Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 327-332, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-327-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
12 Sep 2017
AN INDOOR SLAM METHOD BASED ON KINECT AND MULTI-FEATURE EXTENDED INFORMATION FILTER
M. Chang1,2 and Z. Kang1 1School of Land Science and Technology, China University of Geosciences, 29 Xueyuan Road, Haidian District, Beijing 100083, China
2The First Monitoring and Application Center, China Earthquake Administration,7 Naihuo Road, Hedong District,Tianjin,300180, China
Keywords: Indoor Positioning,RGB-D Camera,Multi-Feature Extend Information Filter Model,ICP,SLAM Abstract. Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.
Conference paper (PDF, 1497 KB)


Citation: Chang, M. and Kang, Z.: AN INDOOR SLAM METHOD BASED ON KINECT AND MULTI-FEATURE EXTENDED INFORMATION FILTER, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 327-332, https://doi.org/10.5194/isprs-archives-XLII-2-W7-327-2017, 2017.

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