Metrological Evaluation and Testing of Robots in International CompetitionS

ended

The METRICS project will organise challenge-led robotics competitions inThe METRICS project will organise challenge-led robotics competitions in the four Priority Areas (PAs) identified in the topic ICT-09-2019-2020: Healthcare, Inspection and Maintenance, Agri-Food, and Agile Production. METRICS is designed to organise competitions as reproducible and objective evaluation campaigns and aims to structure in a sustainable way the European robotics and Artificial Intelligence (AI) community around the four PAs. In order to assess the reliability of the different competing robots in a rigorous and unbiased way, METRICS will develop an evaluation framework based on metrological principles. For each competition, METRICS will organize 3 field evaluation campaigns (in physical environments) and 3 cascade evaluation campaigns (on datasets) to engage with the AI community. The competitions are designed to draw attention from the entire economic sector, the academia and Digital Innovation Hubs (DIH) in Europe, while stimulating public engagement. Indeed, METRICS will implement a dedicated strategy to mobilize external partners and sponsors to support the organization of the competitions or ensure their industrial relevance. A specific outreach strategy will be developed to promote robotics systems towards the general public and ensure the compliance of robots with ethical and socio-economic principles. METRICS brings together 17 partners, all expert in robotics competition and metrology, with highly complementary testing facilities and networks in the four PAs. This experienced consortium will ensure that METRICS benefits from the feedback of past and current competitions and projects and is highly complementary with European initiatives and networks (e.g. DIH). Thus, METRICS will contribute to structuring a sustainable network of European robotics stakeholders in the four PAs through the organisation of industry-relevant competitions based on robust evaluations methods.