Xuejie Wang
Papers
2
Total Citations
7
H-Index
2
About
Xuejie Wang’s research lies at the intersection of human-centered design and industrial robotics, with a focus on how users perceive and interact with robotic systems. Her work explores the construction of perceptual intention spaces—a framework that integrates both user and expert perspectives to guide the aesthetic and functional design of industrial robots. In her most-cited paper, “Study on the Perceptual Intention Space Construction Model of Industrial Robots Based on ‘User + Expert’” (2016, 5 citations), Wang proposes a novel model that bridges subjective user impressions with objective design parameters, enabling robots to better align with human expectations. A related study, “Research on modeling design of industrial robot based on perceptual image” (2016, 2 citations), further develops these ideas by translating perceptual imagery into tangible design features. Though her citation counts are modest, Wang’s contributions are foundational in the emerging field of perceptual robotics, offering a systematic approach to human-robot interaction that prioritizes user experience. Her work is particularly valuable for researchers and students interested in the cognitive and emotional dimensions of robotic design, providing a roadmap for creating more intuitive and user-friendly industrial machines.
Research Focus
Key Achievements
Top Papers
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- 2