arrow
返回

Selective visual odometry for accurate AUV localization

delete2015-12-26
delete30
PRE
AI
F
Fabio Bellavia
M
Marco Fanfani *
C
Carlo Colombo
DOI:10.1007/s10514-015-9541-1delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
In this paper we present a stereo visual odometry system developed for autonomous underwater vehicle localization tasks. The main idea is to make use of only highly reliable data in the estimation process, employing a robust keypoint tracking approach and an effective keyframe selection strategy, so that camera movements are estimated with high accuracy even for long paths. Furthermore, in order to limit the drift error, camera pose estimation is referred to the last keyframe, selected by analyzing the feature temporal flow. The proposed system was tested on the KITTI evaluation framework and on the New Tsukuba stereo dataset to assess its effectiveness on long tracks and different illumination conditions. Results of a live archaeological campaign in the Mediterranean Sea, on an AUV equipped with a stereo camera pair, show that our solution can effectively work in underwater environments.
Keyword:
Visual odometry
Stereo
Underwater
AUV
RANSAC
Feature matching
Keyframe selection

期刊

Autonomous Robots 封面图
Autonomous Robots
IF:
4.3
论文数:
1.7K
被引数:
5.0K

机构

U
university of florence
学者数:
4.2W
论文数: 3.1W
被引数: 42
引用论文

引用论文

Response to Subsequent Docetaxel in a Patient Cohort With Metastatic Castration-Resistant Prostate Cancer After Abiraterone Acetate Treatment
err2014-10-01
err0
PREAI
errRahul Aggarwal; Anna Harris; Carl Formaker; Eric J. Small; Arturo Molina; Thomas W. Griffin; Charles J. Ryan
err分享
err收藏
Scan matching SLAM in underwater environments水下环境下的扫描匹配SLAM
err2013-06-25
err65
PREAI
errMallios, Angelos; Ridao, Pere; Ribas, David; Hernandez, Emili
err分享
err收藏
AUV Navigation and Localization: A Review
err2014-01-01
err1.2K
PREAI
errPaull, Liam; Saeedi, Sajad; Seto, Mae; Li, Howard
err分享
err收藏
err分享
err收藏
学者 查看更多内容