be to synthesize 3D surfaces with roughness that match desired friction properties.
A small dataset of highly detailed microgeometry scans and their corresponding friction coefficients will be assembled and then used to learn a generative model that is parameterized by the friction coefficient. The model will be used to synthesize novel surface geometry for pairs of surfaces, which will be integrated into interactive computer graphics applications and also used in the context of computational fabrication design. 
 

Connaissances requises

- Bachelors’s degree in computer science, software engineering or a related field
- Knowledge of computer graphics and physics simulation
- Knowledge of supervised learning and generative models (e.g. GANs) and numerical optimization
- Strong programming skills in C++ or Python
 

Programme d'études visé

Maîtrise avec mémoire

Domaines de recherche

Technologies de l'information et des communications

Financement

A scholarship will be provided from the professor.

Autres informations

Date de début : 2021-09-01

Personne à contacter

Sheldon Andrews | sheldon.andrews@etsmtl.ca