An Improved MbICP Algorithm for Mobile Robot Pose Estimation

Abstract

Featured Application: The metric-based iterative closest point algorithm is frequently used for mobile robot pose estimation by scan matching. The improved version can be used for matching scans that partially overlap.Abstract: This paper presents an improved version of the metric-based iterative closest point algorithm to estimate robot poses by matching 2D laser scans with different overlapping percentages. Because of the greatly varied density distribution of realistic point clouds, a resampling method is used to accelerate the iteration process and protect the calculation of the rejection threshold from being distorted by reducing dense but unhelpful points. A new procedure that combines point-to-point and point-to-line metrics is used to determine the correct correspondence between partially overlapping scans, which maintains both efficiency and accuracy. In addition, a rejection threshold that is based on the MAD-from-median method is utilized to discard correspondences with large distances, which are likely to be incorrect. Experiments show that the improved algorithm is more accurate and robust than the standard algorithm with respect to the existence of non-overlapping areas, and testing demonstrates that it is valid in practice.

MIM_SLAM: A Multi-Level ICP Matching Method for Mobile Robot in Large-Scale and Sparse Scenes

“…Finally, it computes a transformation matrix so that the error function is minimized. In the past 30 years, many ICP variant algorithms [21] have been proposed. In this paper, an ICP variant algorithm that calls point-to-plane ICP [22] is used.…”

Preface of Special Issue on Laser Scanning

“…Detecting object position and movement is important for mobile applications, especially in the realm of robotics, where laser scanning can provide this information at a very fast rate. Robot position and moving direction is a key information that can be provided as described in [8]. Elevation maps extracted from laser scanning can also support robot navigation as shown in [11].…”

“…Laser scanning applications covered in this special issue can be divided into the following categories: multi-wavelength LiDAR [3,4], mobile mapping support for indoor [5][6][7], outdoor, and other applications [8], object tracking and navigation [9][10][11], deformation monitoring [12,13], modelling and detection [14][15][16], geometric accuracy assessment [17][18][19], and hybrid technologies like LiDARgrammetry [20], which are summarized in more detail in the following section.…”

Smart Building Surveillance System as Shared Sensory System for Localization of AGVs

“…One of the most used methods is Simultaneous Localization and Mapping (SLAM) [2] where the environment is not known, so a vision based system is placed on a robot to observe the area and create a map of it, eventually to perform trajectory planning on top of it. There were many enhancements of the SLAM methods proposed, some of them are compared by Santos [3] and the most common sensors used there are lidars [4][5][6][7] and depth cameras [4,[8][9][10]. However, when the environment is known (indoor areas frequently), the advanced SLAM systems may become redundant and if more robots are deployed, it becomes costly when every single robot has to carry all sensors.…”