Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion - He, Jinhao; Huang, Huaiyang; Zhang, Shuyang; Jiao, Jianhao; Liu, Chengju; Liu, Ming (2024 IEEE International Conference on Robotics and Automation (ICRA), 2024)
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.