Ting Fei

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Total Citations

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About

Ting Fei is a pioneering researcher in the field of robotic musical performance, with a particular focus on the intersection of traditional Chinese instrumental art and advanced robotics. Their primary research areas include anthropomorphic robotic control systems, redundant manipulator kinematics, and neural network-based decision-making for performance robots. Fei’s most notable contribution is the development of a specialized dulcimer-playing robot, a groundbreaking project that bridges cultural heritage with cutting-edge engineering. Their 2017 paper on the performance control system of this robot (4 citations) introduced an innovative task assignment method tailored to the mechanical constraints of the dulcimer. Building on this, Fei’s 2019 work employed neural networks to enable online anthropomorphic decision-making for a dual-arm version of the robot, allowing it to learn and replicate human playing behaviors autonomously. Additionally, Fei has advanced the control of redundant manipulators under joint limits, proposing a novel method that combines weighted least-norm and gradient projection techniques. While their citation counts are modest, Fei’s work represents a unique and creative fusion of robotics, music, and cultural preservation, offering valuable insights for researchers in human-robot interaction and artistic robotics.