Georg Biegelbauer

TU Wien

Papers

13

Total Citations

202

H-Index

8

About

Georg Biegelbauer is an Austrian robotics and computer vision researcher whose work spans industrial automation, 3D object detection, and autonomous robot programming. His research has made significant contributions to the challenge of enabling robots to perceive, interpret, and interact with their environments across both industrial and domestic settings. Biegelbauer's most influential work, "Efficient 3D Object Detection by Fitting Superquadrics to Range Image Data" (2007, 71 citations), introduced a fast and robust method for localizing diverse objects in cluttered environments using laser range sensors — a breakthrough for robotic service and assistance applications. His model-based 3D object detection research further consolidated his reputation in machine perception. A recurring theme throughout his career is automated robot programming for industrial tasks. His contributions to the EU-funded FlexPaint project pioneered fully automated spray painting of high-variant, low-volume parts, removing the costly burden of manual offline programming. Complementing this, his work on sensor-guided bore inspection systems — deploying 3D vision to direct robotic endoscopes into bore holes — demonstrated practical, industrially deployed solutions with real quality-control impact. Spanning sewing robots, mobile navigation, and combined shape-appearance recognition, Biegelbauer's diverse portfolio reflects a researcher committed to bridging perception and action in robotics across challenging real-world applications.

Research Focus

Key Achievements

8
H-Index
13
Papers
202
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Efficient 3D Object Detection by Fitting Superquadrics to Range Image Data for Robot's Object Manipulation
71 citations · 2007
📈 Most Prolific Year: 2004 (4 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: TU Wien

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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