Danshi Li

Papers

1

Total Citations

2

H-Index

1

About

Danshi Li is a robotics researcher whose work centers on advancing perception and manipulation for industrial automation, with a particular focus on challenging object detection scenarios. His key research areas include 6-DoF grasp and suction detection, transparent object manipulation, and vision-based robotic systems for production lines. Li’s most notable contribution is STOPNet, a multiview-based framework for 6-DoF suction detection specifically designed for transparent objects—a notoriously difficult problem in robotics due to the failure of standard depth sensors on such surfaces. By addressing this gap, his work directly impacts modern manufacturing and logistics, where transparent items like glassware and packaging are common. Though early in his career, with STOPNet already garnering citations, Li’s research demonstrates practical significance by bridging computer vision and industrial robotics. His achievements highlight a commitment to solving real-world automation challenges, making his work essential reading for students and researchers interested in robotic perception, grasping, and industry 4.0 applications.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
STOPNet: Multiview-based 6-DoF Suction Detection for Transparent Objects on Production Lines
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 7

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago