Tag Archives: Application Industrie4.0

FI-NEXT – Bringing FIWARE to the NEXT Step

Das Projekt FI-NEXT setzt eine Reihe ASR-Forschungsaktivitäten im Rahmen von FIWARE fort. FI-NEXT konzentriert sich nun auf die Vereinheitlichung von Schnittstellen und Datenmodellen, sowie die Optimierung der Kommunikation zwischen den verschiedenen Generic-Enabler, um die Ergebnisse aus FI-WARE und FI-CORE zu einer einheitlichen Open-Source-Infrastruktur zu erheben. In FI-NEXT wird sich der Fachbereich ASR auf Linked-Data als aufstrebenden Mechanismus für leistungsfähigere und flexiblere Schnittstellen konzentrieren. Dabei werden sowohl die Schnittstellen zu Diensten, als auch das für die Übertragung von Daten verwendete Modelle in einer standardisierten Sprache semantisch beschrieben. Das Ziel ist, durch die semantische Beschreibung von Diensten und Schnittstellen, das Design und die Bereitstellung von verteilten Anwendungen im Kontext von FIWARE weiter zu erleichtern. Die Arbeit in FI-NEXT steht in direktem Bezug zu Arbeiten im Advanced Web-based User Interface Chapter in FIWARE, z.B. durch die Weiterentwicklung des in FI-CORE entwickelten, neuartigen Synchronization-Generic-Enabler (FiVES) oder auch XML3D als 3D-User Interface GE. Auch Ergebnisse aus dem Projekt ARVIDA fließen in Form der oben genannten semantischen Dienstebeschreibungen unmittelbar in FI-NEXT mit ein. Ziel ist, die Entwicklung einer end-to-end Anwendungslösung zu vereinfachen, die es erlaubt, den Bogen von IoT-Sensoren bis hin zu interaktiven Visualisierungen in Apps zu spannen. Die Entwicklung soll dabei sowohl das Design der Anwendung, als auch das Deployment der benötigten Service-Infrastruktur beinhalten. Die Arbeitsgruppe um Prof. Slusallek will sich darüber hinaus, abhängig von Wahlergebnissen in der Open Source Community, weiter als Leiter und Architekt des WebUI Chapters, sowie als Co-Chair des Technical Steering Committee engagieren.

Ansprechpartner: Dipl.-Inf. René Schubotz
Homepage: https://forge.fiware.org/projects/fi-next/

Agents

The team Agents  investigates these concepts in real-world (commercial) applications as well as in virtual environments. It concentrates on agent-based modelling and software development as well as on specific technologies for the design of agent behaviour. More recently a stronger focus was set on motion modelling and synthesis for agent design in 3D simulations. In this context learning techniques with statistical models and neuronal networks (deep learning) are investigated. Continue reading Agents

Fastlane

Nowadays Web applications, including 3D virtual worlds, real-time simulations, and virtual reality applications demand a high amount of processing power. JavaScript, yet, is inherently single threaded and computationally intensive tasks need to avoid taking exclusive control over this thread for a prolonged time to not stall the entire Web page.

The JavaScript APIs that enable hardware-supported parallelism, such as SIMD.js and Web Worker, however, are by design low-level APIs and subject to hardware specific limitation, unfamiliar programming idioms, and performance portability issues if they are not available on every platform.

Fastlane solves these problems by combining the results of two successful projects, Xflow and shade.js, to provide a compiler-driven adaptive data-flow-programming framework for parallel data processing on the web.

It utilizes data-flow programming, a proven and well-know programming idiom for data processing, to define a series of data-transformations, each written in a valid subset of JavaScript. The provided data-flow graph is then analyzed and compiled into optimized JavaScript or GLSL shader code, considering all APIs available on the current system. This alleviates the necessity for the developer to define multiple versions of the same computation for different combination of available APIs and platform features.

