Papers
4
Total Citations
28
H-Index
3
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
Top Papers
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- 3Multiagent Rollout with Reshuffling for Warehouse Robots Path Planning4 citations · 2023
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