Papers

14

Total Citations

1,184

H-Index

12

About

Matthias Luber is a leading researcher in human-aware robotics, with his work fundamentally shaping how robots perceive, track, and interact with people in shared spaces. His core research areas span people tracking, socially-aware navigation, and human-robot interaction. Luber’s most influential contribution is his pioneering application of social force models to human motion prediction for people tracking, detailed in his 2010 paper (326 citations), which enabled robots to anticipate complex pedestrian behaviors rather than assuming simple constant velocity. He further advanced the field through innovative multi-sensor fusion, developing robust 3D people detection and tracking methods using RGB-D data (172 citations) and laser range data with multi-hypothesis leg-tracking (147 citations). His work on socially-aware robot navigation (165 citations) established learning-based approaches that balance objective travel efficiency with subjective social comfort. Luber also explored robot-specific emotional body language (70 citations) and place-dependent tracking (62 citations), demonstrating how environmental context influences human motion patterns. With over 1,100 total citations across his top papers, Luber’s research has become foundational for service robots, autonomous vehicles, and any system requiring safe, socially competent navigation in human environments.

Research Focus

Key Achievements

12
H-Index
14
Papers
1,184
Total Citations
85
Avg Citations/Paper
🏆 Most Cited Paper
People tracking with human motion predictions from social forces
326 citations · 2010
📈 Most Prolific Year: 2011 (5 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: University of Freiburg, University of California, Berkeley

Top Papers

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  10. 10
    Classifying dynamic objects
    21 citations · 2009

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago