Bobby K Pappachan
Papers
5
Total Citations
66
H-Index
4
About
Bobby K Pappachan is a researcher specializing in human-machine interfaces, assistive robotics, and intelligent manufacturing systems, with a focus on integrating real-time sensor data and machine learning for advanced robotic control. His major contributions include developing multi-modal wearable systems for upper limb motion trajectory prediction, where he compared various machine learning techniques to enhance motion intention detection—a critical component for assistive robots. This work, published in 2021, has garnered 27 citations, reflecting its impact on human-robot interaction. Pappachan also pioneered frequency domain analysis of sensor data for event classification in real-time robot-assisted deburring, addressing big data challenges in manufacturing (20 citations). His research on robot control and decision-making through sensor monitoring for Industry 4.0 implementation in aerospace component manufacturing (10 citations) demonstrates practical applications in high-precision environments. Additionally, he analyzed contact conditions in robotic abrasive belt grinding using dynamic pressure sensors, contributing to fine-tolerance finishing processes. Pappachan’s work bridges the gap between cyber-physical systems and manufacturing, with notable achievements in applying spectral analysis for event classification in robotic finishing processes. His interdisciplinary approach has significant implications for smart manufacturing and assistive technologies.
Research Focus
Key Achievements
Top Papers
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