Papers
6
Total Citations
92
H-Index
4
About
Shaqi Luo is a robotics researcher whose work spans human-robot interaction, intelligent control systems, and medical robotics — fields where precision, safety, and adaptability are paramount. Luo's most impactful contribution, "Human–Robot Shared Control Based on Locally Weighted Intent Prediction for a Teleoperated Hydraulic Manipulator System" (2022, 63 citations), established a sophisticated framework for improving operational safety and efficiency in demanding, unstructured environments such as rescue response and underwater exploration. This work highlights Luo's expertise in bridging human intent recognition with robust control architectures for heavy-duty systems. Beyond teleoperation, Luo has made significant inroads in autonomous medical robotics, particularly ultrasound scanning systems. Notable recent contributions include a large-scale learning-based robotic system targeting expert-level carotid ultrasonography, and a unified interaction control framework enabling safe, human-intention-aware robotic ultrasound scanning — both addressing critical global shortages of skilled sonographers. Luo's earlier work on hydraulic manipulator damping compensation further demonstrates a strong foundation in dynamic control theory. Collectively, Luo's research reflects a compelling vision: creating intelligent, human-centric robotic systems capable of operating safely and effectively in high-stakes real-world environments, earning recognition across both industrial robotics and medical automation communities.
Research Focus
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Top Papers
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