Papers

8

Total Citations

104

H-Index

5

About

Xuewen Wang is a pioneering researcher at the intersection of extended reality (XR), human-robot collaboration, and intelligent mining systems. His work is fundamentally reshaping how humans and machines interact in industrial environments, particularly within the emerging framework of the industrial metaverse. Wang’s major contributions include developing a novel XR-based human-robot collaboration assembly system (50 citations) and creating advanced methods for the virtual straightening of scraper conveyors using industrial robot models (22 citations). He has also innovated path planning for hydraulic support mechanisms through extreme learning machines (9 citations) and introduced a multi-agent mutual trust evaluation mechanism for human-robot-XR systems (7 citations). With a growing body of work that bridges Industry 5.0 principles and practical mining operations, Wang’s research has garnered significant attention, including recent studies on AR-assisted motion planning integrating large language models (3 citations) and human-centric decision-making for coal mine auxiliary operations (4 citations). His notable achievements include developing spatial multimodal interaction programming methods and advancing the straightness control of armored face conveyors, positioning him as a key figure in the future of intelligent, human-centered industrial automation.

Research Focus

Key Achievements

5
H-Index
8
Papers
104
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
A new XR-based human‐robot collaboration assembly system based on industrial metaverse
50 citations · 2024
📈 Most Prolific Year: 2025 (4 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Taiyuan University of Technology, Taiyuan Normal University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago