High-Resolution Mobile Mapping Platform Using 15-mm Accuracy LiDAR and SPAN/TerraStar C-PRO Technologies

Abstract

Nowadays, most of the mobile mapping systems (MMSs) use global navigation satellite system (GNSS)/inertial navigation system positioning technology and 2-D sensors to construct maps, self-localize, and gather environmental information, as well. Several problems can arise with traditional architectures of these systems, especially in situations where the GNSS signal is unavailable or multiple paths are involved, such as reliability issues and poor accuracy. Moreover, their cost of up to U.S. $\$ $ 2 million still poses a significant challenge for the development of new geographical information system applications. This article proposes a new design of an MMS that incorporates a 1.5-cm accurate 3-D light detection and ranging sensor and a high-accuracy positioning system based on synchronous position attitude and navigation (SPAN)/TerraStar C-PRO technologies. The extended Kalman filter was used in this research to reduce the impact of GNSS signal loss by combining the simultaneous localization and mapping (SLAM) method with SPAN/TerraStar C-PRO technologies. In the experiments, the concept of our mobile mapping platform was validated using the simulation environment Gazebo. So as to evaluate the proposed platform, a real dataset was collected from a complex environment where the GNSS signal is rarely available, exactly, from the campus of Moncton—Université de Moncton. The obtained results disclosed that the proposed platform proves its performance in terms of accuracy and reliability. Due to the integration of the SLAM algorithm with SPAN/TerraStarC-PRO technologies, the generated 3-D point cloud map includes a number of 285 million points with a mean accuracy 0.28 m even in the case of GNSS signal loss.