Papers

2

Total Citations

112

H-Index

2

About

Dr. Yanan Song is a leading researcher in robotic manipulation and computer vision, with a focus on intelligent grasp detection for complex, real-world environments. Her major contributions center on developing deep learning-based frameworks that enable robots to perceive and interact with objects more accurately and efficiently. Her most influential work, "A novel robotic grasp detection method based on region proposal networks" (2020), has garnered 104 citations, introducing a pioneering approach that leverages region proposal networks to identify feasible grasp configurations directly from visual input. Building on this, her subsequent study, "A novel vision-based multi-task robotic grasp detection method for multi-object scenes" (2022), extends the methodology to handle cluttered, multi-object settings, demonstrating her commitment to advancing robotic autonomy in practical applications. Dr. Song's research has significant implications for industrial automation, logistics, and assistive robotics, where reliable grasping is critical. Her work is recognized for its technical rigor and practical impact, making her a notable figure in the intersection of robotics and artificial intelligence.

Research Focus

Key Achievements

2
H-Index
2
Papers
112
Total Citations
56
Avg Citations/Paper
🏆 Most Cited Paper
A novel robotic grasp detection method based on region proposal networks
104 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Huazhong University of Science and Technology, Zhejiang University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago