Papers
6
Total Citations
97
H-Index
4
About
Hanjun Song is a leading researcher at the intersection of human-robot interaction, assistive robotics, and wearable technology. Their work focuses on augmenting human capabilities through Supernumerary Robotic Limbs (SuperLimbs) and developing autonomous systems for feeding and piloting. Song’s most influential contribution is the design and control of SuperLimbs that leverage the human body’s natural redundancy—over 200 muscles—to enable voluntary and reactive collaboration. This work, cited 46 times, introduces a hybrid control framework where some robotic degrees of freedom are powered by human movement, offering transformative support for hemiplegic patients. In assistive feeding, Song resolved the critical trade-off between range and sensitivity in shear force sensing (22 citations), enabling robots to safely manipulate deformable foods. Their recent shared control method, based on Lipschitz analysis, quantifies human-robot collaboration for safer interaction. Song has also explored humanoid robot piloting for unmanned aerial vehicles, broadening the scope of embodied AI. With a growing citation record and innovations spanning rehabilitation, autonomy, and sensor design, Song is shaping the future of wearable robotics and assistive technology.
Research Focus
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Top Papers
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