Toward Efficient 3-D Colored Mapping in GPS-/GNSS-Denied Environments

被引:29
|
作者
Wen, Chenglu [1 ]
Dai, Yudi [1 ]
Xia, Yan [1 ]
Lian, Yuhan [1 ]
Tan, Jinbing [1 ]
Wang, Cheng [1 ]
Li, Jonathan [1 ,2 ,3 ]
机构
[1] Xiamen Univ, Fujian Key Lab Sensing & Comp Smart City, Xiamen 361005, Fujian, Peoples R China
[2] Fujian Collaborat Innovat Ctr Big Data Applicat G, Fuzhou 350003, Fujian, Peoples R China
[3] Univ Waterloo, Dept Geog & Environm Management, GeoSTARS Lab, Waterloo, ON N2L 3G1, Canada
基金
美国国家科学基金会;
关键词
Laser radar; Cameras; Calibration; Three-dimensional displays; Feature extraction; Simultaneous localization and mapping; Cloud computing; GPS-; global navigation satellite system (GNSS)-denied; light detection and ranging (LiDAR); mapping; point cloud; simultaneous localization and mapping (SLAM);
D O I
10.1109/LGRS.2019.2916844
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Efficient 3-D mapping provides useful and detailed 3-D data for many applications. In this letter, we present a multisensor calibration and mapping method, to provide highly efficient and relatively accurate colored mapping for GPS-/global navigation satellite system-denied environments. The sensor data include 3-D laser scanning point clouds and camera images. A simultaneous localization and mapping (SLAM)-assisted calibration method is first proposed for multiple multibeam light detection and ranging (LiDAR) and multiple camera calibration. An improved SLAM method with loop closure is proposed for 3-D mapping. With the proposed calibration and mapping methods, centimeter-level colored point clouds can be obtained efficiently. The proposed method was tested with both backpacked and car-mounted systems on indoor and outdoor scenes. Experimental results show the effectiveness and efficiency of the proposed calibration and mapping methods.
引用
收藏
页码:147 / 151
页数:5
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