Papers
7
Total Citations
92
H-Index
5
About
Dr. Chenhui Wan is a leading researcher at the intersection of digital twin technology, model-based systems engineering (MBSE), and intelligent robotics, with a particular focus on complex industrial and nuclear fusion applications. His most impactful work, "An effective MBSE approach for constructing industrial robot digital twin system" (2022, 57 citations), provides a foundational methodology for creating high-fidelity digital replicas of robotic systems, addressing critical challenges in product lifecycle management. Dr. Wan has also pioneered the use of large language models in manufacturing, introducing "MASC: Large language model-based multi-agent scheduling chain for flexible job shop scheduling problem" (2025, 10 citations), which represents a novel convergence of AI and production optimization. His sustained contributions to the China Fusion Engineering Test Reactor (CFETR) project are particularly notable, where he has engineered the root joints of the multi-purpose overload robot (2024, 6 citations), developed novel inverse kinematics solutions (2024, 5 citations), and created adaptive motion planning algorithms (2023, 3 citations). Most recently, his work on compensating control delays using transformer-enhanced temporal convolutional networks (2025, 2 citations) demonstrates his ongoing commitment to solving real-time control challenges in extreme environments. Dr. Wan’s research consistently bridges theoretical innovation with practical engineering, making him a pivotal figure in advancing autonomous robotic systems for both industrial and fusion energy applications.
Research Focus
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Top Papers
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