Projet TRAIL (Horizon Europe, appel à projets 2021)
Action : Doctoral Networks
Panel : Information Science and Engineering
Statut du projet : SIGNED

TRAIL strategically focuses on a novel, highly interdisciplinary and cross-sectorial research and training programme for a better understanding of transparency in deep learning, artificial intelligence and robotics systems. In order to train a new generation of Doctoral Candidates to become experts in the design and implementation of transparent, interpretable neural systems and robots, we have built a highly interdisciplinary consortium, containing expert partners with long-standing expertise in cutting-edge artificial intelligence and robotics, including deep neural networks, computer science, mathematics, social robotics, human-robot interaction and psychology. In order to build transparent robotic systems, these new ESR researchers need to learn about the theory and practice of the principles of (1) internal decision understanding and (2) external transparent behaviour. Since the ability to interpret complex robotic systems needs highly interdisciplinary knowledge, we will start, on the decision level, to interpret deep neural learning and analyse what knowledge can be efficiently extracted. At the same time, on the behaviour level, the disciplines of human-robot interaction and psychology will be key in order to understand how to present the extracted knowledge as behaviour in an intuitive and natural way to a human user to integrate the robot into a cooperative human-robot interaction. A scaffolded training curriculum will guarantee that the ESRs have not only a deep understanding of both research areas, but experience optimal skill training to be fully prepared for a successful research career in academia and industry. The importance and need of this research for the industry is clearly visible with the full commitment of 7 leading European and world-wide-operating robotics companies that together cover the majority of Europe’s robot market and a broad spectrum of AI applications.

Mots clés : neural networks, explainable ai, neural robotics, transparent artificial intelligence systems

Participants :
- Centre national de la recherche scientifique (France) — Partner, beneficiary, Recherche, subvention : 282693.6 €
- Université de Padoue (Italie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 259437.6 €
- Université de Manchester (Royaume-Uni) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Seed cognitiva - robotics innovation lda (Portugal) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Université Comenius de Bratislava (Slovaquie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 235814.4 €
- Université d'Hambourg (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 521078.4 €
- IT+Robotics (Italy) (Italie) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Conseil supérieur de la recherche scientifique (Espagne) — Partner, beneficiary, Recherche, subvention : 251971.2 €
- Institut national des sciences appliquées de Toulouse (France) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Naples - Frédéric-II (Italie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 259437.6 €
- Honda (Germany) (Allemagne) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Center of Applied Aeronautical Research (Allemagne) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- United robotics group gmbh (Allemagne) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Aldebaran (France) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Pal robotics slu (Espagne) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 251971.2 €