Abstract
Mobile mapping is an efficient technology to acquire spatial data of the environment. As a supplement of vehicle-borne and air-borne methods, Backpack mobile mapping system (MMS) has a wide application prospect in indoor and underground space. High-precision positioning and attitude determination are the key to MMS. Usually, GNSS/INS integrated navigation system provides reliable pose information. However, in the GNSS-denied environments, there is no effective long-term positioning method. With the development of simultaneous localization and mapping (SLAM) algorithm, it provides a new solution for indoor mobile mapping. This paper develops a portable backpack mobile mapping system, which integrates multi-sensor such as LiDAR, IMU, GNSS and panoramic camera. The 3D laser SLAM algorithm is applied to the mobile mapping to realize the acquisition of geographic information data in various complex environments. The experimental results in typical indoor and outdoor scenes show that the system can achieve high-precision and efficient acquisition of 3D information, and the relative precision of point cloud is 2~4cm, which meets the requirements of scene mapping and reconstruction.
Highlights
Mobile mapping technology is an advanced and efficient way to survey 3D information in space
This paper mainly introduces the key technologies and methods involved in the system, including high-precision time synchronization, sensors spatial relationship calibration based on planar features, scan matching and pose graph optimization in simultaneous localization and mapping (SLAM) algorithm
We do some experiments in indoor and outdoor scenes to verify the feasibility of applying laser SLAM algorithm to backpack mobile mapping system
Summary
Mobile mapping technology is an advanced and efficient way to survey 3D information in space. The mobile mapping system(MMS) integrates multi-sensor such as global navigation satellite system (GNSS) receiver, inertial measurement unit (IMU), laser scanner, CCD camera. SLAM is an autonomous navigation and mapping method, which is independent of GNSS signals [5, 6] It is suitable for indoor and underground space and has broad prospects in MMS. This paper mainly introduces the key technologies and methods involved in the system, including high-precision time synchronization, sensors spatial relationship calibration based on planar features, scan matching and pose graph optimization in SLAM algorithm. We do some experiments in indoor and outdoor scenes to verify the feasibility of applying laser SLAM algorithm to backpack mobile mapping system. Compared with the results obtained by other measurement methods, it shows that the 3D point cloud results acquired by backpack mobile mapping system have high accuracy
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