About

Yuchao Li is a robotics researcher whose work bridges perception, planning, and manipulation for autonomous systems in complex, real-world environments. His primary research areas include robotic grasping, agricultural robotics, multi-agent path planning, and reinforcement learning for assembly tasks. Li’s most influential work, the Double Strand robotic Grasp Detection Network (DSNet), introduces a novel encoder-decoder architecture that fuses a transformer branch with a U-Net branch via cross-attention, enabling the model to reconcile local and global features for robust grasp detection. This paper has already garnered 18 citations since its 2024 publication, signaling strong impact in the computer vision and robotics community. In agricultural robotics, Li proposed a YOLOv5-based method for fruit tree trunk recognition and visual navigation, enabling robots to operate reliably in cluttered orchard environments. He has also contributed to warehouse automation with a multiagent rollout algorithm incorporating reshuffling for efficient path planning among large robot fleets, and to industrial manufacturing with a visuo-tactile reinforcement learning framework for high-precision terminal assembly. Li’s work consistently addresses the gap between perception and action, advancing the deployment of intelligent robots in agriculture, logistics, and manufacturing.

Research Focus

Key Achievements

3
H-Index
4
Papers
28
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
DSNet: Double Strand Robotic Grasp Detection Network Based on Cross Attention
18 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Nanjing University of Information Science and Technology, Henan University of Science and Technology, KTH Royal Institute of Technology, Shanghai Jiao Tong University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago