Papers

2

Total Citations

13

H-Index

2

About

Yong Yue is a leading researcher at the intersection of agricultural robotics and sustainable manufacturing, whose work advances intelligent automation in both food production and industrial recycling. His primary research areas include deep learning-based computer vision for harvesting robots and human-robot collaborative systems for disassembly tasks. Yue’s major contribution lies in developing perception systems that enable robots to accurately detect and assess produce in complex field environments—a critical step toward addressing global labor shortages in agriculture. His comprehensive review on deep learning for produce perception (2025, 11 citations) synthesizes cutting-edge algorithms and identifies key challenges, serving as a foundational resource for the field. Additionally, Yue has pioneered novel approaches to battery disassembly, using Stackelberg game theory and multi-agent deep reinforcement learning to optimize human-robot collaboration in recycling retired power batteries (2025, 2 citations). This work directly supports the circular economy by improving efficiency and safety in handling hazardous materials. Through these contributions, Yue demonstrates how advanced AI can transform both food security and sustainable manufacturing, making him a notable figure in robotics research.

Research Focus

Key Achievements

2
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Deep learning in produce perception of harvesting robots: A comprehensive review
11 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Xi’an Jiaotong-Liverpool University, Wuhan University of Science and Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago