DARTBOARD BASED GROUND DETECTION ON 3D POINT CLOUD

Abstract. LiDAR (Light Detection And Ranging) laser scanners acquire 3D point clouds of real environments. The process consists in sampling the scene with beams rotating around an axis. By construction, density decreases distance to scanner. This heterogeneity is a major issue, particular for mobile systems context autonomous driving, as usually single scan processed simultaneously (instead mapping applications that can integrate several scans, reducing heterogeneity). We propose dartboard grid cell size increasing radially order adapt density. effectiveness this strategy demonstrated by means ground detection task, fundamental step many workflows analysis clouds.