Cui Xie

Papers

Total Citations

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About

Cui Xie is a researcher whose work bridges human-computer interaction and robotics, with a focus on intuitive, conflict-free gesture recognition. Their key research areas include skeleton-based gesture analysis, robot control interfaces, and natural human-robot interaction. Xie’s most notable contribution is the development of a skeleton-guided, conflict-free hand gesture recognition system for robot control, published in 2020. This work addresses a critical challenge in the field: the ambiguity and conflicting gesture interpretations that often arise in skeleton-based interaction. By leveraging Kinect-derived skeleton data, Xie’s approach aligns more closely with natural human behaviors than traditional methods, offering a more seamless and reliable way for operators to command robots. The paper has garnered 7 citations, reflecting its early impact on improving the robustness of gesture-based control systems. Xie’s research is particularly valuable for applications in assistive robotics, manufacturing, and human-robot collaboration, where intuitive and error-free interaction is essential. Their work represents a meaningful step toward making robot control as natural as human communication.