Tomoya Yasunaga
Papers
3
Total Citations
15
H-Index
3
About
Tomoya Yasunaga is a researcher at the forefront of intelligent robotics and computer vision, with a focused expertise in developing fuzzy-based systems for surface characterization. His primary contributions lie in designing robot vision systems capable of recognizing micro-roughness and micro-convex features on arbitrary surfaces—a critical challenge for precision manufacturing and vibration reduction in robotic arms. In his most cited work (2022, 9 citations), Yasunaga introduced a novel fuzzy logic approach that enables robots to adaptively interpret surface textures, significantly improving accuracy over conventional methods. His subsequent studies (each with 3 citations) further validated this system through comparative experiments, demonstrating robust performance across different materials and conditions. By bridging fuzzy inference with real-time visual feedback, Yasunaga’s research offers practical solutions for enhancing robotic dexterity in automated quality control and surface finishing tasks. His work is particularly notable for its experimental rigor, providing clear benchmarks for future advancements in intelligent robotic perception.
Research Focus
Key Achievements
Top Papers
- 1
- 2Design of a Robot Vision System for Microconvex Recognition3 citations · 2022
- 3