| Li Haifeng (李海丰),Wang Hongpeng,Liu Jingtai.[J].高技术通讯(英文),2015,21(1):31~38 |
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| Autonomous map query: robust visual localization in urban environments using Multilayer Feature Graph |
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| DOI：10.3772/j.issn.1006-6748.2015.01.005 |
| 中文关键词: |
| 英文关键词: visual localization, urban environment, multilayer feature graph（MFG）, voting-based method |
| 基金项目: |
| Author Name | Affiliation | | Li Haifeng (李海丰) | | | Wang Hongpeng | | | Liu Jingtai | |
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| 中文摘要: |
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| 英文摘要: |
| When a vehicle travels in urban areas, onboard global positioning system (GPS) signals may be obstructed by high-rise buildings and thereby cannot provide accurate positions. It is proposed to perform localization by registering ground images to a 2D building boundary map which is generated from aerial images. Multilayer feature graphs (MFG) is employed to model building facades from the ground images. MFG was reported in the previous work to facilitate the robot scene understanding in urban areas. By constructing MFG, the 2D/3D positions of features can be obtained, including line segments, ideal lines, and all primary vertical planes. Finally, a voting-based feature weighted localization method is developed based on MFGs and the 2D building boundary map. The proposed method has been implemented and validated in physical experiments. In the proposed experiments, the algorithm has achieved an overall localization accuracy of 2.2m, which is better than commercial GPS working in open environments. |
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