Siqin Yang

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About

Siqin Yang is advancing the frontier of medical robotics, with a primary focus on automated robotic ultrasound imaging and cooperative manipulator control. Their most influential work, "Task Space Compliant Control and Six-Dimensional Force Regulation Toward Automated Robotic Ultrasound Imaging" (2023, 22 citations), introduces a pioneering control framework that enables compliant motion and precise six-dimensional force regulation—a critical capability for safe, high-quality autonomous ultrasound scans. This contribution directly addresses the challenge of maintaining consistent contact force and orientation during robotic tissue imaging, enhancing both diagnostic reliability and patient safety. Yang also explores cooperative human-robot interaction through "Cooperative Manipulator Control Based on IgH Ethercat Master" (2023) and tackles disturbance rejection in surgical contexts with "A Disturbance Compensation Method Using Adaptive Neural Network for Robotic Manipulator" (2023). By integrating adaptive neural networks into force control, Yang’s work improves precision when robots contact hard tissues like bone, a key requirement for orthopedic and dental procedures. With a research trajectory that bridges control theory, human-robot collaboration, and clinical application, Siqin Yang is shaping the next generation of intelligent, force-sensitive surgical and diagnostic robots.