Projektbeschreibung
Mit neuen Strategien die KI-Robotertechnikinnovation in kleinen und mittleren Unternehmen fördern
Roboter agieren bereits in der realen Welt. Wenn bei ihnen Methoden der künstlichen Intelligenz (KI) zum Einsatz kommen, birgt die kontinuierliche und dynamische Natur der physischen Welt viele Herausforderungen, die in rein digitalen Bereichen wie Internetrecherchen und sozialen Netzwerken nicht auftreten. Um diese Herausforderungen zu meistern, baut das EU-finanzierte Projekt VeriDream auf den Forschungsprojekten DREAM und RobDream auf, um eine in zwei Richtungen abzielende Innovationsstrategie für künstliche Intelligenz in der Robotertechnik zu verfolgen. Seine in die Tiefe gehende Innovationsstrategie verfolgt das Ziel, in einigen Anwendungsfällen eines Lagerlogistik-Start-up-Unternehmens einen hohen Technologie-Reifegrad zu erreichen. Seine breit angelegte Innovationsstrategie wird eine breitere Akzeptanz effektiver Innovationsmethoden in kleinen und mittleren Unternehmen fördern und auf diese Weise deren Innovationspotenzial in Bezug auf künstliche Intelligenz in der Robotertechnik erhöhen.
Ziel
"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."
Wissenschaftliches Gebiet
- 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
Schlüsselbegriffe
Programm/Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-EIC-FETPROACT-2019
Finanzierungsplan
RIA - Research and Innovation actionKoordinator
51147 Koln
Deutschland