Papers
61
Total Citations
1,443
H-Index
20
About
Matej Hoffmann is a prominent robotics and cognitive science researcher whose work sits at the fascinating intersection of neuroscience, embodied cognition, and autonomous systems. His research spans body representations in robotics, morphological computation, peripersonal space, and robot self-calibration — areas that collectively address how artificial agents can develop human-like awareness of their own bodies and environments. Hoffmann's most influential contribution, "Body Schema in Robotics: A Review" (2010, 243 citations), synthesized interdisciplinary insights from psychology, philosophy, and neuroscience to illuminate how body representations can be implemented in robotic systems. His highly cited work on morphological computation (186 citations) further advanced understanding of how physical body structure itself contributes meaningfully to cognition and control, reducing reliance on centralized processing. His studies on peripersonal space and artificial skin demonstrate how humanoid robots like iCub can learn multisensory body boundaries, directly inspired by primate neurophysiology. Beyond perception, Hoffmann has made significant engineering contributions through innovative self-calibration methods for complex robotic systems. His developmental robotics work, linking infant motor learning experiments to computational models, exemplifies his commitment to biologically grounded approaches. With nearly 900 cumulative citations, Hoffmann has established himself as a leading voice in embodied artificial intelligence and humanoid robotics research.
Research Focus
Key Achievements
Top Papers
- 1Body Schema in Robotics: A Review243 citations · 2010
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