About

Xiaoqi Chen is a distinguished robotics and automation researcher whose work spans human-robot collaboration, agricultural robotics, robotic manufacturing, and brain-computer interfaces. With a career marked by consistently influential contributions, Chen has accumulated nearly 1,300 citations across his most recognized works alone, reflecting the broad reach of his research. Chen's early work addressed precision manufacturing challenges, with his robotic grinding and polishing systems for turbine vane overhaul (2002, 168 citations) and his SMART robotic system for 3D profile airfoil repair (2003, 121 citations) establishing him as a pioneer in automated aerospace maintenance. His 2008 literature review on human-robot collaboration (304 citations) remains a landmark reference, synthesizing research directions and introducing augmented reality frameworks that continue to influence the field. Beyond manufacturing, Chen has demonstrated remarkable versatility — developing an intelligent grape vine pruning robot (2016, 218 citations) that combines trinocular stereo vision and AI planning, and exploring EEG-controlled robotic systems through brain-computer interfaces (2020, 75 citations). His recent work applying machine learning techniques like XGBoost and extreme learning machines to robotic belt grinding reveals a forward-thinking integration of artificial intelligence into precision automation, cementing his legacy as an innovator bridging traditional robotics with emerging intelligent systems.

Research Focus

Key Achievements

29
H-Index
107
Papers
2,757
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Human-Robot Collaboration: A Literature Review and Augmented Reality Approach in Design
304 citations · 2008
📈 Most Prolific Year: 2018 (11 Papers)
🤝 Key Collaborators: 189
🏛 Institutions: University of Canterbury, Singapore Institute of Manufacturing Technology, Shanghai Jiao Tong University, Swinburne University of Technology, Tianjin University of Technology, South China University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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