Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.15849 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918258373820416 |
|---|---|
| author | Muravyev, Kirill Kobozev, Artem Yuryev, Vasily Melekhin, Alexander Bulichev, Oleg Yudin, Dmitry Yakovlev, Konstantin |
| author_facet | Muravyev, Kirill Kobozev, Artem Yuryev, Vasily Melekhin, Alexander Bulichev, Oleg Yudin, Dmitry Yakovlev, Konstantin |
| contents | We propose PRISM-Loc - a lightweight and robust approach for localization in large outdoor environments that combines a compact topological representation with a novel scan-matching and curb-detection module operating on raw LiDAR scans. The method is designed for resource-constrained platforms and emphasizes real-time performance and resilience to common urban sensing challenges. It provides accurate localization in compact topological maps using global place recognition and an original scan matching technique. Experiments on standard benchmarks and on an embedded platform demonstrate the effectiveness of our approach. Our method achieves a 99\% success rate on the large-scale ITLP-Campus dataset while running at 150 ms per localization and using a 20 MB map for localization. We highlight three main contributions: (1) a compact representation for city-scale localization; (2) a novel curb detection and scan matching pipeline operating directly on raw LiDAR points; (3) a thorough evaluation of our method with performance analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_15849 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PRISM-Loc: a Lightweight Long-range LiDAR Localization in Urban Environments with Topological Maps Muravyev, Kirill Kobozev, Artem Yuryev, Vasily Melekhin, Alexander Bulichev, Oleg Yudin, Dmitry Yakovlev, Konstantin Robotics Computer Vision and Pattern Recognition We propose PRISM-Loc - a lightweight and robust approach for localization in large outdoor environments that combines a compact topological representation with a novel scan-matching and curb-detection module operating on raw LiDAR scans. The method is designed for resource-constrained platforms and emphasizes real-time performance and resilience to common urban sensing challenges. It provides accurate localization in compact topological maps using global place recognition and an original scan matching technique. Experiments on standard benchmarks and on an embedded platform demonstrate the effectiveness of our approach. Our method achieves a 99\% success rate on the large-scale ITLP-Campus dataset while running at 150 ms per localization and using a 20 MB map for localization. We highlight three main contributions: (1) a compact representation for city-scale localization; (2) a novel curb detection and scan matching pipeline operating directly on raw LiDAR points; (3) a thorough evaluation of our method with performance analysis. |
| title | PRISM-Loc: a Lightweight Long-range LiDAR Localization in Urban Environments with Topological Maps |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.15849 |