Description du projet
Des stratégies assistées par IA pour améliorer l’innovation des PME dans la robotique
Les robots opèrent dans le monde réel. Quand on déploie des méthodes d’intelligence artificielle (IA) sur les robots, la nature continue et dynamique du monde physique pose de nombreux défis qu’on ne rencontre pas dans des domaines purement numériques comme celui des recherches sur Internet et les réseaux sociaux. Pour relever ces défis, le projet VeriDream, financé par l’UE, s’appuie sur les projets de recherche DREAM et RobDream afin d’appliquer une stratégie d’innovation double pour l’IA dans la robotique. Sa stratégie d’innovation profonde tentera de parvenir à un niveau élevé de maturité technologique dans un ensemble de cas d’utilisation dans une start-up de logistique de stockage. Sa vaste stratégie d’innovation promouvra une plus large adoption de méthodes d’innovation efficaces dans les PME, améliorant ainsi le potentiel d’innovation des PME dans l’IA destinée à la robotique.
Objectif
"Advances in artificial intelligence (AI) are changing the business models of many companies, and creating entirely new ones. But whereas the general public associates AI predominantly with autonomous and humanoid robots, the economic impact of AI on robotics has been very limited in comparison to domains which were digitised from the start, such as Internet search and social networks. This is because acting in the physical world raises many challenges related to the variability of the real world, its continuous and dynamic nature, as well as the consequences of suboptimal or erroneous behaviour.
To address these challenges, VeriDream proposes a two-fold research and innovation strategy for AI in robotics, based on the generalisation and robustification of AI methods developed by the three research partners in two previous H2020 projects, DREAM and RobDREAM. The deep innovation strategy aims at high TRL on a set of use cases from the specific domain of warehouse logistics at the start-up Magazino. The broad innovation strategy, pursued by Synesis and GoodAI, aims at fostering a broader uptake of DREAM methods in SMEs, also beyond the project, and even beyond robotics. VeriDream thus aim at both concrete high-TRL innovation success stories, as well as providing experience and templates for innovation from which other European SMEs may profit.
In both strategies, our methodology is based on ""closing the innovation loop"". This means that research on AI methods is driven less by performance on static benchmarks, but rather by general methodological requirements derived from the performance on multiple industrial use cases. This will require scientific advances in state representation learning, failure discovery and resolution, and continual learning. The generalisation and robustification of DREAM methods that results from this research will have a substantial impact on the innovation potential of these methods. Demonstrating this is VeriDream's mission."
Champ scientifique
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesinternet
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robots
- social scienceseconomics and businessbusiness and managementbusiness models
Mots‑clés
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
51147 Koln
Allemagne