Papers
9
Total Citations
390
H-Index
7
About
Zicheng Kan is a robotics researcher whose work sits at the dynamic intersection of soft robotics, tactile sensing, and bio-inspired design. His research focuses on developing innovative soft robotic systems that mimic biological principles to achieve human-like dexterity and adaptability. Kan's most influential contribution, his 2019 paper on hybrid jamming for bioinspired soft robotic fingers (148 citations), introduced a groundbreaking design integrating layer and particle jamming with fiber-reinforced pneumatic actuation, significantly advancing controllable stiffness in soft manipulators. Alongside this, his work on vision-based tactile sensing has been particularly impactful: his "FingerVision" sensor (74 citations) and the accompanying Helmholtz–Hodge Decomposition-based contact force estimation algorithm (72 citations) represent meaningful steps toward robust robotic perception. Kan has also explored low-cost actuation strategies, leveraging supercoiled polymer artificial muscles in both inchworm-inspired locomotion robots and variable stiffness actuators. His origami-inspired designs further demonstrate his versatility in pursuing elegant, fabrication-efficient solutions for robotic grasping. With over 390 cumulative citations, Kan's body of work reflects a consistent commitment to bridging biological inspiration with practical engineering advances in next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Hybrid Jamming for Bioinspired Soft Robotic Fingers148 citations · 2019
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- 7An Origami-Inspired Monolithic Soft Gripper Based on Geometric Design Method16 citations · 2019
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