Papers
52
Total Citations
1,359
H-Index
20
About
Angelika Peer is a leading researcher in human-robot interaction, with particular expertise in haptic interfaces, physical collaboration, teleoperation, and assistive robotics. Her work sits at the intersection of robotics, neuroscience, and human factors, addressing one of the central challenges in modern robotics: enabling machines to interact naturally and intuitively with people. Peer's most influential contributions center on understanding and replicating the dynamics of human physical interaction. Her pioneering HMM-based framework for haptic human-robot handshaking (123 citations) demonstrated how probabilistic models could generate realistic, context-aware robot behavior during contact. Complementing this, her investigations into dominance and role determination during haptic collaboration (68 and 62 citations respectively) provided foundational insights into how partners negotiate control during shared manipulation tasks. Beyond interaction modeling, Peer has advanced tactile sensing through a biologically inspired neurorobotic texture classifier using spiking neural networks (70 citations), and contributed to assistive technology through work on sit-to-stand transfer modeling and adaptive shared control for mobility robots. Her brain-computer interface research further demonstrates her commitment to empowering individuals living with physical disabilities. With a body of work spanning foundational theory and applied systems, Peer has meaningfully shaped how researchers approach safe, intuitive, and responsive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1An HMM approach to realistic haptic human-robot interaction123 citations · 2009
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- 3Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch70 citations · 2016
- 4Experimental analysis of dominance in haptic collaboration68 citations · 2009
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- 7Role determination in human-human interaction62 citations · 2009
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