– Hybr-iT

Hybr-iT

Hybrid and intelligent human-robot collaboration – hybrid teams in versatile, cyber-physical production environments

The aim of the Hybr-iT joint research project funded by the Federal Ministry of Education and Research (BMBF) is to build and test hybrid teams of humans and robots working together with software-based assistance systems in intelligent environments in industrial manufacturing. Based on a holistic approach to the various disciplines of human-robot collaboration, intelligent planning and simulation environments, assistance systems and knowledge-based robotics, workers in the production process are supported by robots in such a way that this intensive human-robot cooperation is convenient, safe and efficient.


Hybr-iT researches and evaluates the components required for planning and optimizing hybrid teams in an industrial context – in terms of their integration in existing IT and production systems and as necessary for their control in a production operation. From an IT perspective, this will involve heavily distributed systems with very heterogeneous subsystems (such as plant and robot controls, safety, logistic, database, assistance, tracking, simulation, and visualization systems), which are implemented together in a comprehensive resource oriented architecture (ROA). ASR contributes to the ROA and develops the simulation environment for hybrid human-robot teams, using AJAN and Motion Synthesis.

The Hybr-iT project is funded by the Federal Ministry of Education and Research.

Ansprechpartner: Ingo Zinnikus

Individualisierte Implantate und Prothesen für die Versorgung unterer Extremitäten (IIP-EXTREM)

Individualisierte Implantate und Prothesen für die Versorgung unterer Extremitäten (IIP-EXTREM)

Severe injuries of the lower leg require individual treatment and often require the treating doctors to make difficult decisions. The funded research project  IIP-EXTREM in the BMB+F program „Individualized Medical Technology“ aims to provide technical support for those decisions and make them more quantitative.

The project follows two strategies: the first strategy aims for reconstruction using individualized and standardized implants. Powerful simulations and visualizations based on clinical CT or MRT data will help to re-orient bone fragments, make decisions concerning the right choice of implant and finally generate individual implants. The fabrication of the implants will be performed using modern methods of additive metal fabrication.

The second strategy will come in place if a severe injury makes an amputation inevitable. In this case, simulation software  will help to create an exact fitting, high performance prothesis shaft.

Both subprojects aim to use efficient simulations and modern additive manufacturing methods to optimize the production chain and save expensive recurring treatments.

The clinical side of the consortium is represented by the Chair of Orthopedics of the Trauma Surgery of the university Witten/Herdecke. The simulation and its validation is developed jointly between the Chair of Applied Mechanics of Saarland University and the German Research Center for Artificial Intelligence (DFKI), that also creates the user interfaces. Individualized implants are developed and manufactured by Karl Leibinger Medizintechnik GmbH & Co. KG, the prothesis shafts are developed and manufactured by Ottobock HealthCare GmbH, who also coordinates the consortium.

Project duration: 01.06.2016 – ???

Contact: Dr Tim Dahmen

Team

AJAN

AJAN (Access Java Agent Nucleus) is a modular agent web service which integrates different AI technologies in an intuitive way for creating autonomous systems. The main goal of the development is to address a heterogeneous community with an easy to use, flexible and powerful AI tool for different domains, such like 3D simulations, programmable web or home automation. AJAN is in use for different virtual reality applications, such as pedestrian or shop floor simulations (in the context of Industrie 4.0) in which multiple autonomous 3D entities has to be controlled.
Continue reading AJAN

AnyDSL

AnyDSL – A Framework for Rapid Development of Domain-Specific Libraries

AnyDSL is a framework for domain-specific libraries (DSLs). These are implemented in our language Impala. In order to achieve high-performance, Impala partially evaluates any abstractions these libraries might impose. Partial evaluation and other optimizations are performed on AnyDSL’s intermediate representation Thorin.

More information can be found on the AnyDSL website: http://anydsl.github.io

MotionGraph

Morphable Graph [1] is a generative, graph-based approach for data-driven motion modeling and synthesis. Motion capture data is represented by a directed graph and motion synthesis tasks are converted to graph searching problem.

Continue reading MotionGraph