A Distributed Indoor Mapping Method Based on Control-Network-Aided SLAM: Scheme and Analysis

Abstract

Indoor mobile mapping techniques are important for indoor navigation and indoor modeling. As an efficient method, Simultaneous Localization and Mapping (SLAM) based on Light Detection and Ranging (LiDAR) has been applied for fast indoor mobile mapping. It can quickly construct high-precision indoor maps in a certain small region. However, with the expansion of the mapping area, SLAM-based mapping methods face many difficulties, such as loop closure detection, large amounts of calculation, large memory occupation, and limited mapping precision. In this paper, we propose a distributed indoor mapping scheme based on control-network-aided SLAM to solve the problem of mapping for large-scale environments. Its effectiveness is analyzed from the relative accuracy and absolute accuracy of the mapping results. The experimental results show that the relative accuracy can reach 0.08 m, an improvement of 49.8% compared to the mapping result without loop closure. The absolute accuracy can reach 0.13 m, which proves the method’s feasibility for distributed mapping. The accuracies under different numbers of control points are also compared to find the suitable structure of the control network.