Jiuya Song

Papers

Total Citations

H-Index

About

Jiuya Song is a leading researcher in the field of robotic grasping and underactuated mechanisms, with a focus on developing novel, efficient, and anthropomorphic robot hands and fingers. Their work centers on advancing hybrid grasping modes that combine coupled and self-adaptive (COSA) or coupled and active (CA) behaviors, enabling robotic digits to both mimic human-like motion and automatically conform to object shapes. Song’s most influential contribution is the **PASA Hand** (2016), a parallel and self-adaptive underactuated hand utilizing gear-link mechanisms, which has garnered **34 citations** and set a benchmark for simplifying complex transmission systems. This work addresses critical limitations in traditional designs—such as excessive springs, multiple transmission sets, and high power consumption—by introducing a streamlined, energy-efficient architecture. Further innovations include the **COSA-LET finger** (2017), which employs a linear empty-trip transmission to reduce mechanical complexity, and the **CA robot finger** (2016), which pioneers a hybrid coupled-active mode for improved adaptability. Song’s research is highly regarded for bridging the gap between dexterity and simplicity, offering practical solutions for prosthetic and industrial robotic applications. Their achievements underscore a commitment to creating more intuitive, robust, and human-like robotic hands.