Cylindrical Scan Context: A Multi-Channel Descriptor for Vertical-Structure-Aware LiDAR Localization

This study introduces Cylindrical Scan Context (CSC), a novel LiDAR descriptor designed to improve robustness and efficiency in GPS-denied or degraded outdoor environments. Unlike the conventional Scan Context (SC), which relies on azimuth-range projection, CSC employs an azimuth-height representation that preserves vertical structural information and incorporates multiple physical channels-range, point density, and reflectance intensity-to capture both geometric and radiometric characteristics of the environment. This multi-channel cylindrical formulation enhances descriptor distinctiveness and robustness against viewpoint, elevation, and trajectory variations. To validate the effectiveness of CSC, real-world experiments were conducted using both self-collected coastal-forest datasets and the public MulRan-KAIST dataset. Mapping was performed using LIO-SAM with LiDAR, IMU, and GPS measurements, after which LiDAR-only localization was evaluated independently. A total of approximately 700 query scenes (1 m ground-truth threshold) were used in the self-collected experiments, and about 1200 scenes (3 m threshold) were evaluated in the MulRan-KAIST experiments. Comparative analyses between SC and CSC were performed using Precision-Recall (PR) curves, Detection Recall (DR) curves, Root Mean Square Error (RMSE), and Top-K retrieval accuracy. The results show that CSC consistently yields lower RMSE-particularly in the vertical and lateral directions-and demonstrates faster recall growth and higher stability in global retrieval. Across datasets, CSC maintains superior DR performance in high-confidence regions and achieves up to 45% reduction in distance RMSE in large-scale campus environments. These findings confirm that the cylindrical multi-channel formulation of CSC significantly improves geometric consistency and localization reliability, offering a practical and robust LiDAR-only localization framework for challenging unstructured outdoor environments.