Range-Aided SLAM Initialization Exploiting Accurate Heading Information

2026-09-21

AI Summary

本文提出了一种利用精确航向信息的新型测距辅助SLAM初始化方法，通过两步解决AUV和信标位置估计问题，提高了RA-SLAM的初始化精度。

Abstract

This paper presents a novel initialization method for range-aided simultaneous localization and mapping (RA-SLAM). The general SLAM problem has a well-known separable structure where landmark and robot positions can be solved for in a linear fashion given known robot headings. This paper considers the case where highly accurate heading information is available, which is typical of autonomous underwater vehicle (AUV) navigation, to solve for the range transponder and robot positions. The proposed approach consists of two steps. First, using a generalized trust region subproblem (GTRS), the positions of the transponders relative to the AUV are solved for given the nonlinear range measurements. Second, the relative transponder positions and the known heading of the AUV are used to estimate the transponder and AUV positions by solving a linear least-squares problem. These transponder and AUV position estimates, combined with the highly accurate heading information, provide a reliable initialization method for the general nonlinear RA-SLAM problem. The effectiveness of the proposed approach is tested on a real-world AUV dataset where long baseline (LBL) range measurements are provided in concert with highly accurate heading information provided by an inertial navigation system (INS).

Problem

• Range-aided SLAM
• accurate heading information
• AUV navigation
• transponder positions
• linear least-squares

Innovation

• Range-aided SLAM
• accurate heading information
• generalized trust region subproblem (GTRS)
• linear least-squares problem