All posts by Ingo Zinnikus

– 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


Hybrid Social Teams for Long-Term Collaboration in Cyber-Physical Environments

HySociaTea is short for Hybrid SociaTeams for Long-Term Collaboration in Cyber-Physical Systems. In this project, funded by the German Ministry for Education and Research, the German Research Center for Artificial Intelligence (Deutsches Forschungszentrum für Künstliche Intelligenz – DFKI) investigates how teams of humans, robots and software agents (i.e. virtual characters and softbots) can work collaboratively in a production scenario.

Many large-scale real-world problems, such as effective disaster response, the careful dismantling of contaminated structures or the efficient manufacturing and construction of complex artifacts, require the coordination of such teams of humans, robots, and software agents to accomplish the collection of challenging tasks. It is well known that more can be achieved through teamwork in a shorter timeframe and at a higher quality than by individual performance. Our vision of effective hybrid social teams of humans, robots and software agents working together seamlessly in dynamic cyber-physical environments can only be achieved by combining the research excellence and experience of eight DFKI research departments located at the three main sites (Bremen, Kaiserslautern, Saarbrücken) in a joint effort. HySociaTea is thus a collaborative grand challenge project, which combines the diverse DFKI competencies in a wide spectrum of subfields of Artificial Intelligence to address a fundamental research goal in the area of intelligent interacting agents.

The envisioned characteristics of hybrid social teams of physical and virtual agents imply the following fundamental research challenges:

  1. Distributed problem analysis and task allocation based on skills, knowledge and experience
  2. Sharing goals, plans as well as intentions and coordinating plan execution
  3. Understanding all physical and communicative interactions of all team members
  4. Developing social group behavior and emotional coherence
  5. Building mutual trust and demonstrating accountability for the assigned subtasks
  6. Compensating weaknesses of individual team members by empathetic help

Project Homepage:

Contact: Ingo Zinnikus

Deutsche Version

Das vom Bundesministerium für Bildung und Forschung (BMBF) geförderte Projekt HySociaTea (Hybrid Social Teams for Long-Term Collaboration in Cyber-Physical Environments) realisiert und untersucht die Zusammenarbeit von technologisch unterstützten Menschen mit autonomen Robotern, virtuellen Avataren und Softbots, die zusammen in einem Team gemeinsame Aufgaben lösen sollen.

Im Zusammenhang mit dem Zukunftsprojekt Industrie 4.0 ermöglichen diese hybriden Teams z.B. eine flexible Produktion, in der auch auf ungeplante Ereignisse durch eigenständige Reorganisation des Teams reagiert werden kann. Neben der Erforschung der reinen technischen Grundlagen, liegt der Schwerpunkt auch auf der Entwicklung von robotischen Teamkompetenzen, sowie auf intelligentem Multi-Agenten-Verhalten, welche auch wichtige Aspekte in rein menschlichen Teams sind. Technische Systeme sollen hier vor allem als Assistenzsystem für den Menschen in der Produktion eingesetzt werden – die Roboter müssen also als Partner im Gesamtprozess wahrgenommen werden.

Der in HySociaTea entwickelte und untersuchte hybride Teamaufbau kann auf lange Sicht in unterschiedlichen realen Herausforderungen eingesetzt werden, z.B. bei modularen Produktionsanlagen in der Fabrik der Zukunft, als Rettungsteam bei Katastrophenszenarien, oder bei der notwendigen Arbeitsteilung zwischen Menschen und Maschinen beim sicheren Rückbau von Atomkraftwerken.

Zur Realisierung des Projekts bündeln verschiedene Fachbereiche aus allen DFKI-Standorten (Bremen, Kaiserslautern, Saarbrücken) ihre Kompetenzen:

  • RIC (Robotics Innovations Center, DFKI Bremen): autonome und kooperative Robotersysteme, mobile Manipulation
  • CPS (Cyber-Physical Systems, DFKI Bremen): sichere Mensch-Roboter Interaktion
  • EI (Embedded Intelligence, DFKI Kaiserslautern): technische Einbindung des Menschen, tragbare Sensorik
  • AV (Augmented Vision, DFKI Kaiserslautern): Perzeptionsmodule mittels Bildverarbeitung und Sensorfusion
  • KM (Knowledge Management, DFKI Kaiserslautern): blickgesteuerte Aufmerksamkeitserkennung, Realzeit-Objekterkennung
    IUI (Intelligent User Interfaces, DFKI Saarbrücken): emo-soziale virtuelle Charaktere, multimodale Dialogplattform
  • LT (Language Technology Lab, DFKI Saarbrücken): autonome Teamreorganisation, Sprachinteraktion
  • ASR (Agents and Simulated Reality, DFKI Saarbrücken): Kommunikations-Middleware, Dual Reality

HySociaTea wird gefördert durch das Bundesministerium für Bildung und Forschung (BMBF) unter Förderkennzeichen 01IW14001.

Project Homepage:

Ansprechpartner: Ingo Zinnikus


INVERSIV: Integrated Verification, Simulation and Visualization for Industrial Applications

Industry 4.0 is a main topic in the high-tech strategy of the German  government, aimed at enabling fundamental innovation in industry. The idea behind Industry 4.0 is that “driven by the Internet, the real and virtual worlds are growing closer and closer together to form the Internet of Things. Industrial production of the future will be characterized by the strong individualization of products under the conditions of highly flexible (large series) production, the extensive integration of customers and business partners in business and value-added processes, and the linking of production and high-quality services leading to so-called hybrid products” (BMBF). Together with the increasing requirements of high flexibility, reduced delivery time, and short product life cycles, the Industry 4.0 concept represents the highly dynamic, individualized, and networked environment of modern, digital factories.

There is a large number of challenges on the IT side for realizing Industry 4.0: (i) The high flexibility of production processes requires the ability to quickly redesign and adapt production lines and all supporting processes in a company. (ii) The high variability of products with small batch sizes requires novel, highly adaptable ways to monitor the production line for quality and errors while providing support and training for workers that adapts to the current situation. (iii) To support quick changes we must move from fixed, specialized networks and interfaces to flexible architectures and service interfaces that can easily be reconfigured and support the low-latency, high-volume communication needed in industrial environments.

The main objective of the INVERSIV project is the ability to build fully functional models of systems (such as production lines) and from those models derive the data to monitor, predict, and possibly suggest corrections to the operation of those systems based on live data from real systems (dual reality).

INVERSIV aims at processing and using realtime data streams in production scenarios for visualizing the state of production facilities, detecting failures and problematic situations, and propose and visualize appropriate maintenance and repair actions. In case an error situation has been detected (respectively predicted) actions to resolve the situation have to be planned. We will explore the setup and evaluation of alternative models in terms of hybrid automata and verify their proper functionality with an extended hybrid verification system. The planning stage will also explore maintenance repair actions generated by involving human or intelligent virtual characters, e.g. for installing an alternative model. This highlights again the need to have common data representation and communication mechanism between the modules (here, multi-agent planning and hybrid verification).

The INVERSIV project is funded by the Federal Ministry of Education and Research (FKZ 01IW14004).

Ansprechpartner: Ingo Zinnikus