Qiao Sun

Papers

1

Total Citations

2

H-Index

1

About

Qiao Sun is a robotics researcher specializing in robot manipulation, grasp planning, and generative modeling for autonomous systems. Their work sits at the intersection of deep learning and robotic perception, with a particular focus on enabling robots to interact effectively with objects in real-world environments using partial, single-view observations. Sun's most notable contribution is the Grasp Diffusion Network, a sophisticated approach that applies diffusion models operating over the SE(3) manifold — combining rotational (SO(3)) and translational (R³) spaces — to learn grasp pose generators from partial point clouds. This work addresses a fundamental challenge in robot manipulation: reliably grasping novel objects when only incomplete 3D information is available from a single camera viewpoint. By leveraging simulation-generated datasets and conditional generative modeling, the framework enables rapid, high-quality grasp synthesis during deployment. Although still a recently published work with 2 citations, the research tackles one of the most practically significant bottlenecks in robotic manipulation pipelines. Sun's integration of state-of-the-art diffusion-based generative techniques with SE(3) geometry reflects a growing and impactful trend in robotics research, positioning their contributions as timely and relevant to both academic and industrial communities advancing autonomous manipulation.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 6

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago