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

Abstract

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.