Introduction

This is the post excerpt.

The area of unmanned systems for surveying and hydrographic purposes is one that is growing and developing with space for innovative ideas. Therefore, this can be followed with much interest and how they can be most valuable and effective is still being explored. This page will focus on Autonomous underwater vehicles (AUVs) through a range of posts.
As this is quite a recent area of development there are many new terms used that would be unfamiliar to most. Some acronyms used when discussing this topic relating to the vehicle are:

  • AUV – autonomous underwater vehicle;
  • ASV – autonomous surface vehicle;
  • UUV – unmanned underwater vehicle;
  • ROV – remotely operated vehicle;
  • UAV – unmanned aerial vehicle;

There are differences between these while UUV is a more general term. Within these terms there are many different designs and sizes and more being developed. They are then integrated with sonars for bathymetry information and high resolution mapping and imagery. There can also be integrated systems, running a number of vehicles cooperatively.
Some further acronyms include:

  • IMU – inertial measurement unit;
  • SLAM – simultaneous localisation and mapping;

where IMU is a sensor unit on the vehicle used to get its orientation and direction, and SLAM is a more computer based process originating from above ground robotics.

My interest in autonomous vehicles grows from being exposed to a scanning survey vehicle in the open cut mining industry. Similar aspects then extends to unmanned underwater vehicles and the development of these types of machines. Development is growing with the industries most vested being defence and military, oil and gas, as well as deep water research. Therefore, it is a booming sector with commercial interests noted by magazine Hydro International and having released three special issues on unmanned systems over three years. It is seen as of particular value as these vessels can access areas unreachable by people or are deemed unsafe and so would be important to many industries.

A further challenge of the development is that autonomous mapping can be seen as a broad area that is interdisciplinary. Expertise in computer science, algorithms, robotics, sensors, positioning is required for these machines. Some issues that can be explored include navigation challenges, underwater communication, autonomous mapping, detection and classification, as well as system and data interoperability.

The potential of this sector may yet to be identified as the new technology is developed and experimented with in different applications and industries. This requires effective collaboration and  is why this is an interesting topic as it is unknown where the sector will go and how far certain technologies will be taken. There will also be discussion whether the use is cost-effective and therefore financially worthwhile for the data and outputs.

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