Localization of a Drifting Underwater Vehicle Using a Terrain-Based Particle Filter

David Casagrande, K. Krasnosky, Chris Roman
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引用次数: 5

Abstract

In this paper we present a terrain-aided particle filter to localize a freely drifting underwater vehicle. The vehicle is a bottom imaging Lagrangian float used for habitat classification, monitoring and fish abundance studies. During operation the vehicle captures down looking images at a controlled altitude above the bottom. Direct navigation information is often, but not always, recorded with an ultra short baseline (USBL) acoustic system. The presented methodology provides an alternate means for georeferencing when USBL is unavailable. The implemented particle filter utilizes a background bathymetry map and visual odometry measurements from the camera system. The particle filter is implemented using the Robot Operating System (ROS) and Orocos Bayesian Filtering Library (BFL). The Grid Map package is used to store and retrieve the bathymetryic data. Results using data collected on field deployments show the method is able to effectively utilize the terrain information and produce drift trajectories which closely match the recorded USBL data. Utilizing the method allows the float system to be deployed with minimal ship-side support while providing georeferencing that is critical to the end use of the collected images.
基于地形粒子滤波的水下航行器定位
本文提出了一种地形辅助粒子滤波方法,用于水下航行器的定位。该飞行器是一个底部成像拉格朗日浮子,用于栖息地分类、监测和鱼类丰度研究。在操作过程中,车辆在底部上方的控制高度捕捉向下看的图像。直接导航信息通常(但并非总是)使用超短基线(USBL)声学系统进行记录。所提出的方法为USBL不可用时的地理参考提供了另一种方法。所实现的粒子滤波器利用背景水深图和来自相机系统的视觉里程测量。粒子滤波采用机器人操作系统(ROS)和Orocos贝叶斯滤波库(BFL)实现。Grid Map包用于存储和检索测深数据。现场部署数据的结果表明,该方法能够有效利用地形信息,并产生与USBL记录数据密切匹配的漂移轨迹。利用该方法,浮子系统可以在最少的船侧支持下部署,同时提供地理参考,这对最终使用收集到的图像至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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