Zhe Xiao

China University of Geosciences, Intelligent Automation (United States)

Papers

Total Citations

H-Index

About

Zhe Xiao is a pioneering researcher at the intersection of robotics, computer vision, and music technology, whose work focuses on creating intelligent musical robots capable of autonomous performance. His primary research areas include optical music recognition (OMR), robotic kinematics, and visual positioning systems for musical instruments. Xiao’s major contribution lies in developing a real-time OMR system for a dulcimer musical robot, which enables the robot to read and interpret scanned sheet music autonomously—a novel fusion of traditional OMR with robotic control. This work, cited 4 times, represents a significant step toward fully automated musical performance. He further advanced the field by proposing a Particle Swarm Optimization (PSO)-based inverse kinematic solution for the dulcimer robot, addressing the challenge of heterogeneous robots that do not satisfy the Pieper criterion. Additionally, Xiao developed a visual positioning method using an improved Roberts operator to accurately locate dulcimer keys, enhancing the robot’s spatial awareness and intelligence. With a total of 8 citations across his most-cited papers, Xiao’s research is foundational for the emerging field of robotic musicianship, offering practical solutions for real-time, autonomous musical interaction.