Guangming Yuan

Hebei University of Technology, Space Engineering University

Papers

Total Citations

H-Index

About

Guangming Yuan is a robotics researcher whose work bridges the gap between autonomous systems and human-robot interaction, with a particular focus on wheeled mobile robots and sensor-based control. His early research introduced an innovative "Mending Robot" that combined hearing capabilities with virtual reality teleoperation, using microphone arrays and time delay of arrival (TDOA) estimation to localize leak points—a creative fusion of auditory sensing and robotic manipulation. More recently, Yuan has advanced the field of mobile robot tracking control, addressing persistent challenges in dynamic modeling under nonholonomic constraints. His 2020 work on RBF network supervisory control proposes a neural network-based approach to improve trajectory tracking accuracy for wheeled robots used in industrial, agricultural, and defense applications. While his citation counts remain modest (2 citations each), Yuan's contributions demonstrate a thoughtful progression from sensor-integrated manipulation to intelligent control systems, reflecting the evolving priorities of robotics research over the past decade. His work on auditory localization in robotics represents an early exploration of multi-modal sensing that has since become increasingly relevant in autonomous systems.