Papers
4
Total Citations
130
H-Index
4
About
Zhengxu Zhao is a leading researcher in human-robot interaction and augmented reality (AR)-enhanced robotic systems. His work focuses on developing intuitive, safe, and efficient methods for robot teaching and teleoperation, bridging the gap between human intent and machine action. Zhao’s major contributions include pioneering AR-based robot teleoperation using RGB-D imaging and attitude teaching devices, which has garnered 58 citations. He also advanced collision detection interfaces for AR-based interactive teaching, cited 49 times, and introduced innovative systems that recognize hand-robot contact states and motion intentions for more natural robot guidance. More recently, Zhao has explored path reinforcement learning for manual guidance and robot path tracking, demonstrating his commitment to integrating machine learning with real-time human control. His research has significant implications for manufacturing, education, and assistive robotics, enabling non-experts to program and interact with robots safely. With a growing citation record and a focus on practical, user-centered solutions, Zhao is shaping the future of collaborative robotics and intelligent automation.
Research Focus
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