About

Kai Lingemann is a pioneering researcher in robotics and autonomous systems, with a particular focus on simultaneous localization and mapping (SLAM) and mobile robot navigation. His most influential contributions center on 6D SLAM — an advanced approach to mapping that accounts for all six degrees of freedom in robot pose estimation, encompassing positional coordinates and rotational angles. This work proved especially transformative for robots operating on uneven, natural terrain where traditional 2D or simplified 3D methods fall short. Lingemann's landmark 2007 paper, "6D SLAM — 3D Mapping Outdoor Environments," has accumulated over 440 citations, establishing him as a leading voice in three-dimensional environmental mapping. His early work on autonomous mine mapping demonstrated real-world applicability in challenging, GPS-denied environments, while his contributions to high-speed laser localization and iterative closest point (ICP) algorithms pushed the boundaries of computational efficiency in robot positioning. His research into loop closing techniques and globally consistent 3D mapping addressed critical challenges in long-term robot autonomy. Across his most-cited publications, Lingemann has garnered well over 1,500 citations, reflecting sustained influence on the robotics community. His work continues to underpin modern developments in autonomous vehicles, industrial robotics, and environmental modeling.

Research Focus

Key Achievements

19
H-Index
35
Papers
1,979
Total Citations
57
Avg Citations/Paper
🏆 Most Cited Paper
6D SLAM—3D mapping outdoor environments
446 citations · 2007
📈 Most Prolific Year: 2005 (7 Papers)
🤝 Key Collaborators: 37
🏛 Institutions: Osnabrück University, Stanford University, Fraunhofer Institute for Intelligent Analysis and Information Systems, German Research Centre for Artificial Intelligence, Czech Academy of Sciences, Institute of Computer Science

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago