Papers

2

Total Citations

18

H-Index

2

About

Eduardo do Amaral Leivas is a researcher specializing in intelligent robotic welding systems, with a focus on vision-based automation for industrial applications. His work centers on developing Vision-Based Measurement (VBM) systems that enhance the precision and adaptability of robotic welding, particularly in demanding environments like shipbuilding. Leivas’s most cited paper, “Vision-based system for welding groove measurements for robotic welding applications” (2016, 14 citations), introduces a system that uses a CMOS camera and algorithms to measure beveled edges, improving weld quality control. His follow-up study, “Automated Control Module Based on VBM for Shipyard Welding Applications” (2015, 4 citations), demonstrates a practical implementation on the Bug-O Matic Weaver robot, integrating FPGA-based processing for real-time automation. These contributions address critical challenges in meeting international welding standards and reducing manual oversight. Leivas’s work is notable for bridging computer vision and industrial robotics, offering scalable solutions for complex tasks like shipyard welding. His research has implications for advancing smart manufacturing, making him a key figure in the field of automated welding systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
18
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Vision-based system for welding groove measurements for robotic welding applications
14 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of Rio Grande and Rio Grande Community College, Universidade Federal do Rio Grande

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago