The overall objective of the project is to create a Centre of Excellence for Autonomous and Cooperative Robotic Systems in Croatia (ACROSS CoE), which will be at the forefront of research and innovation of novel methodologies and advanced engineering approaches in the targeted domains. ACROSS CoE will be created and run as a long-term joint venture between the UNIZG-FER  ̵ University of Zagreb Faculty of Electrical Engineering and Computing, the KTH  ̵ Royal Institute of Technology, and the ICENT  ̵ Innovation Centre Nikola Tesla. To achieve the overall objective, the proposal focuses on long-term objectives for Teaming Phase 2 and on one-year objective for Teaming Phase 1. Long-term objectives of the Phase 2 and beyond are: (i) Reinforcing scientific capacity and innovation performances in autonomous and cooperative robotic systems, (ii) Increasing scientific visibility and reputation at international level, and (iii) Improving responses to socioeconomic needs of Croatia. ACROSS CoE will achieve these objectives by striving for high quality research, in line with international standards of excellence, and by directing its research towards areas serving the technological needs identified by the Croatian Smart Specialisation Strategy. The ultimate objective of the Phase 1 is to produce an extensive, detailed, and robust Business Plan for ACROSS CoE; and to achieve this, the plan will be built upon (i) Assessment of the existing ACROSS ecosystem and (ii) Development of roadmaps for achieving ACROSS CoE excellence. The ACROSS project is relevant to the work programme since the main goal is to create a new Centre of Excellence in Croatia, a low R&I performing country, by building upon partnership with KTH, a world leading scientific and innovation institution. Creation of the ACROSS CoE will help Croatia in attaining a competitive position in the global value chains, thus also contributing to Europe’s competitiveness and its ability to address future societal challenges.

KTH – Royal Institute of Technology, Innovation Centre Nikola Tesla

The project will establish a Pan-European ecosystem of Competence Centres (CCs) supported by Logistics for Manufacturing SMEs (L4MS) marketplace. The objective is to facilitate the take up of logistics automation by manufacturing SMEs across Europe by acting as a broker between SMEs who seek solutions and financing and the CCs and their ecosystem who are interested to provide consulting, solutions, best practices and areas for demonstration and experimentation. Central to the ecosystem is a marketplace which provides access to support services with tools and online helpdesk thus providing a single point of access to the SMEs. Six strategically located CCs and several regional associations, Digital Innovation Hubs and consulting agencies will establish the ecosystem.  An Open Platform for Innovations in Logistics (OPIL) will be developed to provide latest navigation, localization, mapping and traffic management services and IOT infrastructure for logistics automation. Cross border Application Experiments (AE) will be used to deploy OPIL for small and flexible logistics solutions requiring no infrastructure change, no production downtime and no in-house expertise, making investment in logistics automation attractive for manufacturing SMEs. AEs will be developed with the infrastructure of already participating and new CCs. Results from AEs will be used to advance the OPIL and enrich L4MS marketplace with business success stories. The business sustainability of the L4MS marketplace as a potential start-up and its ecosystem comprising of CCs, regional DIHs, industry associations and technology suppliers will be the focus of the work, adopting the already developed best practice in I4MS phase 2.

Teknologian tutkimuskeskus VTT Oy (coordinator), Asociatia Producatorilor De Mobila Din Romania, Automatismos Y Sistemas De Transporte Interno, S.A.U., Chemi-Pharm AS, Technologiko Panepistimio Kyprou, European Dynamics Advanced Systems of Telecommunications Informatics and
Telematics Sa, Engino.net Ltd., Fundingbox Accelerator Sp Zoo, Hermia Yrityskehitys Oy, IMECC OÜ, Fraunhofer Gesellschaft Zur Foerderung Der Angewandten Forschung E.V., Kine Robot Solutions Oy, Lithuanian robotics association, MURAPLAST d.o.o., Fundacio Barcelona Mobile World Capital Foundation, Odense Robotics, Pannon Gazdasagi Halozat Egyesulet, Politecnico di Milano, Visual Components Oy

