See our next articles.


See our next articles.


The dataset is genrated by the fusion of three publicly available datasets: COVID-19 cxr image (, Radiological Society of North America (RSNA) (, and U.S.  national  library  of  medicine  (USNLM) collected  Montgomery  country - NLM(MC) (http


The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at-sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, we present a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks.


This repository contains the AURORA dataset, a multi sensor dataset for robotic ocean exploration.

It is accompanied by the report "AURORA, A multi sensor dataset for robotic ocean exploration", by Marco Bernardi, Brett Hosking, Chiara Petrioli, Brian J. Bett, Daniel Jones, Veerle Huvenne, Rachel Marlow, Maaten Furlong, Steve McPhail and Andrea Munafo.

Exemplar python code is provided at


The dataset provided in this repository includes data collected during cruise James Cook 125 (JC125) of the National Oceanography Centre, using the Autonomous Underwater Vehicle Autosub 6000. It is composed of two AUV missions: M86 and M86.

  • M86 contains a sample of multi-beam echosounder data in .all format. It also contains CTD and navigation data in .csv format.

  • M87 contains a sample of the camera and side-scan sonar data. The camera data contains 8 of 45320 images of the original dataset. The camera data are provided in .raw format (pixels are ordered in Bayer format). The size of each image is of size 2448x2048. The side-scan sonar folder contains a one ping sample of side-scan data provided in .xtf format.

  • The AUV navigation file is provided as part of the data available in each mission in .csv form.


The dataset is approximately 200GB in size. A smaller sample is provided at and contains a sample of about 200MB.

Each individual group of data (CTD, multibeam, side scan sonar, vertical camera) for each mission (M86, M87) is also available to be downloaded as a separate file. 


Results(including reported and extra results) for LSstab. Please refer to our paper "Efficient real-time video stabilization with a novel least squares formulation and parallel AC-RANSAC".


Stabilization results for LSstab. Please refer to our paper"Efficient real-time video stabilization with a novel

least squares formulation and parallel AC-RANSAC"


Stabilization results include:

(1) stabilized videos reported in the paper

(2) extra stabilized videos

(3) Challenging videos that LStab fails to stabilize.