Papers

7

Total Citations

73

H-Index

4

About

Daxian Hao is a leading researcher in robotic machining, with a primary focus on high-speed robotic milling, chatter stability, and the automation of composite material processing. His most impactful work, "Experimental study of stability prediction for high-speed robotic milling of aluminum" (2019, 39 citations), provides critical experimental validation that regenerative chatter theory, long established for CNC machine tools, is indeed applicable to robotic milling—a topic of significant debate. This contribution directly addresses the stability challenges that limit robot adoption in precision manufacturing. Hao further advances the field by developing a combined calibration method for workpiece positioning in robotic machining systems (2025), integrating vision-based simplicity with contact-based precision to meet the demanding tolerances of large aerospace components. His research also explores structural optimization of polishing robots and the application of robotics in composite material processing, highlighting the trend toward automation in high-value industries. With a growing citation record and work spanning from foundational chatter modeling to practical calibration algorithms, Hao’s research is pivotal for enabling robots to achieve the accuracy and stability required for industrial-scale machining.

Research Focus

Key Achievements

4
H-Index
7
Papers
73
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Experimental study of stability prediction for high-speed robotic milling of aluminum
39 citations · 2019
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Beihang University, Huazhong University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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