Autonomous Underwater Vehicles (AUV’s) are taking bigger roles in science, industry, and defence. Essentially robotic submarines, or subsea drones, AUV technology lags its aerospace counterpart due to the physics of the subsea medium making robotics advancements more difficult. A high degree of uncertainty in navigation and manoeuvring results from the significant limitations of physics underwater. Subsea robotics cannot rely upon GPS for navigation and communication is hugely limited once the drone dives. These factors push for increasing levels of autonomy and demand that increasing decision-making capability be embedded onboard the AUV. This means there are exponential benefits to be achieved through even basic advancements in subsea Artificial Intelligence (AI).

Localization is seen as a critical step to increasing artificial intelligence of robotics systems. My engineering honours thesis of AUV Localization and Homing to a single beacon was commissioned with two goals in mind. Firstly, for expedited recovery of vehicles deployed underneath ice, and secondly, for advancement toward automated docking with a surface vessel (manned or unmanned).

AUVs are being deployed beneath ice for various reasons. For example, Environmental Scientists map the underside of icebergs to validate ice-thickness models generated by satellite, and NASA trains astronauts to work alongside robotic systems for over-the-horizon exploration in an environment hostile to humans. AUVs are often deployed through relatively small holes cut through the ice. Recovery after these missions can be a significant task, especially given a case where an AUV gets ‘lost’ under the ice. Having an AUV capable of locating and returning to a beacon dipped through the ice is thus an important redundancy.

Launch and Recovery of AUVs is still also a major challenge from surface vessels. While there are various Launch and Recovery Systems (LARS) in operations, there is also a push for having the AUV home to an automated docking capability. This has been achieved by various groups, such as Woods Hole Oceanographic Institute (WHOI), and work continues in this area around the world. Of course, different vessels and operational requirements require a range of solutions. Covert operations in defence for example will benefit from having an AUV capable of localizing and homing to an Unmanned Surface Vessel (USV). Long term, the goal is to have AUVs, USVs and Unmanned Aerial Vehicles (UAV) working with swarm capability for multi-platform fleet autonomy.

We achieved AUV Localisation and Homing to a single beacon in Iceland in 2015 working alongside Teledyne Gavia to deploy a Teledyne Gavia AUV enhanced with Mission Oriented Operating Suite Interval Programming (MOOS-IvP) as a backseat driver. MOOS-IvP-GAVIA was able to take in range-reports generated from Long BaseLine (LBL) beacon ‘pings’ and generate a homing behaviour using a custom algorithm. This demonstrated an increased level of autonomy wherein the AUV was effectively able to update its original mission plan and execute the new plan without human involvement.

Real-time adaptive manouevring will be key to efficient robotics operations in the subsea environment. As AUVs become more ‘aware’ of their environments they become increasingly useful as they adapt their mission plans according to pre-programmed priorities. For instance, an AUV conducting survey operations could identify an item of interests (e.g. a shipwreck or a mine) and re-task itself to conduct closer inspection of the area before continuing on its original mission plan.

Keep an eye out for the research of Fletcher Thompson who has just been awarded a fellowship from the Institute of Marine Engineering Science & Technology (IMarEST) to extend his graduate research in autonomous multi-platform fleet capabilities at the Australian Maritime College.

James Keane

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