Matthias Luber
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
Top Papers
- 1People tracking with human motion predictions from social forces326 citations · 2010
- 2People tracking in RGB-D data with on-line boosted target models172 citations · 2011
- 3Socially-aware robot navigation: A learning approach165 citations · 2012
- 4
- 5Tracking people in 3D using a bottom-up top-down detector104 citations · 2011
- 6Robot-specific social cues in emotional body language70 citations · 2012
- 7Place-dependent people tracking62 citations · 2011
- 8Multi-Hypothesis Social Grouping and Tracking for Mobile Robots32 citations · 2013
- 9
- 10Classifying dynamic objects21 citations · 2009