Papers

41

Total Citations

1,352

H-Index

20

About

Todor Stoyanov is a prominent robotics researcher whose work spans 3D perception, autonomous mobile robotics, and industrial automation. He is perhaps best known for his foundational contributions to 3D scan registration, particularly through the Normal Distributions Transform (NDT) framework. His 2012 paper on fast and accurate scan registration through compact 3D NDT representations has garnered over 240 citations, establishing him as a key figure in the field of point cloud alignment and simultaneous localization and mapping (SLAM). Stoyanov has made significant methodological contributions to evaluating and benchmarking scan-matching algorithms, advocating for rigorous, reproducible experimental standards in a 2015 study with 85 citations. His research extends into outdoor autonomous navigation, where he developed NDT-based traversability mapping for challenging vegetated environments, and into depth-camera pose estimation through his SDF Tracker system. Beyond perception, Stoyanov has driven practical impact in industrial robotics, tackling autonomous warehouse picking, palletizing, and container unloading — problems with direct commercial relevance. More recently, his work on mixed-reality teleoperation has attracted substantial attention, earning over 90 citations. Across more than a decade of research, Stoyanov has consistently bridged fundamental algorithmic innovation with real-world robotic deployment.

Research Focus

Key Achievements

20
H-Index
41
Papers
1,352
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
Fast and accurate scan registration through minimization of the distance between compact 3D NDT representations
242 citations · 2012
📈 Most Prolific Year: 2022 (6 Papers)
🤝 Key Collaborators: 83
🏛 Institutions: Örebro University, Constructor University, University of Pisa

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago