  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.
