Paper ID: 2407.09091

Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion

Jinhao He, Huaiyang Huang, Shuyang Zhang, Jianhao Jiao, Chengju Liu, Ming Liu

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.

Submitted: Jul 12, 2024