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METHOD OF ESTIMATING A LOCATION BY FUSING INDOOR SPATIAL INFORMATION DATA
METHOD OF ESTIMATING A LOCATION BY FUSING INDOOR SPATIAL INFORMATION DATA
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机译:融合室内空间信息数据估算位置的方法
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摘要
The present invention relates to a method for estimating a location through convergence of indoor spatial information data, and using a mobile mapping system (MMS), 3D image information in the building for autonomous driving of vehicles entering the building and A first step of obtaining location information; A second step of receiving two-dimensional image information and location information that is architectural drawing information of the building from an external server; The 3D image information and location information obtained in the first step and the 2D image information and location information received in the second step are matched to obtain spatial information in the building for parking of the autonomous vehicle. A third step of generating; including, even if the vehicle for autonomous driving has entered a building that cannot receive a GPS signal, it is possible to obtain the location information of the vehicle, and it is difficult to obtain image information and location information in the building It is possible to provide a technique capable of compensating spatial information for a boundary area. According to the present invention, by automatically integrating a building construction drawing containing location information into image information and location information obtained through a mobile mapping system (MMS) of an autonomous vehicle, the autonomous vehicle entering the building automatically Parking is possible, and by integrating the processed 2D building construction drawings into 3D raw data, it is possible to supplement the incorrectly acquired image information and location information by the attachments in the building, thereby making it more accurate. It includes the effect of generating indoor spatial information, and by integrating architectural drawings with 3D point cloud data, the process of constructing 3D spatial information, which is mostly manual, is automated to update spatial information in buildings faster. We include effect that we can perform.
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