Kazuya Okawa
Papers
4
Total Citations
57
H-Index
4
About
Kazuya Okawa’s research lies at the intersection of field robotics, automation, and human skill training, with a focus on solving real-world industrial challenges. His most influential work tackles the complex path planning for wheel loader robots in mining operations, where he pioneered the use of Genetic Algorithms to optimize scooping and loading motions—a contribution that has garnered 24 citations and addresses a critical demand for open-pit mine automation. In mobile robotics, Okawa has made significant strides in self-localization, developing a three-tiered system that fuses 3D environmental maps with gyro-odometry (18 citations) and later refining map-matching with the downhill simplex method for robust indoor-outdoor navigation (6 citations). Beyond autonomous systems, he has advanced human-centered technology with a virtual reality training system for manual arc welding (9 citations), targeting the persistent need for skilled welders in custom manufacturing. Okawa’s work is notable for its practical impact, bridging optimization algorithms, sensor fusion, and immersive training to enhance both robotic autonomy and human expertise in demanding industrial settings.
Research Focus
Key Achievements
Top Papers
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- 3Simple Virtual Reality Skill Training System for Manual Arc Welding9 citations · 2014
- 4