Papers
17
Total Citations
560
H-Index
9
About
H.-J. Boehme is a prominent robotics researcher whose career has been defined by a sustained commitment to developing intelligent, interactive mobile service robots capable of operating in real-world environments. Best known for leading the long-running PERSES and ShopBot/TOOMAS research programs, Boehme has spent over a decade advancing the design of autonomous shopping assistant robots deployed in demanding settings such as home improvement stores. His foundational contributions to vision-based probabilistic self-localization — particularly omnidirectional Monte Carlo Localization techniques — have provided robust navigation solutions for mobile robots navigating complex, dynamic spaces, earning him over 150 citations for the TOOMAS project alone. Beyond navigation, Boehme has made significant strides in human-robot interaction, pioneering neural network architectures for gesture-based communication that allow intuitive user control of mobile platforms. His work on user-centered design principles further reflects a commitment to making robots genuinely accessible and practical. Later research extended these capabilities to museum environments, exploring augmented reality projection systems for tour guide robots. With a cumulative citation record spanning foundational algorithms to full-scale field deployments, Boehme's research represents a rare and valuable integration of theoretical rigor with real-world impact in service robotics.
Research Focus
Key Achievements
Top Papers
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- 3User-Centered Design and Evaluation of a Mobile Shopping Robot64 citations · 2014
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- 6PERSES-a vision-based interactive mobile shopping assistant32 citations · 2002
- 7Neural architecture for gesture-based human-machine-interaction23 citations · 1998
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- 9Neural networks for gesture-based remote control of a mobile robot16 citations · 2002
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