Papers

7

Total Citations

132

H-Index

4

About

Dr. Prasarn Kiddee is a leading researcher in intelligent robotics and automated welding systems, whose work bridges advanced computer vision with practical industrial applications. His primary research areas include weld seam tracking, robotic vision systems, and omnidirectional vehicle control. Dr. Kiddee’s most impactful contribution is his development of an automated weld seam tracking system for thick plates using cross mark structured light, a method that has garnered 96 citations and revolutionized precision in heavy-duty welding. He has also pioneered techniques for visual recognition of lap joint endpoints in welding robots, enhancing automation reliability. Beyond welding, Dr. Kiddee has advanced obstacle avoidance and person-following capabilities for omnidirectional vehicle robots, integrating range sensors and stereo vision for safer, more adaptive navigation. His notable achievements include a real-time feature detection method employing hierarchical strategies and modified Kalman filters for robust seam tracking, as well as a simple yet effective structured light calibration technique for welding robots. With a portfolio of highly cited papers and practical innovations, Dr. Kiddee’s work continues to shape the future of automated manufacturing and intelligent robotics, offering scalable solutions for industry and research alike.

Research Focus

Key Achievements

4
H-Index
7
Papers
132
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
An automated weld seam tracking system for thick plate using cross mark structured light
96 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Chinese Academy of Sciences, Polytechnic University, Tokyo Polytechnic University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago