2021/12/25 by Yusheng Wang, Wang, Yusheng, Weiwei Song +9
Earth and Planetary Sciences · Engineering · Environmental Science · #3D Surveying and Cultural Heritage #FOS: Computer and information sciences #Infrastructure Maintenance and Monitoring #Remote Sensing and LiDAR Applications #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2112.13224
openalex publication_date 2021/12/25 · openalex created_date 2021/12/31 · openalex updated_date 2026/07/28
Precise and real-time rail vehicle localization as well as railway environment monitoring is crucial for railroad safety. In this letter, we propose a multi-LiDAR based simultaneous localization and mapping (SLAM) system for railway applications. Our approach starts with measurements preprocessing to denoise and synchronize multiple LiDAR inputs. Different frame-to-frame registration methods are used according to the LiDAR placement. In addition, we leverage the plane constraints from extracted rail tracks to improve the system accuracy. The local map is further aligned with global map utilizing absolute position measurements. Considering the unavoidable metal abrasion and screw loosening, online extrinsic refinement is awakened for long-during operation. The proposed method is extensively verified on datasets gathered over 3000 km. The results demonstrate that the proposed system achieves accurate and robust localization together with effective mapping for large-scale environments. Our system has already been applied to a freight traffic railroad for monitoring tasks.