The Centre of Research Excellence for Data Science and Advanced Cooperative Systems is the first centre of excellence in the field of technical sciences in Croatia. The Centre brings together researches from thirteen renowned organizations, including eleven higher education institutions from Zagreb, Split, Rijeka, Osijek and Dubrovnik, as well as the Ruđer Bošković Institute and the company Ericsson Nikola Tesla. The Centre comprises two research units: the Research Unit for Data Science (DATASCIENCE) and the Research Unit for Cooperative Systems (ACROSS). Find out more about the participating organizations here.

The vision of the centre is to establish itself as the leader in research and development of new methods and advanced engineering approaches related to data science and cooperative systems.

The mission of the centre is to advance Croatian science and strengthen its inclusion in the European Research Area, in particular by promoting the participation in EU and other international research programmes. The centre fosters cooperation between the academic community and the public sector in the specific research areas that are in the focus of the Centre.

The goal of the SafeTRAM project is to develop an innovative system which would increase  traffic safety by implementing safety functions for urban rail traffic, thus lowering the number of accidents causing great material damage and human casualties. Electric trams use up to five times less energy than an automobile, do not pollute the environment and have a number of ecological advantages with respect to road traffic, which is responsible for 95% of traffic gas emissions. In the near future, systems like  SafeTRAM will be a key element of autonomous vehicles which is one of the final goals of the modern society.

The goal of the DUV-NRKBE project is to develop a remotely controlled vehicle for acting in extreme Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNe) conditions. It will be a unique system on continuous tracks which will give the end user a capability to work in extreme heat zones - in conditions where a human could not survive, along with an array of tools and sensors with which it will perform various missions and drastically shorten the time and intensity of accidents. Furhtermore, besides remote control one of the goals of the project is to enhance the vehicle with autonomous capabilities such as autonomous patrolling, laser cartography etc.

The main objective of the RoboCom++ project is to lay the foundation for a future global interdisciplinary research programme (e.g., a FET-Flagship project) on a new science-based transformative robotics. RoboCom++ will gather the community and organise the knowledge necessary to rethink the design principles and fabrication technologies of future robots. RoboCom++ will aim at developing the cooperative robots (or Companion Robots) of the year 2030, by fostering a deeply multidisciplinary, transnational and federated effort. The RoboCom++ community will pursue these ambitious objectives by cooperating along three main lines of action: 1) building the community and the tools for research reproducibility (benchmarks, metrics, data sharing protocols, test platforms, standards); 2) proof-of-concept research pilots; and 3) defining the long-term S&T roadmap, competitiveness strategy, governing and financing structure, and the ethical, legal, economic and social framework of a future FET Flagship.

University of Zagreb Faculty of Electrical Engineering and Computing (LARICS, LABUST), Scuola Superiore Sant’Anna/The BioRobotics Institute (coordinator Paolo Dario), Université Libre de Bruxelles, Tallinn University of Technology, Centre National de la Recherche Scientifique, Laboratoire National de Métrologie et d’Essais, Istituto Italiano di Tecnologia, Riga Technical University, National Institute for R&D in Microtechnologies, Universitatea Transilvania Brasov, Ecole Polytechnique Fédérale de Lausanne, Middle East Technical University, University Carlos III of Madrid, Weizmann Institute of Science, Czech Technical University, Czech Institute of Informatics, Robotics and Cybernetic, Vrije Universiteit Brussel, National Technical University of Athens,Universitat Politecinca de Catalunya, Cognitive Systems Research Institute, Technical University of Kosice, University of Plymouth, University of Twente, Consorzio Nazionale delle Ricerche/ Istituto di Studi sui Sistemi Intelligenti per l'Automazione

