Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion

Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread a...

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Veröffentlicht in:	2024 IEEE International Conference on Robotics and Automation (ICRA) S. 11934 - 11940
Hauptverfasser:	He, Jinhao, Huang, Huaiyang, Zhang, Shuyang, Jiao, Jianhao, Liu, Chengju, Liu, Ming
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 13.05.2024
Schlagworte:	Cameras Laser radar Localization Location awareness Robot vision systems Robotics in Under-Resourced Settings Robustness Sensor Fusion Sensor systems Visualization
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Beschreibung
Zusammenfassung:	Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread adoption in mass-market applications. In this paper, we aim to use only a monocular camera to achieve comparable onboard localization performance by tracking deep-learning visual features on a LiDAR-enhanced visual prior map. Experiments show that the proposed algorithm can provide centimeter-level global positioning results with scale, which is effortlessly integrated and favorable for low-cost robot system deployment in real-world applications.
DOI:	10.1109/ICRA57147.2024.10611105