A novel control data based on typical ground objects: intelligent landmark
To address the limitations of conventional control schemes in terms of geographical scope and precision, and to fully utilize existing high-precision geographic information resources for obtaining global high-precision control data, an intelligent landmark control data approach based on typical ground objects was proposed. This method, which incorporates intelligent processing techniques, offers novel strategies for the efficient and accurate transmission of high-precision control information. Focusing on the presentation of intelligent landmarks, this paper firstly proposed an intelligent landmark construction scheme with sports field as the landmark carrier and established four experimental areas to verify the feasibility of the scheme in controlling data distribution and density. Secondly, combining the flat terrain of the sports field, a three-dimensional (3D) geographic information storage strategy for landmark carriers has been designed, which combines accuracy, completeness, and accessibility. Finally, a comprehensive and systematic metadata system for intelligent landmarks has been constructed. The identification of landmark carriers, the design of storage strategies, and the establishment of a metadata framework collectively form the fundamental architecture for the transmission and application of intelligent landmark control information, which can provide theoretical and technical support for the construction of a global intelligent landmark control network and is of great significance for promoting the application of control data in remote sensing and geographic information science.
Authors
- Chenguang Dai (ORCID: https://orcid.org/0000-0003-4681-3851)
- Bing Shi (ORCID: https://orcid.org/0000-0002-2382-4104)
- Dashuai Shang (ORCID: https://orcid.org/0000-0002-6730-7168)
- Yongsheng Zhang (ORCID: https://orcid.org/0000-0002-1104-5605)
Institutions
- PLA Information Engineering University (CN)
- Chinese People's Liberation Army (CN)
Publication Details
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1117/12.3082686
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 0.00