Description du projet
Former une nouvelle génération d’ingénieurs en CAO
Les progrès récents des mathématiques, de la conception assistée par ordinateur (CAO) et de l’apprentissage automatique nous ont permis d’accomplir de nombreuses tâches concernant le multimédia et les données 2D, mais l’automatisation du traitement et de l’analyse de la géométrie 3D accuse de sérieux retards. L’industrie de la CAO a un besoin urgent de méthodes et d’outils avancés pour relever de nouveaux défis. Le projet GRAPES, financé par l’UE, vise à combler cette lacune grâce à un consortium multidisciplinaire composé de leaders dans leurs domaines respectifs. Le projet a pour ambition de former une nouvelle génération de scientifiques et d’ingénieurs européens pour créer des applications qui prendront en charge la simulation et la fabrication, l’hydrodynamique et la conception marine, la fabrication et l’impression 3D.
Objectif
GRAPES aims at considerably advancing the state of the art in Mathematics, Computer-Aided Design, and Machine Learning in order to promote game changing approaches for generating, optimising, and learning 3D shapes, along with a multisectoral training for young researchers. Recent advances in the above domains have solved numerous tasks concerning multimedia and 2D data. However, automation of 3D geometry processing and analysis lags severely behind, despite their importance in science, technology and everyday life, and the well-understood underlying mathematical principles. The CAD industry, although well established for more than 20 years, urgently requires advanced methods and tools for addressing new challenges.
The scientific goal of GRAPES is to bridge this gap based on a multidisciplinary consortium composed of leaders in their respective fields. Top-notch research is also instrumental in forming the new generation of European scientists and engineers. Their disciplines span the spectrum from Computational Mathematics, Numerical Analysis, and Algorithm Design, up to Geometric Modelling, Shape Optimisation, and Deep Learning. This allows the 15 PhD candidates to follow either a theoretical or an applied track and to gain knowledge from both research and innovation through a nexus of intersectoral secondments and Network-wide workshops.
Horizontally, our results lead to open-source, prototype implementations, software integrated into commercial libraries as well as open benchmark datasets. These are indispensable for dissemination and training but also to promote innovation and technology transfer. Innovation relies on the active participation of SMEs, either as a beneficiary hosting an ESR or as associate partners hosting secondments. Concrete applications include simulation and fabrication, hydrodynamics and marine design, manufacturing and 3D printing, retrieval and mining, reconstruction and visualisation, urban planning and autonomous driving.
Champ scientifique
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesmathematicspure mathematicsgeometry
- engineering and technologymechanical engineeringmanufacturing engineeringadditive manufacturing
- natural sciencesmathematicsapplied mathematicsnumerical analysis
Mots‑clés
Programme(s)
Régime de financement
MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)Coordinateur
151 25 Maroussi
Grèce