Jan Guhl

About

Jan Guhl is a leading researcher in industrial robotics, specializing in human-robot interaction, augmented reality (AR), and advanced programming methods. His work focuses on making industrial robots more accessible and intuitive to program, bridging the gap between complex automation systems and human operators. Guhl’s major contributions include developing concepts for programming robots using AR devices like the Microsoft HoloLens, enabling drag-and-drop-like pick-and-place tasks, and integrating cloud-based model predictive control to compensate for communication delays in networked systems. His scoping review on industrial robot programming methods (51 citations) provides a comprehensive overview of the field, while his deep learning-based object recognition system for robot control (60 citations) demonstrates practical AI integration. With over 290 total citations across his publications, Guhl’s research has significantly advanced the feasibility of AR in robotics, addressing technical obstacles to industrial applicability. His work on service-oriented architectures for robotic manufacturing systems, including lessons from the World Robot Challenge 2018, showcases his commitment to real-world implementation. Guhl’s innovative approaches are shaping the future of flexible, user-friendly automation in Industry 4.0.

Research Focus

Key Achievements

Top Papers

1. 1
   Industrial Robot Control with Object Recognition based on Deep Learning

   60 citations · 2018
2. 2
   Concept and architecture for programming industrial robots using augmented reality with mobile devices like microsoft HoloLens

   54 citations · 2017
3. 3
   Industrial Robot Programming Methods: A Scoping Review

   51 citations · 2020
4. 4
   Model predictive control as a service — Concept and architecture for use in cloud-based robot control

   42 citations · 2016
5. 5
   Towards commissioning, resilience and added value of Augmented Reality in robotics: Overcoming technical obstacles to industrial applicability

   29 citations · 2021
6. 6
   Enabling Human-Robot-Interaction via Virtual and Augmented Reality in Distributed Control Systems

   15 citations · 2018
7. 7
   Holo Pick'n'Place

   15 citations · 2018
8. 8
   Combining the Advantages of On- and Offline Industrial Robot Programming

   6 citations · 2019
9. 9
   Visualizing trajectories for industrial robots from sampling-based path planning on mobile devices

   2 citations · 2018
10. 10
    A Service-oriented Robotic Manufacturing System: Lessons Learned from Participating in the World Robot Challenge 2018

    2 citations · 2019

Key Collaborators

Contact & Links