Range Image-based LiDAR Localization for Autonomous Vehicles
Autor: | Thomas Läbe, Xieyuanli Chen, Ignacio Vizzo, Jens Behley, Cyrill Stachniss |
---|---|
Rok vydání: | 2021 |
Předmět: |
FOS: Computer and information sciences
Computer science business.industry Monte Carlo method ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Monte Carlo localization Location awareness Mobile robot Frame rate computer.software_genre Computer Science - Robotics Lidar Triangle mesh Computer vision Artificial intelligence Representation (mathematics) business computer Robotics (cs.RO) |
Zdroj: | ICRA |
DOI: | 10.48550/arxiv.2105.12121 |
Popis: | 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. Comment: Accepted by ICRA 2021. Code: https://github.com/PRBonn/range-mcl. arXiv admin note: text overlap with arXiv:2105.11717 |
Databáze: | OpenAIRE |
Externí odkaz: |