Jianchuan Tang

University of Electronic Science and Technology of China

Papers

Total Citations

H-Index

About

Jianchuan Tang is a rising researcher at the intersection of Augmented Reality (AR) and Human-Robot Interaction (HRI), with a focused interest in enhancing the ergonomics and psychological comfort of collaborative tasks. His most cited work, "Improving Interaction Comfort in Authoring Task in AR-HRI through Dynamic Dual-Layer Interaction Adjustment" (2024, 2 citations), addresses a critical gap in AR-HRI: the discomfort users experience when selecting interaction methods during authoring tasks. Tang’s key contribution lies in proposing a **dynamic dual-layer interaction adjustment** framework, which intelligently adapts between different interaction modalities (e.g., gesture-based versus menu-based) based on real-time user context and task demands. This work builds on prior research into shared robot intent and visual feedback, but uniquely targets the *authoring* phase—a cognitively demanding stage often overlooked in comfort studies. By demonstrating that adaptive interaction can reduce cognitive load and improve user satisfaction, Tang provides a practical pathway toward more intuitive and comfortable AR-driven collaborative robotics. While his citation count is currently modest, the novelty of his approach positions him as an emerging voice in the field, with potential for significant impact as AR-HRI systems become more prevalent in industrial and domestic settings.