Papers
1
Total Citations
5
H-Index
1
About
Junnan Ye is a researcher whose work bridges human-centered design and industrial robotics, with a focus on perceptual intention modeling. Ye’s most-cited paper, “Study on the Perceptual Intention Space Construction Model of Industrial Robots Based on ‘User + Expert’,” published in 2016, proposes a novel framework that integrates user and expert feedback to enhance robot interaction. This work, with 5 citations, lays foundational groundwork for understanding how robots can better interpret human intent in manufacturing and collaborative settings. Ye’s contributions are particularly relevant to the growing field of human-robot interaction, where intuitive control and adaptive behavior are critical. By combining cognitive models with engineering design, Ye offers a pathway toward more responsive and user-friendly industrial robots. While the citation count is modest, the research is notable for its interdisciplinary approach, merging psychology, ergonomics, and robotics. Ye’s work is especially valuable for students and researchers exploring how to embed human perceptual cues into robotic systems, making industrial automation safer and more intuitive. This early study remains a stepping stone for those seeking to advance intention-driven robot design.
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Top Papers
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