距離画像を用いたLiDAR自己位置推定
Range Image-based LiDAR Localization for Autonomous Vehicles
3D LiDARスキャンから生成した距離画像とメッシュ地図のレンダリング画像を照合し、モンテカルロ法で大規模屋外環境における車両の自己位置を高精度に推定する手法を提案した。
著者: Xieyuanli Chen, Ignacio Vizzo, Thomas Läbe, Jens Behley, Cyrill Stachniss
分類: cs.RO
原文アブストラクト
Robust and accurate, map-based localization is crucial for autonomous mobile systems. In this paper, we exploit range images generated from 3D LiDAR scans to address the problem of localizing mobile robots or autonomous cars in a map of a large-scale outdoor environment represented by a triangular mesh. We use the Poisson surface reconstruction to generate the mesh-based map representation. Based on the range images generated from the current LiDAR scan and the synthetic rendered views from the mesh-based map, we propose a new observation model and integrate it into a Monte Carlo localization framework, which achieves better localization performance and generalizes well to different environments. We test the proposed localization approach on multiple datasets collected in different environments with different LiDAR scanners. The experimental results show that our method can reliably and accurately localize a mobile system in different environments and operate online at the LiDAR sensor frame rate to track the vehicle pose.
