Precise indoor localization and mapping using mobile laser scanners: a scoping review

Abstract

Indoor localization and mapping are essential for a wide range of applications. The absence of GPS signals in indoor environments such as buildings, caves, and tunnels brings significant challenges for applications where accurate positioning (i.e., centimeter-level accuracy) is required. This paper presents a scoping review of the most recent studies on precise indoor localization and mapping using mobile technologies, specifically, mobile laser scanners. The scoping review allows for a comprehensive and structured review of the literature to maximize the capture of relevant information and provide reproducible results. We extracted and reported a range of information from the selected articles published since 2009, with the goal of identifying the most frequently used sensors and methods of fusing their collected observations. The results show that in the majority of studies, LiDAR is the core sensor and IMUs with 75% and odometers with 67% magnitude are the main sensors integrated with the LiDAR system to enhance the localization precision. In addition, the classical iterative closest point (ICP) algorithm with approximately 60% frequency and the extended Kalman filter (EKF) method with over 40% frequency are the main algorithms used for the scan matching and fusion of different sensor data, respectively. This scoping review also revealed the lack of mapping-systems calibration as the main limitation in over 70% of the papers analyzed.