Accessing hard-to-reach areas with Advanced and Breakthrough Innovation for reLiable In-situ characterization of a faciliTY

ongoing

The XS-ABILITY project aims to develop advanced robotic solutions by embedding various types of sensors to address remaining challenges in D&D as remote and mobile investigation of hard-to-access areas and difficult-to-measure radionuclides characterization, in innovative, safe and cost-effective ways. The project innovations are related to nuclear instrumentation (accurate and compact sensors), their integration onto robotic platforms as well as Data-driven (through IA algorithms) robot fleet management by considering accuracy, compactness, automation, and cost-efficient aspects. To achieve this goal, the consortium will develop all the necessary subcomponents. The demonstration will be achieved by integrating all the XS-ABILITY developments and testing (mainly in indoor environment) throughout use cases scenarios on real D&D facilities to assess in-situ performances and to acquire data in real experimental conditions. The consortium behind XS-ABILITY is a unique combination of cross-functional experts from nuclear instrumentation, robotic and artificial intelligence (AI) fields. It consists of 8 partners from 7 EU countries, including 4 RTO (CEA, IFE, VTT, SCK), 2 SME (CAEN, FLY), 1 industrial company (SIGM) and 1 association (DEV) representative of the whole value chain. Workshops with stakeholders will be organized in order to guide the XS-ABILITY consortium during the project’s main steps. The innovative solutions provided by the project will be exploited in Dismantling & Decommissioning, Nuclear Power Plant Monitoring & Maintenance market, sensor and CBRN-E defense markets. The enhanced knowledge generated will be disseminated to all these stakeholders according to the D&E&C measures defined. Furthermore, on the basis of the project demonstrations, guidelines covering multi-robot systems behaviour in indoor environment, data collection protocols as well as best practice harmonization will be developed showing how to effectively deploy in real D&D scenarios.