Siegfried Hochdorfer

Technische Hochschule Ulm, Robotics Research (United States)

Papers

11

Total Citations

81

H-Index

5

About

Siegfried Hochdorfer is a robotics researcher whose work centers on simultaneous localization and mapping (SLAM), mobile service robotics, and robust autonomous navigation in real-world environments. His research has made meaningful contributions to the challenge of enabling service robots to operate reliably over extended periods — a problem known as lifelong operation — particularly in dynamic, everyday indoor settings. Hochdorfer's most influential work addresses one of SLAM's core practical limitations: the continuously growing number of landmarks that accumulates during long-term robot operation. His papers on landmark rating and selection strategies (17 citations) and 6 DoF SLAM using time-of-flight cameras (20 citations) propose principled approaches to managing computational resources without sacrificing localization accuracy. He has explored multiple sensing modalities, including omnidirectional vision, bearing-only SLAM with omnicams, and manipulator-mounted laser rangers for object manipulation tasks. Beyond mapping, Hochdorfer has investigated probabilistic fusion of object recognition algorithms and human-machine interfaces for autonomous robots in public spaces, reflecting a broad commitment to making service robots genuinely deployable. With cumulative citations across a decade of publications, his body of work represents a sustained and practical contribution to bridging the gap between laboratory robotics and robust, real-world autonomous systems.

Research Focus

Key Achievements

5
H-Index
11
Papers
81
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
6 DoF SLAM using a ToF camera: The challenge of a continuously growing number of landmarks
20 citations · 2010
📈 Most Prolific Year: 2009 (3 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Technische Hochschule Ulm, Robotics Research (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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