Papers

6

Total Citations

173

H-Index

5

About

Shiqing Xin is a leading researcher in computer graphics, robotics, and geometric computing, whose work bridges fundamental theory with practical applications in 3D reconstruction and robotic manipulation. His most impactful contribution is the development of a multi-robot collaborative scanning approach for dense 3D reconstruction of unknown indoor scenes, a paper that has garnered 109 citations and pioneered efficient coordination strategies for autonomous scanning teams. In visual SLAM, Xin has advanced robustness by introducing dynamic object removal techniques, addressing a critical limitation of traditional algorithms that assume static environments. His theoretical work on the extended Xin–Wang algorithm for computing geodesic offsets on triangle meshes (27 citations) provides efficient solutions for geometric processing, while his research on caging loops in shape embedding space offers a novel framework for synthesizing feasible robotic grasps by decoupling grasp planning from surface geometry. Additionally, Xin has contributed probability-driven methods for point cloud registration in indoor scenes. His work consistently combines rigorous mathematical foundations with real-world applicability, making him a key figure in the intersection of geometry processing and autonomous robotics.

Research Focus

Key Achievements

5
H-Index
6
Papers
173
Total Citations
29
Avg Citations/Paper
🏆 Most Cited Paper
Multi-robot collaborative dense scene reconstruction
109 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Shandong University, Nanyang Technological University, Shandong University of Science and Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago