Bremen, Germany

The German Research Center for Artificial Intelligence is one of the world's largest nonprofit contract research institutes in the field of innovative software technology based on artificial intelligence methods. DFKI was founded in 1988, and has facilities in the German cities of Kaiserslautern, Saarbrücken, Bremen and Berlin.DFKI shareholders include Microsoft, SAP, BMW and Daimler. The current directors are Prof. Wolfgang Wahlster and Dr. Walter G. Olthoff . Wikipedia.


Time filter

Source Type

Grant
Agency: European Commission | Branch: H2020 | Program: IA | Phase: FoF-09-2015 | Award Amount: 9.52M | Year: 2015

BEinCPPS Innovation Action aims to integrate and experiment a CPS-oriented Future Internet-based machine-factory-cloud service platform firstly intensively in five selected Smart Specialization Strategy Vanguard regions (Lombardia in Italy, Euskadi in Spain, Baden Wuertemberg in Germany, Norte in Portugal, Rhone Alpes in France), afterwards extensively in all European regions, by involving local competence centers and manufacturing SMEs. The final aim of this Innovation Action is to dramatically improve the adoption of CPPSs all over Europe by means of the creation, nurturing and flourishing of CPS-driven regional innovation ecosystems, made of competence centers, manufacturing enterprises and IT SMEs. The BE in CPPS project stems upon three distinct pillars: A FI-based three-layered (machine-factory-cloud) open source platforms federation, integrated from state-of-the-art R&I advances in the fields of Internet of Things, Future Internet and CPS / Smart Systems and able to bi-directionally interoperate data pertaining to the machine, the factory and the cloud levels. A pan-European SME-oriented experimentation ecosystem. In a first phase of the project, the five Champions will provide requirements to the platforms integrators. In a second phase, an Open Call for IT SMEs developers (applications experiments) will award 10 third parties. In a final third phase, the extended platform will be instantiated and deployed in additional 10 third parties equipment experiment SMEs. A well-founded method and toolbox for Innovation management, where an existing TRL-based methodology for KETs technology transfer will be enriched by a CPPS certification, education and training programme for young talents and experienced blue collar workers and by a well-founded three-fold (objectives-variables-indicators) method for results assessment and evaluation.


Grant
Agency: European Commission | Branch: H2020 | Program: IA | Phase: FOF-02-2016 | Award Amount: 7.26M | Year: 2016

COROMA project proposes to develop a cognitively enhanced robot that can execute multiple tasks for the manufacturing of metal and composite parts. COROMA will therefore provide the flexibility that European metalworking and advanced material manufacturing companies require to compete in the rapidly evolving global market. The main output of COROMA project will be a modular robotic system that will perform multitude of different manufacturing tasks in an autonomous way to adapt to the production requirements. The robot will be capable of performing drilling, trimming, deburring, polishing, sanding, non-destructive inspection and adaptive fixturing operations. Using a simple interface the robot will receive basic commands that require a minimum programming effort from the human operator. The robot will autonomously navigate in the workshop and will automatically perceive the manufacturing scene and locate the part that must be manufactured and even handle some of the required tools. Learning from previous experiences during displacement, tool grasping, part localisation and the manufacturing process itself, the robot will improve its performance. It will be able to interact with other machines in the shop floor and to work on a part even while other manufacturing operations are being performed by these other machines. Safe human-robot and machine-robot collaborations will be paramount and the robot will automatically react to the presence of both humans and other machines. The modularity of the COROMA robot will permit to customize it to meet specific requirements from different manufacturing companies. These challenges require a project consortium where the latest robotic technologies meet knowledge from manufacturing experts, including both industry and academia. COROMA project consortium presents a perfect balance between manufacturing and robotics sectors players.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: FETHPC-1-2014 | Award Amount: 7.88M | Year: 2015

Worldwide data volumes are exploding and islands of storage remote from compute will not scale. We will demonstrate the first instance of intelligent data storage, uniting data processing and storage as two sides of the same rich computational model. This will enable sophisticated, intention-aware data processing to be integrated within a storage systems infrastructure, combined with the potential for Exabyte scale deployment in future generations of extreme scale HPC systems. Enabling only the salient data to flow in and out of compute nodes, from a sea of devices spanning next generation solid state to low performance disc we enable a vision of a new model of highly efficient and effective HPC and Big Data demonstrated through the SAGE project. Objectives - Provide a next-generation multi-tiered object-based data storage system (hardware and enabling software) supporting future-generation multi-tier persistent storage media supporting integral computational capability, within a hierarchy. - Significantly improve overall scientific output through advancements in systemic data access performance and drastically reduced data movements. - Provides a roadmap of technologies supporting data access for both Exascale/Exabyte and High Performance Data Analytics. - Provide programming models, access methods and support tools validating their usability, including Big-Data access and analysis methods - Co-Designing and validating on a smaller representative system with earth sciences, meteorology, clean energy, and physics communities - Projecting suitability for extreme scaling through simulation based on evaluation results. Call Alignment: We address storage data access with optimised systems for converged Big Data and HPC use, in a co-design process with scientific partners and applications from many domains. System effectiveness and power efficiency are dramatically improved through minimized data transfer, with extreme scaling and resilience.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: COMPET-4-2016 | Award Amount: 1.00M | Year: 2016

The FACILITATORS goals are: -To Enable the highest possible level of validation of the common building blocks (developed by concurring operational grants) in the most relevant environment by adapting and providing the best available European test facilities, as well as -To Guarantee coherence among the different test facilities and among the building blocks by establishing common implementation/validation scenarios (to be reproduced during ground testing) and common interfaces with the test facilities. More concretely, in order to achieve such goals, the objectives of our project are to: 1. Analyse and identify the validation needs of each building block 2. Identify and adapt the already-existing top-notch European test platforms that will form a federation of facilities which will host the validation tests of ALL building blocks in BOTH demonstration scenarios 3. Characterize the facilities and provide representative datasets to support the design and development of the building blocks, carried out by concurring operational grants (OGs) 4. Ensure coherence among the different building blocks by agreeing on common demonstration scenarios that will be carried out within the federation of facilities, as well as by preparing common interfaces in coordination with the SRC board and the other parallel OGs 5. Provide easy access to the identified facilities, and ensure their availability when the building blocks will be tested 6. Assist the building blocks validation tests execution by providing monitoring and measuring means, as well as giving on-site support. The Federation of Facilities concept lies in a network of coordinated, complementary and exchangeable state-of-the-art facilities across Europe, identified, made available to the SRC, adapted and (if needed) enhanced for the scope of: -Validating the building blocks developed in the other parallel operational grants and -Providing regulated services to the space robotics community beyond this project.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: COMPET-4-2016 | Award Amount: 3.49M | Year: 2016

InFuse aims to develop very essential data fusion capabilities (aka. Common Data Fusion Framework, or CDFF) that will serve in the context of many space robotics applications, on planetary surface as well as in orbit or other microgravity environments. The InFuse CDFF will be developed relying on the expertise of partners having tangible experience with a wide range of sensors data processing (Perception and Navigation related) and a wide range of robotic applications both in space and terrestrial conditions. InFuse makes provision for convenient and effective articulation with other SRC common building blocks in particular: OG1 (RCOS), OG2 (autonomy framework) and OG4 (sensors suite). The solution proposed in InFuse to wrap and handle data fusion technologies and their produced data will make easy and effective their adoption by a wide range of users, both among the SRC stakeholders and in the wider space robotics community. In particular, InFuse will not only provide access to an extensive set of robust data fusion capabilities, applicable both On-Orbit and Planetary scenarios, but will also include a data product management component allowing to retrieve and request conveniently (on-demand) relevant data such as maps, models of the environment or objects, possibly science data, etc.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: COMPET-4-2016 | Award Amount: 3.50M | Year: 2016

The ESROCOS activity is devoted to the design of a Robot Control Operating Software (RCOS) that can provide adequate features and performance with space-grade Reliability, Availability, Maintainability and Safety (RAMS) properties. The goal of the ESROCOS proposal is to provide an open source framework which can assist in the generation of flight software for space robots. By providing an open standard which can be used by research labs and industry, it is expected that the elevation of TRL levels can be made more efficient, and vendor lock-in through proprietary environments can be reduced. Current state-of-the-art robotic frameworks are already addressing some of these key aspects, but mostly fail to deliver the degree of quality expected in the space environment. Terrestrial RCOS developed by industrial robot companies (e.g. VxWorks, PikeOS) are not usable for space robotics because their Intellectual Property Rights (IPR) enforce the vendors dependency on space development. Other open-source frameworks do not have sufficient RAMS properties for its use in space missions. The ESROCOS objectives are to: 1. Develop a Space-oriented RCOS including space-grade RAMS attributes, formal verification and qualification of industrial drivers. 2. Integrate advanced modelling technologies, separating the model from the platform 3. Focus on the space robotics community, with requirements coming from actors leading robotics missions 4. Allow integration of complex robotics applications by including the Time and Space partitioning approach 5. Avoid vendor-lock in situations by delivering an open-source solution 6. Leverage on existing assets, such as already existing frameworks properly extended, mature toolsets and libraries) 7. Ease the development of robotics systems by providing a solution interoperable with other robotics frameworks (e.g. Rock/ROS third-party libraries and visualizers/simulator) 8. Cross-pollinate with non-space solutions and applications


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: COMPET-4-2016 | Award Amount: 3.49M | Year: 2016

