The current boom in e-commerce is challenging the logistics industry because shipment volumes are growing rapidly and online retail typically requires more logistical work per item compared to traditional brick and mortar retail. Manual picking is currently preferred when the number and variety of objects increases because automation becomes increasingly challenging. The specific need addressed in the project is the robot-based automatic collection of sets of small objects in weakly-engineered warehouses. The goal of the project is to address this need by the realisation of the innovation potential of the GOAL-Robots FET project technology applied to industry-relevant warehouse environments. In particular, the project will show that the “open-ended autonomous learning” technology developed within the GOAL-Robots project allows the creation of general-purpose robots for object-retrieval capable of autonomously learning to reach, grasp, and collect a large variety of objects, independently of their shape, rigidity, position, and orientation on shelves. This technological transfer will be achieved through three objectives: (a) the implementation of a demonstrator to show the potential of the technology to the target stakeholders; (b) the technology assessment of the GROW solution involving relevant stakeholders and partners for technology transfer, validating the innovation and its commercial viability; (c) the development of the business case and plan, the dissemination of the solution, and the preparation of communication material to reach potential stakeholders and support the implementation of an effective marketing strategy.

Drones in Europe are a rapidly developing sector with enterprises increasingly using drones for their business and the EU Legislator giving EASA rulemaking responsibility for civil drones of any mass. The common rules have been developed and will be enforced from January 2021. The performance of flight operations requires the compilation of a safety risk assessment document, in particular, the SORA (Specific Operations Risk Assessment) established for drone operations and endorsed by EASA. Compiling this assessment is expertise intensive and time-consuming. Currently, EUSC supports this operation with a web service called SAMWISE that, however, still requires the manual gathering of a large amount of information and the satisfaction of several constraints. The project aims to integrate into the web-solution built by EUSC the Artificial Intelligence (AI) technology generated by the FET-OPEN GOAL-Robots project, allowing the search of solutions in highly-nonlinear search spaces. The new technology from GOAL-Robots will support the semi-autonomous search of a solution to formulate flight plans based on an interactive interface, that meets the user’s requirements (flight start/arrival points, drone available, pilot licences, etc.), the SORA requirements, and the GIS characteristics of the involved overflown territory/airspace. The project will accomplish a systematic validation of the integrated system by testing the acceptability and usability of the proposed technology by selected stakeholders through the wide stakeholder network of the consortium. Moreover, business case refinement and focused dissemination activities will pave the way to the commercialisation of the produced service within the European drone market.

PILLAR-Robots aims at developing a new generation of robots endowed with a higher level of autonomy, that are able to determine their own goals and establish their own strategies, creatively building on the experience acquired during their lifetime to fulfil the desires of their human designers/users in real-life application use-cases brought to TRL5. To this end, the project will operationalize the concept of Purpose, drawn from the cognitive sciences, to increase the autonomy and domain independence of robots during autonomous learning and, at the same time, to lead them to acquire knowledge and skills that are actually relevant for operating in target real applications. In particular, the project will develop algorithms for the acquisition of purpose by the robot, ways to bias the perceptual, motivational and decision systems of the robots’ cognitive architectures towards purposes, and strategies for learning representations, skills and models that allow the execution of purpose-related deliberative and reactive decision processes. Given the aim of reaching TRL5, PILLAR-Robots will implement and validate demonstrators of purposeful lifelong open-ended autonomy using the resulting Purposeful Intrinsically Motivated Cognitive Architecture within three different application fields characterized by different types and levels of variability: Agri-food, Edutainment, and unstructured Industrial/retail. PILLAR-Robots will perform a complete evaluation of the possibilities and impacts of purposeful lifelong open-ended autonomy in these realms from an operational perspective, but also from a market-oriented (with significant productivity gains) and societal (socio-economic, ethical and regulatory) perspective. Engagement of industry and SME players is also expected in order to prepare the ground for further large-scale demonstration.

