Rundong Li
Papers
1
Total Citations
5
H-Index
1
About
Rundong Li is a researcher specializing in robotics perception, sensor fusion, and 3D computer vision. His work focuses on developing robust calibration and mapping techniques for autonomous systems. Li’s most notable contribution is a novel targetless method for joint intrinsic and extrinsic LiDAR-camera calibration, introduced in his 2023 paper “Joint Intrinsic and Extrinsic LiDAR-Camera Calibration in Targetless Environments Using Plane-Constrained Bundle Adjustment.” This approach leverages planar features in the scene to simultaneously calibrate both sensor intrinsics and extrinsics without requiring special calibration targets, significantly improving flexibility and accuracy in real-world deployments. By combining LiDAR point cloud measurements with visual points derived from the same planes, the method achieves precise alignment through plane-constrained bundle adjustment. With 5 citations in a short time, this work has already gained attention for addressing a critical bottleneck in multi-sensor systems. Li’s research has direct applications in autonomous driving, robotics, and augmented reality, where accurate sensor fusion is essential. His contributions advance the state of the art in targetless calibration, offering practical solutions for systems operating in unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1