LiDAR SLAM Positioning Quality Evaluation in Urban Road Traffic

Abstract

This paper addresses the positioning quality of Simultaneous Localization And Mapping (SLAM) based on Light Detection and Ranging (LiDAR) sensors within urban road traffic. Based on the assumption of functional capability of existing SLAM implementations, the paper evaluates specific details of urban car drives that arise when SLAM is to be used for automatic car control. In the presented case, LiDAR-based positioning is done with the Google Cartographer software which generates real-time updates that are compared to GNSS reference. The evaluation is done by using own Light Detection And Ranging (LiDAR) sensor recordings from urban driving. Next to the overall GNSS-free path estimation, the paper zooms into some typical situations (e.g. waiting at busy intersection, driving curves) where SLAM might be inaccurate.