Autonomous Underwater Vehicles

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An Autonomous Underwater Vehicle (AUV) is a robotic device that is driven through the water by a propulsion system, controlled and piloted by an onboard computer, and maneuverable in three dimensions. This level of control, under most environmental conditions, permits the vehicle to follow precise preprogrammed trajectories wherever and whenever required. Sensors on board the AUV sample the ocean as the AUV moves through it, providing the ability to make both spatial and time series measurements. Sensor data collected by an AUV is automatically geospatially and temporally referenced and normally of superior quality. Multiple vehicle surveys increase productivity, can insure adequate temporal and spatial sampling, and provide a means of investigating the coherence of the ocean in time and space.
The fact that an AUV is normally moving does not prevent it from also serving as a Lagrangian, or quasi Eulerian, platform. This mode of operation may be achieved by programming the vehicle to stop thrusting and float passively at a specific depth or density layer in the sea, or to actively loiter near a desired location. AUV’s may also be programmed to swim at a constant pressure or altitude or to vary their depth and/or heading as they move through the water, so that undulating sea saw survey patterns covering both vertical and/or horizontal swaths may be formed. AUV’s are also well suited to perform long linear transects, sea sawing through the water as they go, or traveling at a constant pressure. They also provide a highly productive means of performing seafloor surveys using acoustic or optical imaging systems.
When compared to other Lagrangian platforms, AUV’s become the tools of choice as the need for control and sensor power increases. The AUV’s advantage in this area is achieved at the expense of endurance, which for an AUV is typically on the order of 8- 50 hours. Most vehicles can vary their velocity between 0.5 and 2.5 m/s. The optimum speed and the corresponding greatest range of the vehicle occur when its hotel load (all required power except propulsion) is twice the propulsive load. For most vehicles, this occurs at a velocity near 1.5 m/s.
The degree of autonomy of the robot presents an interesting dichotomy. Total autonomy does not provide the user with any feedback on the vehicle’s progress or health, nor does it provide a means of controlling or redirecting the vehicle during a mission. It does, however, free the user to perform other tasks, thereby greatly reducing operational costs, as long as the vehicle and the operator meet at their duly appointed times at the end of the mission. For some missions, total autonomy may be the only choice; in other cases when the vehicle is performing a routine mission, it may be the preferable mode of operation.

ROV MANUAL

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Operations Procedures Before any circuits are energized for the first time, an operations procedure must be developed that covers the following topics:

• Authorized Personnel
• Safety Lectures
• Equipment Familiarization
• Deck Officer In Charge
• Emergency Procedures
• Start-up Scenario
• Personnel Responsibilities Assignment

This operations procedure must encompass more than the Argus Remote Systems a/s checklists as indicated. The operations procedure must assign tasks to specific individuals and establish the line of authority for the safe operation of the equipment.
It is the responsibility of the system operators to work within the guidelines of their corporate and/or govermental codes where there is a conflict with the Argus Remote Systems a/s guidelines. The operations procedure must be thoroughly understood by the operators, and all routines must be strictly followed for the operations procedure to be effective.

Maintenance Procedures Basic good maintenance procedures relative to the hydraulic system must be developed and implemented by the operator. These procedures must encompass the following topics:

• Change filters if there is any sign of seawater in the oil and flush with clean test stand fluid.
• Change filters if there is any question of contamination. Filters are cheap relative to the system components.
• Any components that has to be replaced should be cycled through the test before assembly into the system.
• Any hose or fitting which is replaced should be thoroughly cleaned before installation.
• Change filters every time the system integrety is broken.
• Never leave open fittings or components exposed. Cap with the proper fitting.
• Never reuse oil which has been flushed from the system.
• Never use oil from partially filled containers.
• Do not mix oils. The hydraulic fluid for manips on the Hydro-Lek manips are Tellus 32 or equivalent.
• Always keep spare components sealed in plastic bags and stored under the proper conditions.
• Always tightly cap oil storage cans

Adaptive Sensing for Localisation of an Autonomous Underwater Vehicle

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This paper demonstrates an improved robot localisation approach based on adaptive sensing.
Using a particle ¯lter to represent the uncertainty in location the approach minimises the
expected entropy after the next robot action.It is demonstrated in simulation that this ap-
proach is useful in sensor management of an Autonomous Underwater Vehicle when a digi-
tised elevation map of the environment is available.

1 Introduction
The sophistication and usefulness of Autonomous Underwater Vehicles (AUVs) has increased dramatically in recent years, with record feats of depth and endurance offering new opportunities for ocean science and exploration. However the majority of these vehicles have only a primitive level of autonomy, with current AUVs typically carrying out a mission by attempting to follow a pre-planned trajectory. Sensing is usually passive, in that the perceived sensor data does not in°uence the actions taken by the vehicle.1 We propose to provide the
AUV with a means to make sensor management decisions based upon the information it obtains during the course of the mission, in order to enhance navigation performance. There are also opportunities to improve battery life [Nygren and Jansson, 2004] and the overall effectiveness of a mission [Makarenko et al., 2002] by sensing intelligently rather than continuously and indiscriminately. In this paper we demonstrate the potential of adaptive sensing by applying it to a terrain-aided tracking algorithm [Williams, 2003].

IMPROVING THE OPERABILITY OF REMOTELY OPERATED VEHICLES (ROV)

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ABSTRACT
Underwater Remotely Operated Vehicles (ROVs) have a significant support role to play in offshore petroleum production facilities. The extent to which ROVs can replace diver-based operations depends significantly on ROV capacity and the relative costs of mobilising and implementing the two modes of underwater operation. This paper presents work directed at two aspects of ROV operability: the quality of visual information presented to the ROV pilots and the degree of station keeping control exhibited by the vehicle.
Significant improvement in pilot performance of selected maintenance-type tasks has been achieved by the use of a purpose built underwater stereoscopic video camera and
associated ship-based stereoscopic display unit. Two generations of cameras have now been built and used on a Perry Triton vehicle in use at the North Rankin A platform on the North West Shelf.
In a related program, stereoscopic images of the platform structure are processed to determine the relative position of the ROV. Changes in position are used as inputs to thruster control algorithms, with a view to enabling the vehicle to hold position in fluctuating current fields. The position data from the processed 3D images are linked to output from an on-board inertial system to enable position to be maintained despite periodic loss of visual information.
First trials of the combined vision-inertial system indicated some success, notably using the vision system, but indicated difficulties with the inertial package and its integration into the control process. An extension of this project is now being supported by the Australian Maritime
Engineering Cooperative Research Centre (AME CRC).