Maochuan Wu

Papers

Total Citations

H-Index

About

Maochuan Wu is a researcher at the forefront of intelligent manufacturing and human-robot collaboration, with a focus on computer vision and biomedical signal processing. His work addresses critical challenges in industrial automation and rehabilitation robotics. In his highly cited 2019 study on robot welding seam tracking, Wu pioneered a multi-feature image recognition approach that leverages the rich data from advanced seam imaging equipment. By moving beyond single-image features, his system significantly enhances the accuracy and robustness of automated welding—a vital contribution to modern industry automation. This work has garnered 5 citations, underscoring its relevance to the field. Wu also advances human-robot interaction (HRI) through his innovative use of surface electromyography (SEMG) signals. In another 2019 paper, he developed a SEMG-angle model based on a Hidden Markov Model (HMM), enabling more intuitive control of exoskeleton robots for rehabilitation. This model bridges the gap between biological signals and robotic motion, offering a pathway to more responsive and adaptive assistive devices. With 2 citations, this work highlights his commitment to creating friendly, effective HRI systems. Wu’s research stands at the intersection of vision-based automation and bio-signal-driven robotics, promising safer, smarter, and more human-centric technologies.