Can-yu Huang
Papers
1
Total Citations
4
H-Index
1
About
Dr. Can-yu Huang is a researcher at the forefront of industrial robotics and intelligent manufacturing, with a specialized focus on computer vision and deep learning for automation. Their most notable contribution is a pioneering method for detecting key points on chemical barrel valve handwheels, integrating Keypoint R-CNN with MobileNetV3 to enable robots to precisely identify position and rotation angles during valve operation. This work, published in 2023 and garnering 4 citations, directly addresses a critical industrial challenge: preventing mechanical interference between robot grippers and handwheels during automated opening and closing processes. By combining high-accuracy keypoint detection with the computational efficiency of MobileNetV3, Huang's approach balances precision with real-time performance, making it viable for deployment in chemical processing environments. This research represents a significant step toward safer, more reliable industrial automation, where robots must interact with existing manual infrastructure. Dr. Huang's work exemplifies the practical application of advanced neural network architectures to solve tangible manufacturing problems, bridging the gap between cutting-edge computer vision research and real-world industrial requirements.
Research Focus
Key Achievements
Top Papers
- 1