Juan Hao

Beijing Institute of Technology

Papers

6

Total Citations

67

H-Index

4

About

Juan Hao is a robotics and automation researcher whose work centers on the integration of industrial robotics with non-destructive testing (NDT) systems, particularly for composite materials with complex curved surfaces. His research addresses a critical challenge in modern manufacturing: how to reliably inspect composite workpieces — increasingly common in aerospace, automotive, and industrial applications — using automated robotic platforms. Hao's most influential contribution is his development of dual-robot ultrasonic NDT systems, where two coordinated robots work in tandem to inspect semi-enclosed and irregularly shaped workpieces. His 2019 paper on this system has accumulated 29 citations, reflecting strong community interest. Complementing this, his work on tool centre point calibration (16 citations) and trajectory planning for probe alignment (10 citations) addresses the precise technical challenges of maintaining ultrasonic probe accuracy during complex robotic motion. Earlier foundational work from 2016 established kinematic constraint frameworks and workpiece frame calibration methods for twin-robot coordination, providing the theoretical backbone for his later applied systems. Across his publication record, Hao has made meaningful contributions to robotic path planning, sensor calibration, and multi-robot coordination — collectively advancing the automation of quality control in composite material manufacturing.

Research Focus

Key Achievements

4
H-Index
6
Papers
67
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Ultrasonic Non-Destructive Testing System of Semi-Enclosed Workpiece with Dual-Robot Testing System
29 citations · 2019
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Beijing Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago