Yingze Xie

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About

Yingze Xie is a robotics researcher whose work centers on the kinematics and control of redundant manipulators, with a particular focus on solving the complex inverse kinematics problem for high-degree-of-freedom systems. In his most-cited work, "A Synthetic Inverse Kinematic Algorithm for 7-DOF Redundant Manipulator" (2018, 15 citations), Xie developed a novel hybrid approach that combines the damped least-squares method with the Newton-Raphson iteration method. This synthetic algorithm effectively addresses the numerical stability and singularity challenges inherent in computing solutions for 7-DOF redundant arms, offering a practical and computationally efficient framework for real-time robotic control. The algorithm was specifically validated on a manipulator designed and built in his laboratory, demonstrating its applicability to physical hardware. While still early in his career, Xie’s contribution provides a valuable tool for researchers and engineers working on dexterous manipulation, human-robot collaboration, and industrial automation, where redundant degrees of freedom are essential for flexibility and obstacle avoidance. His work represents a meaningful step toward more reliable and robust motion planning for complex robotic systems.