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TU Berlin

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at the chair of Industry Grade Networks and Clouds.

Smart Manufacturing


Modern manufacturing environments are defined by high flexibility along the whole life cycle.



User interfaces and human-machine-collaboration are supported by cloud applications.

Cloud Control of Machines


Bringing intelligence to the machine requires secure and reliable network and transmission.

The Chair of "Industry Grade Networks and Clouds" deals with applications of network technology and virtualization in industrial manufacturing. The main areas of application are industrial robotics, mobile industrial service robotics, human-robot-interaction, machine learning and Augmented Reality. 

Current Communications

  • Our courses continue in full in spite of Covid-19. The tasks of the projects are adjusted so that they can be worked on at the TU without a physical presence.
  • On 01.11.2019 Prof. Dr.-Ing. Lambrecht will be chair for the first session "Machine Learning in Robotics" of the 7th IEEE International Conference on Robot Intelligence Technology and Applications at KAIST in Daejeon, South Korea.

  • Prof. Dr.-Ing. Lambrecht will be chair for the session "Human Robot Collaboration and Cooperation" on 16.10.2019 at 28ten IEEE International Conference on Robot and Human Interactive Communication in New Delhi.

  • Prof. Dr.-Ing. Lambrecht is holding an invited seminar on 21.05.19 entitled "Human-centered Automation and Human-Robot-Collaboration in the Industral Context" within the course Humanoide Roboter – Die Simulation des Sozialen at Humboldt Universität zu Berlin.
  • Augmented Reality (AR) visualization of ROS navigation stack on Microsoft Hololens. The seamless connection between Unity and ROS was based on a Open Source projects of Siemens. These packages have been extended to support real-time visualization of sensor data, environment map and motion planning. In addition, an automatic spatial matching between robot and AR was implemented. Furthermore, we are enabling intuitive gesture-based interaction for remote control and definition of navigation goals. Further work will focus on merging mapping and localization of robot and AR in order to create benefits on both sides.

  • On the 4th of December 2018 Prof. Dr.-Ing. Jens Lambrecht holds a lecture in context of the lecture series "Digital Future": "Digitalization on the shop floor - from mass production to ultraflexible manufacturing" 
  • New video of an external Bachelor thesis at Volkswagen: 3D pose matching from 2D images using Deep Learning for 2D pose detection - Interactive demo on Pepper Robot 
  • At 13th November 2018 Prof. Dr.-Ing. Lambrecht takes part at the VDE Tec Summit for the session "Andere Realitäten" and expert discussion. The presentation is entitled "Assistenz zur Maschine bringen - Augmented Reality auf dem Shop Floor".
  • New video on Deep-Lerning-based pose estimation between monocular cameras and dynamic industrial manipulators

  • New video on Deep-Lerning-based skeleton detection for industrial robots

  • New publication published:

    T. Kittmann, J. Lambrecht, C. Horn: A Privacy-aware Distributed Software Architecture for Automation Services in Compliance with GDPR. IEEE 23rd International Conference on Emerging Technologies and Factory Automation, 2018.

  • We released a first video about our research on "Visual Asset Detection for Industry" targeting the usage of Deep Learning in production and manufacturing environments

  • Currently, we have an open position for a student assistant in the field of AI in industrial applications and robotics. Feel free to share and spread! http://virtual-prsb.service.tu-berlin.de/AD/advertisement_details.php?id=6547

  • Prof. Dr.-Ing. Lambrecht participates as expert for the topic Artificial Intelligence in the HOT SEAT Session of Deutsche Telekom at Hannover Messe.
    Where: Hanover Messe, hall 6, booth F16,  OpenLab at Telekom-booth 
    When: 24.4.2018, 16.15-17.00 



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Prof. Dr.-Ing. Jens Lambrecht
Industry Grade Networks and Clouds
sec. TEL 18-1
Ernst-Reuter-Platz 7
10587 Berlin
+ 49 (0)30 835358412