According to the recent report by the International Robotics Federation (IFR, www.ifr.org/industrial-robots/statistics) linking the real-life factory with virtual reality will play an increasingly important role in global manufacturing. Furthermore, it is also stated that global competition requires continued modernization of production facilities and that growing consumer markets require expansion of production capacities. For example, the European market for e-commerce is growing rapidly, with more than 18,6% just in the year 2015. With the growing markets, the need for larger warehouses and their automation will only increase. To advance the position of the European manufacturing and trade sector, a new automation paradigm should be implemented to ensure their efficient operation. According to the same IFR report, robots and human-robot collaboration will play an important role in the upcoming years. And indeed, robots are nowadays able to successfully solve complicated tasks like autonomous transport and autonomous manipulation. Yet, when it comes to human-robot collaboration, cooperation, or generally speaking coexistence, the main barrier is safety as it typically affects performance and costs of the robot system. Current automation solutions in manufacturing and logistics is based on strict separation of humans and robots. In order to enable coexistence of humans and robots in the same environment, one of the prerequisites is to know the location of the humans in the warehouse and predict their intentions. This project aims to overcome this issue by developing methods for human indoor localization and intention prediction based on wearable sensors. This approach also enables solving the project problem with minimal changes to the environment. Furthermore, wearable sensors can also be used to provide online information to workers, e.g., via an augmented reality (AR) device, thus even further increasing the working efficiency and link the real-life factory with virtual reality.

Over the last several decades, robotics has been a key technology for achieving high productivity and industrial competitiveness. Recently, robotics has begun expanding intensively outside of industrial settings, thus bringing robots closer and closer to humans. The main robotics challenges in the coming decade will be to develop robotic systems that can safely cooperate with humans in arbitrary settings and that are capable of autonomously performing complex tasks in human environments.

One of the main prerequisites for robot autonomous operation in unknown environments populated by humans or other robots is to perform simultaneous localization and mapping (SLAM) so that the robot can infer its position and relate it to other objects of interest. The main focus of the cloudSLAM project is to develop algorithms for solving the SLAM problem such that robots can operate reliably even in highly dynamic environments. This will be achieved through a mathematical framework accurately describing the non-Euclidean geometry of objects moving in space and through robot cooperation via a cloud based service.

The methodology of the proposed project will be grounded in a novel estimation approach based on the recently developed Kalman filter on Lie groups. We will estimate the state of the robot and the tracked objects in six degrees of freedom by representing the state with the special Euclidean group (SE3) and performing filtering directly on the introduced group. This way, the non-Euclidean nature of the orientation components will be intrinsically respected, while their uncertainty will be correctly coupled with the uncertainty of the Euclidean members of the SE3 group through the joint covariance matrix.Since the idea of cloudSLAM is to exploit the moving objects for enhancing the SLAM performance, we will develop algorithms for multiple object detection and tracking using Lie groups and random finite sets theory. This result will then serve as an input to a dynamic SLAM algorithm. The dynamic SLAM will also be based on Lie groups, where we will develop an algorithm based on the exactly sparse delayed state filter so as to keep the computational complexity reasonable. Finally, all the information will be shared by multiple agents through a common cloud-based service, thus enabling robots which have just started operating to immediately exploit the experience of veteran team members. The proposed framework will be tested in coordinated exploration scenarios involving heterogeneous teams moving in dynamic environments, including aerial and ground vehicles and human operators.

The European manufacturing industry needs competitive solutions to keep global leadership in products and services. Exploiting synergies across application experts, technology suppliers, system integrators and service providers will speed up the process of bringing innovative technologies from research labs to industrial end-users. As an enabler in this context, the EuRoC initiative proposes to launch three industry-relevant challenges:

• Reconfigurable Interactive Manufacturing Cell (RIMC),
• Shop Floor Logistics and Manipulation (SFLM),
• Plant Servicing and Inspection (PSI).    

It aims at sharpening the focus of European manufacturing through a number of application experiments, while adopting an innovative approach which ensures comparative performance evaluation. Each challenge is launched via an open call and is structured in 3 stages.

45 Contestants are selected using a challenge in a simulation environment: the low barrier of entry allows new players to compete with established robotics teams. Matching up the best Contestants with industrial end users, 15 Challenger teams are admitted to the second stage, where the typical team is formed by research experts, technology suppliers, system integrators, plus end users.

