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About

Yuyang Song is an emerging robotics researcher whose work spans two dynamic frontiers: intelligent robot safety systems and biologically inspired soft robotics. His early research focused on sensorless collision detection for robotic joints, where he developed a novel strategy leveraging model reference adaptive systems to identify motor inertia and viscosity coefficients online, enabling safer human-robot interaction without the cost and complexity of additional sensors — work that has garnered 4 citations since its 2019 publication. More recently, Song has turned his attention to soft robotics and advanced actuation materials, contributing to the development of jellyfish-inspired robots actuated by innovative twisted and coiled polymer fishing line (TCPFL) artificial muscles. His 2023 contributions include the Jelly-Z 2.0 platform and pioneering work on mesoporous carbon-nickel silver powder-PVA coated actuators, addressing critical challenges such as power consumption and actuation efficiency in electrothermal systems. Collectively, these efforts reflect Song's commitment to bridging biomimetic design with practical engineering solutions, positioning him as a researcher with broad potential impact across human augmentation, safe robotics, and next-generation soft actuator technologies.