Australian sea-floor survey data, with images and expert annotations

Abstract This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

Download Full-text

Real time visualisation of sensor data for an autonomous underwater vehicle via a Wi-Fi buoy

2012 Oceans - Yeosu ◽

10.1109/oceans-yeosu.2012.6263418 ◽

2012 ◽

Author(s):

Jeremy Breen ◽

John McCulloch

Keyword(s):

Real Time ◽

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Sensor Data

Download Full-text

Complementary control for robots with actuator redundancy: an underwater vehicle application

Robotica ◽

10.1017/s0263574715000119 ◽

2015 ◽

Vol 35 (1) ◽

pp. 206-223 ◽

Cited By ~ 2

Author(s):

Giovanni Indiveri ◽

Alessandro Malerba

Keyword(s):

Data Processing ◽

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Sensor Data ◽

Design Data ◽

State Space Methods ◽

Alternative State ◽

State Estimators ◽

Simulation Results ◽

Main Ideas

SUMMARYComplementary filtering is a frequency based method used to design data processing algorithms exploiting signals with complementary spectra. The technique is mostly used in sensor fusion architectures, but it may also be effective in the design of state estimators. In spite of its potential in several areas of robotics, the complementary filtering paradigm is poorly used as compared to alternative time domain methods. The first part of the paper aims at reviewing the basics of complementary filtering in sensor data processing and linear systems state estimation. The second part of the paper describes how to exploit the main ideas of complementary filtering to design a depth controller for an actuator redundant autonomous underwater vehicle (AUV). Unlike with alternative state space methods commonly used to address the design of control solutions for actuator redundant systems, the proposed approach allows to fully exploit the knowledge of frequency characteristics of actuators. Simulation results are reported to demonstrate the effectiveness of the proposed solution.

Download Full-text

An In-situ Correction Method of Position Error for an Autonomous Underwater Vehicle Surveying the Sea Floor

International Journal of Ocean System Engineering ◽

10.5574/ijose.2011.1.2.060 ◽

2011 ◽

Vol 1 (2) ◽

pp. 60-67 ◽

Cited By ~ 6

Author(s):

Pan-Mook Lee ◽

Bong-Huan Jun ◽

Jin-Yeong Park ◽

Hyung-Won Shim ◽

Jae-Soo Kim ◽

...

Keyword(s):

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Correction Method ◽

Position Error ◽

Sea Floor

Download Full-text

Self-Repairing Control System for a Hybrid Underwater Vehicle

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.834-836.1256 ◽

2013 ◽

Vol 834-836 ◽

pp. 1256-1262 ◽

Cited By ~ 1

Author(s):

Biao Wang ◽

Chao Wu ◽

Tong Ge

Keyword(s):

Control System ◽

Fault Diagnosis ◽

Autonomous Underwater Vehicle ◽

Control Strategies ◽

Underwater Vehicle ◽

Reconfigurable Control ◽

Sea Floor ◽

Surface Ship ◽

Area Survey ◽

Fault Diagnosis System

A novel remotely operated underwater vehicle-a hybrid remotely operated underwater vehicle (HROV) capable of working to the full ocean depth has been developed. The battery powered vehicle operates in two modes. For broad-area survey, the vehicle can operate as an autonomous underwater vehicle (AUV) capable of mapping the sea floor with sonars and cameras. For close up imaging and sampling, the vehicle can operate as a remotely operated underwater vehicle (ROV) employing a optic fiber tether for real-time telemetry of data and video to its operators on a surface ship. In order for the vehicle to achieve a certain survivability and reliability level, a self-repairing control system (SRCS) has been designed. This paper presents the two basic technologies in SRCS: fault diagnosis and isolation (FDI) and reconfigurable control. For FDI, a model-based hierarchical fault diagnosis system is designed for the HROV. Then, control strategies which reconfigure the control system at intervals according to information from the FDI system are presented. Combining the two technologies, we obtained the fundamental frame of SRCS for the HROV.

Download Full-text