Bathymetric Particle Filter SLAM With Graph-Based Trajectory Update Method
Bathymetric Particle Filter SLAM With Graph-Based Trajectory Update Method
复制标题
基于图的轨迹更新方法的测深粒子滤波器 SLAM
DOI：
10.1109/access.2021.3088541
复制
发表时间：
2021
期刊：
影响因子：
3.9
通讯作者：
Zhang Wenjun
中科院分区：
文献类型：
--
作者：
Zhang Qianyi;Li Ye;Ma Teng;Cong Zheng;Zhang Wenjun
A graph-based particle filter bathymetric simultaneous localization and mapping (BSLAM) method is proposed to solve the oscillation problem of the trajectories estimated by particles when using a low precise vehicle motion model and obtain accurate navigation results for autonomous underwater vehicles (AUVs). A graph-based trajectory update method is proposed to update the trajectories stored in particles before particle weighting to weaken the influence of the low precise odometer model on the particle trajectories. A particle weighting method based on submap matching is proposed to improve the robustness of the particle filter. Besides, a graph-based map generation method is proposed to solve the map selection problem of the particle filtering theory. The performance of the proposed method is demonstrated using a simulated dataset and a field dataset collected from a sea trial. The results show that the proposed method is more accurate and effective compared with a state-of-art particle filter BSLAM method.
