Papers

1

Total Citations

26

H-Index

1

About

Shiqi Lin is a leading researcher in robotics and autonomous systems, with a primary focus on LiDAR-based Simultaneous Localization and Mapping (SLAM). His work addresses critical challenges in enabling reliable, real-time navigation for autonomous vehicles and mobile robots. Lin’s most notable contribution is the development of a novel LiDAR SLAM system that introduces geometry feature group-based stable feature selection and a three-stage loop closure optimization framework. This approach significantly enhances robustness and accuracy in complex, unstructured environments where traditional SLAM methods often fail. His landmark 2023 paper on this system has already garnered 26 citations, reflecting its immediate impact on the field. By tackling the limitations of LiDAR SLAM in diverse real-world scenarios, Lin’s research is paving the way for more dependable autonomous navigation, from urban driving to off-road exploration. His work stands out for its practical, engineering-driven solutions that bridge the gap between theoretical SLAM algorithms and deployable robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
26
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
A LiDAR SLAM System With Geometry Feature Group-Based Stable Feature Selection and Three-Stage Loop Closure Optimization
26 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Science and Technology of China

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago