Descripción del proyecto
Estrategias asistidas por IA para mejorar la innovación en robótica de las pymes
Los robots forman parte de nuestro mundo real. Al implementar métodos de inteligencia artificial (IA) en robots, la naturaleza continua y dinámica del mundo físico plantea múltiples retos que van más allá de los ámbitos puramente digitales como, por ejemplo, la búsqueda en internet y las redes sociales. Para abordar estos retos, el proyecto financiado con fondos europeos VeriDream capitaliza los resultados de los proyectos de investigación DREAM y RobDream para desarrollar una estrategia de innovación doble para la IA en robótica. Su estrategia de innovación exhaustiva se centrará en lograr una alta preparación tecnológica en un conjunto de casos de uso en la logística de almacén de una empresa de nueva creación. Dicha estrategia promoverá una adopción generalizada de métodos de innovación eficaces en las pymes, lo que mejorará el potencial de innovación de las pymes en la IA para la robótica.
Objetivo
"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."
Ámbito científico
- 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
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-EIC-FETPROACT-2019
Régimen de financiación
RIA - Research and Innovation actionCoordinador
51147 Koln
Alemania