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

Abstract

Nowadays, most of the mobile mapping systems use GNSS/INS positioning technology and two-dimensional 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 2 million USD still poses a significant challenge for the development of new GIS applications. This paper proposes a new design of a mobile mapping system that incorporates a 1.5 cm accurate 3D LiDAR sensor and a high accuracy positioning system based on 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 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 SLAM algorithm with SPAN/TerraStarC-PRO technologies, the generated 3D point cloud map includes a number of 285 million points with an mean accuracy 0.28 m even in the case of GNSS signal loss.