Teams are required to benchmark use cases on standard robotic platforms empowered by this consortium. After a mid-term evaluation with public competition, the teams advance to showcasing the use case in a realistic environment. After an open judging process, 6 Challenge Finalists are admitted to run pilot experiments in a real environment at end-user sites to determine the final EuRoC Winner.

A number of challenge advisors and independent experts decide about access to the subsequent stages. A challenge-based approach with multiple stages of increasing complexity and financial support for competing teams will level the playing field for new contestants, attract new developers and new end users toward customisable robot applications, and provide sustainable solutions to carry out future challenges.

Europeans need to save energy. Mayor energy savings can be achieved by preventing heating and air conditioning losses due to thermal bridging, air leakage, discontinuous insulation, air infiltration, and structural defects in buildings, as much as 39 % and 32 % of the energy used is required for heating, cooling and ventilation in residential and commercial buildings, respectively. To create a methodology for cost effective renovation of existing buildings it is essential to have detailed semantic thermal 3D models thereof.

The focus of this project is to extract precise digital models from existing buildings. To ensure that data acquisition is carried out in a complete, accurate and efficient way, novel methods are developed within this project to explore the environment autonomously with mobile robots through active exploration. The robotic platforms are equipped with non-destructive sensors such as 3D laser scanners and thermal cameras for data acquisition. The resulting information is put into a building information model (BIM), i.e., digital representations of physical and functional characteristics of the building. The BIM forms the basis for guiding the user for maintenance and renovation actions.

Advanced technologies in power systems and railway vehicles (FER-KIET) project has the main goal of creation of new knowledge and technologies with commercial application to power systems and railway vehicles. Project is performed as collaboration between Faculty of Electrical Engineering and Computing and industrial partner Končar - Electrical Engineering Institute (KIET).

The VISTA project employs a group of researchers from the University of Zagreb Faculty of Electrical Engineering and Computing and from the Faculty of Transport and Traffic Sciences. As part of this project the researchers will conduct research followed by the development of computer vision-based methods with intended use in road traffic. Vision is the most important sense used for driving and therefore computer vision algorithms are the most critical for Advanced Driver Assistance System (ADAS).

Research and development activities constitute one component of VISTA project in which the focus will be on industrial research and development, feasibility check and prototype development and testing of advanced computer vision systems for safe traffic. The second component of the project consists of networking activities with companies in the Croatian automotive sector through which new possibilities and potentials will be presented, and the process of defining new challenging application of computer vision in traffic will be started.

More than 40% of Europe’s energy consumption is related to buildings, as
estimated by the Commission of the European Communities. Technology will help to exploit a huge saving potential, by automatically generating compact, three-dimensional, and annotated representation of indoor and urban environments. Regular, automatic surveying and monitoring provides the basis for reducing energy losses. By combining the emerging technologies of thermal imaging and terrestrial 3D laser scanning, the prototype system records as-built data of buildings related to energy
issues. Clever exploration and next-best-view-planning strategies with advanced sensors are needed to acquire snapshots of temperature distributions. Regular smart metering combined with advanced visualizations will enable end-users to carry out appropriate measures for saving energy.

The focus of this project is to combine several technologies, namely state of the art thermography, 3D laser scanning, computer vision and mobile robotics. Novel algorithms are used to tie these technologies together and to create 3D computer models containing multi-modal data. These
can be used to inform the user or customer about the temperature distribution and the heat flow in environments and to automate the detection of energy losses. 

The main and general goal of this project is to create scientifically grounded fundamentals for starting development, design, production and application of autonomous mobile robots and vehicles in Croatia. Given that, it would also include Croatia in the most perspective industrial branch of the 21th century. Specific goal of suggested research is the development of general functional system library for control which could be easily applied during the development of autonomous mobile robots and vehicles of different constructions and applications in unknown and dynamic environments.