The last of four multi-year work plans will take the HBP to the end of its original incarnation as an EU Future and Emerging Technology Flagship. The plan is that the end of the Flagship will see the start of a new, enduring European scientific research infrastructure, EBRAINS, hopefully on the European Strategy Forum on Research Infrastructures (ESFRI) roadmap. The SGA3 work plan builds on the strong scientific foundations laid in the preceding phases, makes structural adaptations to profit from lessons learned along the way (e.g. transforming the previous Subprojects and Co-Design Projects into fewer, stronger, well-integrated Work Packages) and introduces new participants, with additional capabilities. The SGA3 work plan is built around improved integration and a sharpening of focus, to ensure a strong HBP legacy at the end of this last SGA. In previous phases, the HBP laid the foundation for empowering empirical and theoretical neuroscience to approaching the different spatial and temporal scales using state-of-the-art neuroinformatics, simulation, neuromorphic computing, neurorobotics, as well as high-performance analytics and computing. While these disciplines have been evolving for some years, we now see a convergence in this field and a dramatic speeding-up of progress. Data is driving a scientific revolution that relies heavily on computing to analyse data and to provide the results to the research community. Only with strong computer support, is it possible to translate information into knowledge, into a deeper understanding of brain organisation and diseases, and into technological innovation. In this respect, the underlying Fenix HPC and data e-infrastructure, co-designed with the HBP, will be key. The services offered by EBRAINS will be grouped in six Service Categories: SC1: Curated and shared data: EBRAINS FAIR data services - neuroscience data publishing SC2: Brain atlas services: navigate the brain in 3D - find, contribute and analyse brain data, based on location SC3: Brain modelling and simulation workflows: integrated tools to create and investigate models of the brain SC4: Closed loop AI and robotics workflows: design, test and implement robotic and AI solutions SC5: Medical Data Analytics SC6: Interactive workflows on HPC or NMC: Europe-wide access to scalable and interactive compute services Their users are to be supported with High-Level Support Teams and Vouchers, as well as Engagement and Facility Hubs located around Europe, at which additional services, unique equipment and compute infrastructure will be offered by local HBP Partners. Significant outcomes in relevant scientific communities are expected to materialise rapidly. Association with new Partnering Projects is still sought, along with wider international cooperation. The SGA3 objectives can be summarised as: 1) Establish a sustainable European scientific research infrastructure, EBRAINS, leading to an increased use and adoption of FAIR data, web-based analyses, model building, simulation, atlasing, and virtual experiments for brain research and brain-inspired sciences. 2) Provide a multi-level atlas of the human brain - the first of its kind that links microstructural detail and inter-subject variability. 3) Increase the capacity of neuroscientists for multiscale neural activity modelling of the human brain network. 4) Increase the availability of integrated multiscale data and computational models supporting brain states transitions, network complexity and cognitive functions. 5) Enhance real-world task performance through biologically plausible adaptive cognitive architectures running on neuromorphic hardware and a closed-loop Neurorobotics Platform. 6) Ensure that neuroscientific insights at the interface of neuro-inspired computing and technology are being translated into a benefit for patients with brain diseases. 7) Ensure an ethically and legally compliant infrastructure and promote embedding of Responsible Research and Innovation, a

Five leading European supercomputing centres are committed to develop, within their respective national programs and service portfolios, a set of services that will be federated across a consortium. The work will be undertaken by the following supercomputing centres, which form the High Performance Analytics and Computing (HPAC) Platform of the Human Brain Project (HBP): ▪ Barcelona Supercomputing Centre (BSC) in Spain, ▪ The Italian supercomputing centre CINECA, ▪ The Swiss National Supercomputing Centre CSCS, ▪ The Jülich Supercomputing Centre in Germany, and ▪ Commissariat à l'énergie atomique et aux énergies alternatives (CEA), France (joining in April 2018). The new consortium will be called Fenix and it aims at providing scalable compute and data services in a federated manner. The neuroscience community is of particular interest in this context and the HBP represents a prioritised driver for the Fenix infrastructure design and implementation. The Interactive Computing E-Infrastructure for the HBP (ICEI) project will realise key elements of this Fenix infrastructure that are targeted to meet the needs of the neuroscience community. The participating sites plan for cloud-like services that are compatible with the work cultures of scientific computing and data science. Specifically, this entails developing interactive supercomputing capabilities on the available extreme computing and data systems. Key features of the ICEI infrastructure are: ▪ Scalable compute resources; ▪ A federated data infrastructure; and ▪ Interactive Compute Services providing access to the federated data infrastructure as well as elastic access to the scalable compute resources. The ICEI e-infrastructure will be realised through a coordinated procurement of equipment and R&D services. Furthermore, significant additional parts of the infrastructure and R&D services will be realised within the ICEI project through in-kind contributions from the participating supercomputing centres.