Papers
14
Total Citations
612
H-Index
11
About
Timm Linder is a robotics researcher whose work sits at the intersection of human-aware robotics, computer perception, and autonomous navigation. His research focuses primarily on people detection and tracking, human attribute recognition, and socially intelligent robot behavior in crowded, dynamic environments. Linder's most celebrated contribution is the SPENCER project, a socially aware service robot designed to guide passengers in busy airports, which has accumulated over 260 citations and stands as a landmark demonstration of real-world human-robot interaction at scale. Building on this foundation, his multi-modal people tracking framework — drawing on both RGB-D and 2D range data — has shaped how mobile robots perceive and follow humans in complex scenes. His investigations into 3D human pose estimation under occlusion brought rigorous scrutiny to a widely overlooked challenge in shared human-robot workspaces. Linder has also advanced the classification of social attributes such as gender and age in real time from depth imagery, equipping robots with richer contextual understanding during interaction. More recently, his context-aware model predictive control formulation pushes toward safer, more efficient human-aware navigation. Across industrial and service robotics settings, Linder's cumulative body of work offers both foundational algorithms and compelling real-world deployments that continue to influence the field.
Research Focus
Key Achievements
Top Papers
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- 3How Robust is 3D Human Pose Estimation to Occlusion?50 citations · 2018
- 4Multi-model hypothesis tracking of groups of people in RGB-D data35 citations · 2014
- 5Deep Person Detection in Two-Dimensional Range Data32 citations · 2018
- 6Real-time full-body human gender recognition in (RGB)-D data30 citations · 2015
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- 9Efficient Context-Aware Model Predictive Control for Human-Aware Navigation13 citations · 2024
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