Ziliang Miao
Papers
2
Total Citations
23
H-Index
2
About
Ziliang Miao is a robotics researcher whose work centers on sensor fusion, 3D mapping, and calibration for autonomous systems. His major contributions lie in developing novel methods to integrate omnidirectional cameras with non-repetitive LiDAR sensors, addressing critical challenges in perception for mobile robots. His most cited work, "Coarse-to-Fine Hybrid 3D Mapping System With Co-Calibrated Omnidirectional Camera and Non-Repetitive LiDAR" (2023, 18 citations), introduces a robotic platform with a full 360° field-of-view sensor suite, featuring an automatic targetless co-calibration method that exploits the unique scanning pattern of non-repetitive LiDAR. This innovation enables robust, accurate 3D mapping without requiring calibration targets. Miao further advanced the field with "Joint Intrinsic and Extrinsic LiDAR-Camera Calibration in Targetless Environments Using Plane-Constrained Bundle Adjustment" (2023, 5 citations), which leverages planar scene features to simultaneously calibrate both intrinsic and extrinsic parameters. His work is notable for pushing toward practical, deployment-ready calibration solutions that eliminate the need for specialized calibration targets, significantly reducing setup complexity in real-world robotics applications.
Research Focus
Key Achievements
Top Papers
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- 2