The main objective is to develop a standard interface that considers a set of connections that allow coupling of payload to manipulators and payload to other payload. The realization of a modular reconfigurable system depends, among other things, on interfaces, that includes mechanical interfaces connecting the blocks to one other, electrical interface for power transmission, thermal interfaces for heat regulation and interfaces to transmit data throughout the satellite. Multi--functional Intelligent interface will be considered to interconnect building blocks and also to connect to the satellite with a servicer. The standard interface will require standardization and modularization of the different components in an integrated form (where mechanical, thermal, electrical, data connections are combined) or a separated form. The standard interface shall allow building up large clusters of modules. APMs are considered for demonstration, validation and verification of all properties of the standard interface. An end-effector for a robotic manipulator will be designed according to the layout of the standard interface. The Modular Interface will take into account long duration missions, no logistics support and missions composed of multiple payloads and architectures. Main benefits: - Improve operational capacity - Reduced logistics with common and modular spares - Common maintenance standards - IF architecture flexibility: common infrastructure needed to support the modular design - Mission flexibility (configuration changes) - Standardizes mechanical, data, electrical, thermal Interfaces - Keep existing standards where applicable - Introduce in the design aspects related to interchangeability and interoperability The standard interfaces will allow to develop the SRC end goals. The output of this development will address the Future Low--cost EXchangeable/EXpandable/EXtendable SATellite, which targets the demonstration of robotics servicing technology.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-26-2016 | Award Amount: 4.30M | Year: 2017

Dreams4Cars takes inspiration from the Simulation Hypothesis of Cognition notably in the sense of Hesslow and in particular from the idea that thoughts are chains of simulated actions and simulated perceptions. The main objective of Dreams4Cars is to set up an offline simulation mechanism in which robots, by recombining aspects of real-world experience, can produce an emulated world, with which they can collectively interact to safely develop and improve their Perception-Action systems, in particular focusing on the analysis of rare events. The Perception Action systems trained by simulations in this way will then be used for sensorimotor control in real interactions. The application domain of Dream4Cars is automated driving, which besides being a major economic sector for the EU also poses the issue of developing systems capable of dealing with arbitrary and open-ended circumstances. Accidents are rare events and, to demonstrate that autonomous systems are safe enough (i.e. significantly safer than humans which is not achieved today at high and full automation levels), extensive field operation tests would normally be required. The solution offered by Dreams4Cars, by focusing on variations of much more frequent near-miss accidents, can develop safe behaviours for hypothetical/unexperienced situations. Hence Dream4Cars will contribute by solving both the problem of discovering critical situations and the problem of updating safely the software. Dreams4Cars will compare the driving agents evolved by the simulation technology to a baseline agent which will have the same State of the Art skills developed by the latest EU project in driving automation (AdaptIVe), hence concretely verifying the added value of the robotic technology (with target TRL 6).


Grant
Agency: European Commission | Branch: H2020 | Program: IA | Phase: ICT-12-2016 | Award Amount: 10.01M | Year: 2016

Digital technologies underpin innovation and competitiveness across a broad range of market sectors. A key technology to boost such innovation and competitiveness is represented by the full and wide adoption of Open Service Platforms. In fact, they will allow increased competition and market penetration because they should be built on top of royalty-free open specifications, adopting open source reference implementations, and s such allowed to be offered by multiple vendors. The Seventh Framework Programme for Research and Technology Development (FP7) has developed the FIWARE platform which has demonstrated its potential of becoming a service platform of choice, with proven potential for usage by SMEs and startups. This rises to the extent that four main ICT players in Europe with global ambition have put FIWARE in their strategy for market development. More than that, those four players announced the creation of an open to all legal entity, the FIWARE Foundation, to have more stakeholders driving the evolution of FIWARE. Well in this scope, the aim of the FI-NEXT project is to put in place all the measures necessary in order to make FIWARE materializing such a potential. This will achieved pursuing the following objectives: a) bringing FIWARE from an European Open Source project to a global Open Source Community, b) ensuring FIWARE meets the highest quality standards and best technical support, c) positioning FIWARE as the de facto standard for the development of smart applications, and d) ensuring FIWARE Lab to be a self-sustainable environment.


Grant
Agency: European Commission | Branch: H2020 | Program: IA | Phase: ICT-22-2016 | Award Amount: 5.55M | Year: 2017

The overarching aim of the iRead project is to develop a software infrastructure of personalised, adaptive technologies and a diverse set of applications for supporting learning and teaching of reading skills. The specific goals of the project proposed are to: 1. Develop a scalable, cloud-based software infrastructure of open, interoperable components, including real-time user modelling and domain knowledge components, to support learning of reading skills by children with different abilities and linguistic backgrounds 2. Develop domain models for English, Greek, German and Spanish learners, and to contextualise those models with respect to skills and difficulties of (i) typically developing readers, (ii) English and Greek readers with dyslexia and (ii) learners of English as a Foreign language. The domain models will utilise and generalise the domain model implemented in a previous FP7 project iLearnRW 3. Develop applications for supporting learning (literacy games, interactive e-books, Reader app) that utilise the infrastructure to yield different types of personalised learning services and experiences 4. Develop and evaluate personalised content classification metrics that enable reading for use by electronic publishers and libraries 5. Enable orchestrated use of the learning applications (games, e-books, Reader app) based on learning analytics, and a personalised experience through adaptive support 6. Implement a number of large-scale evaluation pilots across European countries and providers in order to evaluate the pedagogical effectiveness of the iRead ecosystem.

Loading German Research Center for Artificial Intelligence collaborators
Loading German Research Center for Artificial Intelligence collaborators