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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| Vydáno v: | 2024 IEEE International Conference on Robotics and Automation (ICRA) s. 11934 - 11940 |
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IEEE
13.05.2024
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Jiao, Jianhao Liu, Chengju Zhang, Shuyang Liu, Ming He, Jinhao Huang, Huaiyang |
| Author_xml | – sequence: 1 givenname: Jinhao surname: He fullname: He, Jinhao organization: The Hong Kong University of Science and Technology (Guangzhou),Thrust of Robotics and Autonomous Systems,Guangzhou,China – sequence: 2 givenname: Huaiyang surname: Huang fullname: Huang, Huaiyang organization: Baidu Autonomous Driving Technology Department (ADT) – sequence: 3 givenname: Shuyang surname: Zhang fullname: Zhang, Shuyang organization: The Hong Kong University of Science and Technology,Department of Electronic and Computer Engineering,Clear Water Bay, Kowloon,Hong Kong – sequence: 4 givenname: Jianhao surname: Jiao fullname: Jiao, Jianhao email: ucacjji@ucl.ac.uk organization: The Hong Kong University of Science and Technology,Department of Electronic and Computer Engineering,Clear Water Bay, Kowloon,Hong Kong – sequence: 5 givenname: Chengju surname: Liu fullname: Liu, Chengju organization: Tongji University,School of Electronics and Information Engineering,Shanghai,China – sequence: 6 givenname: Ming surname: Liu fullname: Liu, Ming organization: The Hong Kong University of Science and Technology (Guangzhou),Thrust of Robotics and Autonomous Systems,Guangzhou,China |
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| Snippet | Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization... |
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| SubjectTerms | Cameras Laser radar Localization Location awareness Robot vision systems Robotics in Under-Resourced Settings Robustness Sensor Fusion Sensor systems Visualization |
| Title | Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion |
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