Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion
<|reference_start|>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 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.<|reference_end|>
@article{he2024accurate,
    title={Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion},
    author={Jinhao He, Huaiyang Huang, Shuyang Zhang, Jianhao Jiao, Chengju Liu
  and Ming Liu},
    journal={arXiv preprint arXiv:2407.09091},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.09091},
    primaryClass={cs.RO}
}