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About

Yuling Li is a robotics and control systems researcher whose work centers on bilateral teleoperation, adaptive control, and multi-robot coordination. With a focused body of research developed primarily between 2018 and 2020, Li has made meaningful contributions to one of robotics' most challenging domains: enabling reliable, synchronized control of robotic systems across imperfect communication networks. Li's most influential work addresses the fundamental difficulties that arise in teleoperation — namely communication delays, dynamic uncertainties, and limited bandwidth. Her 2019 paper on bilateral teleoperation of multiple robots under scheduling communication (35 citations) tackled the complex problem of coordinating multiple slave robots from a single master over delayed, sampled-data networks. Complementing this, her 2018 adaptive control framework (33 citations) introduced a novel approach to master-slave task-space synchronization under both kinematic and dynamic uncertainties with time-varying delays — a significant advance over prior methods. Li further extended her contributions by incorporating prescribed performance constraints using barrier Lyapunov functions and leveraging multiple neural networks to approximate unknown robot dynamics. Collectively accumulating nearly 100 citations, her research provides practical, mathematically rigorous solutions that advance the safety and reliability of remote robotic operations in real-world environments.