KolRob: Collaborative, Intelligent Robot Colleague for Specialised Workers of Medium-sized Companies

The project KolRob focuses on the problems arising in the human-machine cooperation in industrial assembly. Lacking technologies and concepts, which have been impeding the full automation of assembly processes in the industry, are being identified thereby. The core research area is, on the one hand, the classification of assembly tasks and the evaluation of robotic systems' feasibility for complex assembly tasks. On the other hand, the possibility of a cooperative assembly by means of concrete application scenarios shall be further developed. Safety and workspace monitoring are just as important as the efficient distribution of assembly steps in the process. In cooperation with SMEs and large-scale enterprises, the limits of automation shall be newly defined and innovative, robotic solution approaches shall be transferred from research into industry.


  • New cooperative production concepts for industrial robots increase the flexibility
  • Safe lightweight robots (LBR) allow the direct contact and can be implemented without using fences
  • Analysing manual assembly processes and identifying potentials for cooperative solutions
  • Realising and evaluating cooperative solutions in demonstration scenarios

Collaborative screw assembly

In the future, teams of robots and specialised workers will not only work efficiently together in large-scale enterprises but also in SMEs. The following key technologies are demonstrated in the KolRob use case "Collaborative Screw Assembly":

  • Fast sensor data processing, including the fusion of 2D/3D images for image recognition and collision prevention
  • Manipulation strategies that use hybrid force/position control for industrial assembly tasks.
  • Cooperative task scheduling between robots and specialised workers for the increase of throughput
  • GPU-based 3D workspace monitoring and the forecasting of human movements enable a safe cooperation




Contact person

Dr.-Ing. Arne Rönnau

Department Manager



Arne Roennau studied Electrical Engineering at the University of Karlsruhe (TH), today's Karlsruhe Institute of Technology (KIT), from 2002 to 2008. The focus of his studies was on control and robotics. His thesis was focussed on sensor-based 3D environmental modelling and foot point planning for the six-legged walking robot LAURON.

From 2008 to 2011, Arne Roennau worked as a robotics expert in the department Interactive Diagnosis and Service Systems (IDS) at FZI. During this time, he worked on the localization of mobile robots, real-time control of AGVs as well as the optimization of multi-legged walking robots.

In 2019, Arne Rönnau earned his doctorate summa cum laude at the Karlsruhe Institute of Technology (KIT) on "Model-based design and optimization of multi-legged walking robots".

His current work focuses on Open Source Software (OSS), in particular ROS (Robot Operating System), human-robot collaboration (HRC), design of innovative service robotics applications such as the BratWurst Bot as well as learning deep neural networks/AI. His most important concern is the evaluation and transfer of these technologies into industrial, real world applications. Arne Rönnau is project manager in numerous public and industrial projects and coordinator of several national as well as federal research projects like AuRorA, VeriKI, CyberProtect.

Since 2011, Arne Roennau heads the department Interactive Diagnostic and Service Systems (IDS) within the research division Intelligent Systems and Production Engineering (ISPE). Besides, Arne Roennau is also the head of the FZI Living Lab Service Robotics since 2012.


Arne Roennau as served as reviewer for many international conferences like IEEE ICRA, IEEE/RSJ IROS, IEEE ICAR and many more. Besides he has also reviewed many articles for international journals likes IEEE Robotics and Automation Letters und IEEE Transactions on Robotics. Moreover, Arne Roennau was part of the Program Committees of the IEEE ECMR 2019.

You can find details and statistics about my scientifc papers her: Google Scholar Profil

zu den Publikationen


Phone: +49 721 9654-228
E-Mail: roennau@dont-want-spam.fzi.de

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