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 b...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 understand- ing in urhan areas. By constructing MFG, the 2D/3D positions of features can be obtained, inclu- cling 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 ex- periments, the algorithm has achieved an overall localization accuracy of 2.2m, which is better than commercial GPS working in open environments.展开更多
基金Supported by the National High Technology Research and Development Program of China(No.2012AA041403)National Natural Science Foundation of China(No.60905061,61305107)+1 种基金the Fundamental Research Funds for the Central Universities(No.ZXH2012N003)the Scientific Research Funds for Civil Aviation University of China(No.2012QD23x)
文摘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 understand- ing in urhan areas. By constructing MFG, the 2D/3D positions of features can be obtained, inclu- cling 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 ex- periments, the algorithm has achieved an overall localization accuracy of 2.2m, which is better than commercial GPS working in open environments.
