Papers
4
Total Citations
22
H-Index
3
About
Xun Wang is a pioneering researcher in human-robot interaction (HRI) and autonomous robotic systems, with a career spanning over a decade of impactful contributions. His work focuses on three key areas: real-time human-robot coaching interfaces, safe robot task planning using large pre-trained models, and multi-robot coordination for target tracking. Wang’s 2012 paper on a full-body control interface for interactive coaching systems laid foundational groundwork in intuitive HRI, earning 7 citations. He later advanced cooperative robotics with a virtual force approach for standoff target tracking (2016, 6 citations), enabling multiple robots to collaboratively monitor stationary targets with enhanced stability. Most notably, his recent 2025 work on "Safe Planner" (6 citations) addresses a critical challenge in autonomous robotics—integrating safety awareness into large pre-trained models for long-horizon task planning, a breakthrough that promises to make AI-driven robots more reliable in complex, real-world environments. Wang also developed a methodology to quantify human-robot interaction forces for rehabilitation robots (2025, 3 citations), improving comfort assessment in stroke therapy devices. With a consistent focus on safety, adaptability, and human-centered design, Wang’s research bridges theoretical advances and practical applications, influencing both robotics and rehabilitation engineering.
Research Focus
Key Achievements
Top Papers
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