Papers
13
Total Citations
347
H-Index
8
About
Hailong Xie is a leading researcher at the intersection of robotic manufacturing and intelligent automation, with key contributions in robotic milling, grinding, and human-robot collaboration. His work addresses critical challenges in industrial robotics, particularly the low stiffness and positioning accuracy that limit machining quality for freeform surfaces. Xie pioneered stiffness-optimized toolpath generation, introducing region-based partitioning and posture optimization methods that significantly enhance robotic machining precision. His 2021 paper on robot posture and workpiece setup optimization, with 96 citations, is a foundational reference in the field. Xie’s research extends to robotic belt grinding, where he developed interference-free, posture-smooth toolpath planning, and adaptive human-robot collaboration frameworks for complex workpieces. Notably, his 2024 work on the “Industrial Metaverse” (31 citations) explores proactive human-robot collaboration, envisioning flexible, human-centric manufacturing systems. With over 340 total citations, Xie’s profile error estimation and hierarchical compensation methods further advance robotic surface machining accuracy. His innovative force feedback models for virtual robot teaching and collision detection in complex environments demonstrate a commitment to practical, industry-ready solutions. Xie’s work is essential reading for researchers in robotic manufacturing, offering both theoretical insights and actionable methodologies for next-generation automation.
Research Focus
Key Achievements
Top Papers
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- 3A robotic belt grinding approach based on easy-to-grind region partitioning38 citations · 2020
- 4Industrial Metaverse: A proactive human-robot collaboration perspective31 citations · 2024
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- 9A novel force feedback model for virtual robot teaching of belt lapping8 citations · 2017
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