Kenya Yoshitugu
Papers
1
Total Citations
2
H-Index
1
About
Kenya Yoshitsugu is a researcher focused on advancing the precision and adaptability of industrial robotics, particularly through the integration of machine learning and automation. His key research areas include robotic positioning error analysis, offline teaching methods, and the application of convolutional neural networks (CNNs) to manufacturing systems. His most notable contribution, "Finding Features of Positioning Error for Large Industrial Robots Based on Convolutional Neural Network" (2021), addresses a critical bottleneck in flexible production: the low accuracy of robot end-effector position and posture during offline programming. By leveraging CNNs to identify and characterize error patterns, Yoshitsugu’s work offers a pathway toward more reliable, variable-production robotic systems without the need for manual teaching playback. While his citation count is currently modest, his research tackles a foundational challenge in Industry 4.0—bridging the gap between simulation and real-world precision. His work is particularly relevant for engineers and researchers seeking to enhance robot autonomy in dynamic manufacturing environments, positioning him as an emerging voice in intelligent robotics and precision automation.
Research Focus
Key Achievements
Top Papers
- 1