Weigang Yu
Papers
1
Total Citations
30
H-Index
1
About
Weigang Yu is a leading researcher at the intersection of intelligent manufacturing, human-robot collaboration, and dynamic disassembly systems. His work focuses on developing adaptive frameworks that enable seamless cooperation between humans and robots in complex, evolving industrial environments. Yu’s most notable contribution is the introduction of a novel approach that integrates Multimodal Large Language Models (MLLMs) with Knowledge Graphs (KGs) to reschedule human-robot collaboration tasks under dynamic disassembly scenarios. This pioneering method, detailed in his 2025 paper, has already garnered 30 citations, reflecting its immediate impact on the field. By leveraging MLLMs for real-time reasoning and KGs for structured domain knowledge, Yu’s framework enhances flexibility and efficiency in disassembly processes, addressing critical challenges in sustainable manufacturing and circular economy. His work is highly regarded for bridging artificial intelligence with practical industrial applications, offering scalable solutions for adaptive task allocation. Yu’s research continues to influence the next generation of smart manufacturing systems, making him a key figure in advancing human-robot teamwork in uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1