Papers
3
Total Citations
20
H-Index
2
About
Xun Li is a versatile robotics and wireless systems researcher whose work spans UAV-assisted IoT networks, surgical robotics, and industrial automation. His most influential contribution, "Efficient Trajectory Planning for Optimizing Energy Consumption and Completion Time in UAV-Assisted IoT Networks" (2023, 11 citations), addresses a critical bottleneck in next-generation mobile networks by developing intelligent path-planning algorithms that simultaneously minimize UAV energy use and task completion time — a dual-objective challenge with significant practical implications for smart infrastructure deployment. Complementing this, his 2024 work on the 3-RRRS needle biopsy robot (7 citations) demonstrates his breadth in medical robotics, introducing a compact six-degree-of-freedom system designed to enhance precision and reduce surgeon fatigue in minimally invasive procedures. His earlier research on substation maintenance robots (2017) reflects a longstanding interest in deploying autonomous systems in hazardous real-world environments. Across these domains, Li consistently tackles problems at the intersection of mechanical design, control systems, and networked intelligence, making his work relevant to students and engineers working in robotics, IoT, and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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