@inproceedings{9f1713f45d614ccdac40c961c036ab2e,
title = "An Acoustic-Inertial Pose Estimation Method with Robust Feature Match and Graph Optimization",
abstract = "High-accuracy pose estimate is necessary for underwater vehicle to perform tasks. In this paper, we present a novel pose-graph navigation system for underwater vehicle using forward-looking sonar (FLS) and inertial measurement unit (IMU). The proposed system first uses A-Kaze features to build an acoustic odometry by triangulation and then utilizes the acoustic structure from motion (AFSM) to obtain pose estimates. Next, all pose estimates are added to a pose graph, associated with inertial odometry measurements, to optimize the pose of the underwater vehicle. The effectiveness of the proposed method is verified via simulations in gazebo.",
keywords = "Acoustic-Inertial, Autonomous Underwater Vehicle, Feature Match, Pose Estimation",
author = "Bufang Li and Weisheng Yan and Huiping Li and Lijun Zhang",
note = "Publisher Copyright: {\textcopyright} 2022 ACA.; 13th Asian Control Conference, ASCC 2022 ; Conference date: 04-05-2022 Through 07-05-2022",
year = "2022",
doi = "10.23919/ASCC56756.2022.9828281",
language = "英语",
series = "ASCC 2022 - 2022 13th Asian Control Conference, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2115--2120",
booktitle = "ASCC 2022 - 2022 13th Asian Control Conference, Proceedings",
}