Jian-Chao He
Papers
1
Total Citations
2
H-Index
1
About
Jian-Chao He is a robotics researcher whose work focuses on advancing simultaneous localization and mapping (SLAM) systems, particularly through LiDAR-based perception for large-scale environments. His key research areas include loop closure detection, point cloud registration, and geometric deep learning applied to 3D spatial understanding. He made a significant contribution with his 2025 paper "Large-Scale LiDAR-Based Loop Closing via Combination of Equivariance and Invariance on SE(3)," which addresses two critical subtasks in SLAM: reliably detecting when a robot revisits a location and accurately aligning the corresponding point clouds. By innovatively combining equivariant and invariant geometric properties on the SE(3) Lie group, his work enhances both the robustness and precision of loop closing in expansive, unstructured settings—a longstanding challenge in autonomous navigation. While his citation count is still growing (2 citations for this key paper), the work represents a timely and theoretically grounded advance that bridges group theory and practical robotics. He is emerging as a thoughtful contributor to the SLAM community, with potential for lasting impact on how robots build consistent maps of the world.
Research Focus
Key Achievements
Top Papers
- 1