Daniel Gebauer
Papers
8
Total Citations
44
H-Index
4
About
Daniel Gebauer is a leading researcher in industrial robotics, with a focus on autonomous manufacturing, human-robot collaboration, and the manipulation of deformable objects. His work addresses critical challenges in modern production, including labor shortages and the need for flexible automation. Gebauer’s major contributions include developing a concept for the automated adaptation of abstract planning domains for specific industrial applications, which has garnered 11 citations, and a method for evaluating layout options in human-robot collaboration, cited 10 times. He has also pioneered techniques for vision-based robotic picking, such as cut-paste image generation for instance segmentation, enabling robots to handle disordered industrial parts more effectively. Notably, his research on deformable linear objects (DLOs), including cables, has led to innovative approaches for bin picking and grasp planning, with recent work on object-oriented grasp planning for DLOs published in 2024. Gebauer’s achievements include advancing the automation of cable assembly and electrical connector mating, with a focus on sensitive robotic manipulation. His work is highly cited and continues to shape the future of flexible, autonomous manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Method for the evaluation of layout options for a human-robot collaboration10 citations · 2019
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- 4Concept for Robot-Based Cable Assembly Regarding Industrial Production4 citations · 2022
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