Boundary Directional Feature Descriptor for LiDAR-OpenStreetMap Matching in Urban Scenarios

Although pre-built LiDAR maps have been widely used for location estimation, the high maintenance cost of pre-built maps hinders their expansion in practical application. Lightweight maps with global consistency and extensive coverage, such as OpenStreetMap (OSM), provide a low-cost potential alternative for prior reference. However, OSM exhibits significant differences in precision and structure with on-board perception, leading to incompatibility and poor performance with the existing descriptor matching method. Thus, this paper proposes a planar descriptor based on building boundary directions that is tailored for OSM-perception unification. Based on the proposed descriptor, OSM can be transformed into a prior map with the potential to replace pre-built maps, suitable for location estimation in urban scenes. To evaluate the effectiveness of replacing pre-built LiDAR maps, we conducted experiments in the urban environment sequences of KITTI. The results indicate that the proposed method achieves the best performance on location estimation accuracy utilizing OSM compared to other feature descriptors.