Christof Elbrechter
Papers
11
Total Citations
325
H-Index
10
About
Christof Elbrechter is a robotics researcher whose work sits at the intersection of robot manipulation, computer vision, and human-robot interaction, with a particular focus on advancing what he terms "manual intelligence" — the rich repertoire of dexterous skills that humans deploy effortlessly but robots struggle to replicate. His most recognized contributions center on robotic manipulation of deformable objects, most notably his pioneering work on paper folding using anthropomorphic robot hands guided by real-time physics-based modeling, which has garnered over 50 citations and remains a landmark study in the field. Elbrechter has also made significant strides in 3D scene segmentation for autonomous grasping, bi-manual coordination strategies inspired by human motion, and multi-modal feedback control integrating vision, haptics, and proprioception for in-hand object manipulation. His curiosity-driven robot learning framework, exploring how untrained users can interactively teach robots novel tasks, reflects a sustained commitment to accessible human-robot collaboration. With additional contributions spanning color-glove-based hand tracking, liquid discrimination for kitchen robotics, and bio-inspired bimanual strategies, Elbrechter's cumulative work — exceeding 300 citations — represents a compelling and cohesive vision for bringing robotic dexterity closer to human-level capability.
Research Focus
Key Achievements
Top Papers
- 1
- 2The curious robot - Structuring interactive robot learning50 citations · 2009
- 33D scene segmentation for autonomous robot grasping48 citations · 2012
- 4Approaching Manual Intelligence33 citations · 2010
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- 8Discriminating liquids using a robotic kitchen assistant20 citations · 2015
- 9Bio-inspired motion strategies for a bimanual manipulation task20 citations · 2010
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