Zheng-Han Shi

National Formosa University

Papers

2

Total Citations

4

H-Index

2

About

Zheng-Han Shi is a robotics and automation researcher whose work focuses on integrating machine learning and advanced sensing technologies for intelligent robotic systems. His key research areas include robot diagnostics, 3D vision-guided manipulation, and automated control systems. In his 2019 study on machine learning approaches for robot diagnostic systems, Shi developed a novel feature algorithm using acoustic filtering techniques within an industrial embedded Compact-RIO environment, enabling more accurate fault diagnosis in robotic platforms. His 2020 work on 3D cameras and multi-angle gripping control advanced robotic arm automation by integrating depth-sensing cameras with network-based image processing for real-time workpiece identification and path planning. Though early in his career, Shi's contributions demonstrate a practical engineering focus on bridging computer vision, machine learning, and industrial robotics. His work on acoustic-based diagnostics and 3D vision-guided manipulation provides foundational methodologies for developing more autonomous and reliable robotic systems in manufacturing environments, with potential applications in quality control and flexible automation.

Research Focus

Key Achievements

2
H-Index
2
Papers
4
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Machine learning approach for robot diagnostic system
2 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: National Formosa University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago