Platforms: Autonomous Underwater Vehicles

Platforms: Autonomous Underwater Vehicles

PLATFORMS: AUTONOMOUS UNDERWATER VEHICLES J. G. Bellingham, Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA & 2009 Elsevier Ltd. All r...

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PLATFORMS: AUTONOMOUS UNDERWATER VEHICLES J. G. Bellingham, Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA & 2009 Elsevier Ltd. All rights reserved.

Introduction Autonomous underwater vehicles (AUVs) are untethered mobile platforms used for survey operations by ocean scientists, marine industry, and the military. AUVs are computer-controlled, and may have little or no interaction with a human operator while carrying out a mission. Being untethered, they must also store energy onboard, typically relying on batteries. Motivations for using AUVs include such factors as ability to access otherwise-inaccessible regions, lower cost of operations, improved data quality, and the ability to acquire nearly synoptic observations of processes in the water column. An example of the first is operations under Arctic and Antarctic ice, an environment in which operations of human-occupied vehicles and tethered platforms are either difficult or impossible. Illustrating the next two points, AUVs are becoming the platform of choice for deep-water bathymetric surveying in the offshore oil industry because they are less expensive than towed platforms as well as produce higherquality data (because they are decoupled from motion of the sea surface). Finally, the use of fleets of AUVs enables the rapid acquisition of distributed data sets over regions as large as 10 000 km2. AUVs are a new class of platform for the ocean sciences, and consequently are evolving rapidly. The Self Propelled Underwater Research Vehicle (SPURV) AUV, built at the University of Washington Applied Physics Laboratory, was first operated in 1967. However, adoption by the ocean sciences community lagged until the late 1990s. Adoption was spurred on by two developments: AUV development teams started supporting science field programs with AUV capabilities, and AUVs that nondevelopers could purchase and operate became available. The first served the purpose of building a user base and demonstrating AUV capabilities. The second enabled scientists to obtain and operate their own vehicles. Today, a wide variety of AUVs are available from commercial manufacturers. An even larger

number of companies develop subsystems and sensors for AUVs. The most common class of AUV in use today is a torpedo-like vehicle with a propeller at its stern, and steerable control surfaces to control turns and vertical motion (see Figure 1). These vehicles are used when speed or efficiency of motion is an important consideration. Such torpedo-like vehicles range in weight from a few tens of kilograms to thousands of kilograms. Most typical are vehicles weighing a few hundred kilograms, with an endurance of about a day at a speed of c. 1.5 m s1. Often they have parallel mid-bodies, which allow the vehicle length to be extended without large hydrodynamic consequences. This is useful when it is necessary to add new sensors or batteries to a vehicle. A disadvantage of torpedo-like vehicles is that, like an aircraft, they must maintain forward motion to generate lift over its control surfaces, and thus are not controllable at very low speed through the water. Gliders are a class of vehicles that use changes in buoyancy rather than a propeller for propulsion. Gliders use their ability to control buoyancy to generate vertical motion. Vertical motion is translated into horizontal motion with lifting surfaces, usually wings mounted in about the middle of the vehicle (see Figure 1). Several types of gliders weighing about 50 kg are in use today. These comparatively small vehicles are designed to move slowly, about 0.25 m s1, and operate sensors consuming a watt or less. By minimizing power consumption, these gliders can operate for periods of months using high-energydensity primary batteries. Disadvantages of this class of system are that they are limited to vertical profiling flight tracks, and can be overwhelmed by ocean currents, especially in the coastal environment or within boundary currents. However, larger gliders in development and testing will operate at higher speeds, and thus not suffer from this limitation. A final class of AUVs uses multiple thrusters to provide capabilities similar to that of a helicopter or a ship with dynamic positioning (see Figure 1). The additional thrusters enable maneuvers such as hovering, translating sideways, and moving vertically. These vehicles are used when maneuverability is needed, for example, when operation near a very rough bottom is a necessity. The disadvantage is that the additional thrusters reduce efficiency for moving large distances or at high speeds.

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Figure 1 From top-left corner clockwise: the Hugin AUV, the Spray glider (courtesy, MBARI), the ABE AUV (courtesy, Dana Yoerger, WHOI), and the Dorado AUV (courtesy, MBARI). Hugin and Dorado are examples of propeller-driven vehicles optimized for moving through the water efficiently, and have a torpedo-like configuration. Spray is an example of a glider, which is a buoyancy-driven vehicle that has no propeller. ABE is a highly maneuverable vehicle capable of hovering or pivoting in place, and of moving straight up or down. Also illustrated are different handling strategies. The large Hugin vehicle is launched and recovered from a ship using a stern ramp. Spray is hand-launched and recovered. ABE is launched and recovered with a crane. Dorado is shown being launched and recovered with a capture mechanism suspended from a J-frame.

While the vehicles described above are representative of the most commonly used systems, a wide range of other vehicles are in development or are in limited use. AUVs that come to the surface and use solar panels to recharge batteries have been demonstrated in seagoing operations. Gliders which extract energy from thermal differences in the ocean for

propulsion have also been tested. A hybrid vehicle is being developed for reaching the deepest portion of the ocean. The hybrid vehicle operates as a tethered platform via a disposable fiber optic link for tasks requiring human perception, in other words as a remotely operated vehicle (ROV), but operates as an AUV when that link is severed. These are just a few

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of the diverse AUVs being developed to answer the needs of ocean science. Terminology

The military term for an AUV is unmanned underwater vehicle, or UUV. This phrase is ambiguous in that it can also refer to ROVs. While ROVs are unmanned, they are tethered and designed to be operated by human, and thus are not considered autonomous. However, common usage is to employ UUV as a synonym for AUV. Military terminology is relevant as many AUVs in use by the scientific community were developed under navy funding, and the military continues to be the largest single investor in AUV technology. Consequently, the technical literature on AUVs also employs military terminology.

Basics of AUV Performance Energy is a fundamental limitation for underwater vehicles. Thus, energy efficiency is a fundamental driver for vehicle design and operations. This section outlines the relationship between vehicle speed and endurance, and its dependence on factors such as power consumed by onboard systems. A simple but useful model for power consumption P of an AUV is as follows: P ¼ Pprop þ H

where Pprop ¼

1 CD Arv3 2 Z

½1

Here the total electrical power consumed by the vehicle, P, is equal to the sum of propulsion power, Pprop and hotel load, H. Hotel load is simply the power consumed by all subsystems other than propulsion. Propulsion power is a function of the drag coefficient of the vehicle, CD, the area of the vehicle, A, the density of water, r, the speed of the vehicle, v, and the efficiency of the propulsion system, Z. What are the typical values for the coefficients in eqn [1]? Consider an ‘example vehicle’ which is a 12 3/400 (0.32 m) diameter torpedo-like AUV. Note that this is a standard for a mid-size class AUV. For such a vehicle, parameter values might be CD ¼ 0.2 (based on frontal area), A ¼ 0.082 m2, and Z ¼ 0.5. Hotel load would depend on sensors, but an overall value of 30 W might be representative, although mapping sonars would consume much more power. We use r ¼ 1027 kg m–3. Note that these numbers, except seawater density of course, can differ greatly from vehicle to vehicle. For example, gliders optimized for low speed and long endurance

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can operate with hotel loads on the order of a watt or less, but at the cost of operating a few very simple sensors. The power relationship provides insight into a variety of AUV design considerations. For example, the speed at which the vehicle will consume the least energy per unit distance traveled (the energetically optimum speed) can be computed from observing that power divided by vehicle speed equals energy per unit distance. Finding the minimum of P/v with respect to v yields the optimum speed from an energy conservation perspective:  vopt ¼

 ZH 1=3 CD Ar

½2

For the example vehicle values given above, the optimum vehicle speed is approximately 1 m s1. What can we say about vehicle performance at the energetically optimum speed? Substituting eqn [2] into eqn [1] we find that the power consumed at the optimum speed is (3/2)H which for our example vehicle is 45 W. If the total energy capacity of the battery system is Ecap, then the maximum range of the vehicle will be: dmax

 1=3 2Ecap Z ¼ CD ArH 2 3

½3

If our example vehicle carries 10 kg of high-energydensity primary batteries providing a total of 1.3  107 J, it will have an endurance of 80 h, and a range of 280 km. The same vehicle with 10 kg of rechargeable batteries, with one-third the energy capacity of the high-energy-density batteries, will have its endurance and range reduced proportionately. There are caveats to the above discussion. For example, propulsion efficiency, Z, is typically a strong function of speed as the electrical motors used tend to have comparatively narrow ranges of efficiency. In practice, a vehicle’s propulsion system is optimized for a particular speed and power. Also, vehicles are often operated at higher speeds than the energetically optimum speed given by eqn [2]. For example, operators of an AUV attended by a ship will be more sensitive to minimizing ship costs than to optimizing energy efficiency of the AUV.

AUV Systems and Technology AUVs are highly integrated devices, containing a variety of mechanical, electrical, and software subsystems. Figure 2 shows internal and external views of a deep-diving vehicle equipped with mapping

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Doppler velocity logger and inertial navigation system Sub-bottom profiler

Fluid intake

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Figure 2 A propeller-driven, modular AUV with labeled subsystems. The top view shows the interior in which an internal mechanical frame supports pressure vessels, internal components, and the propulsion system. This AUV, called a Dorado, is a ‘flooded’ vehicle because the fairings are not watertight, and thus the interior spaces fill with water. Consequently internal components must all be capable of withstanding ambient pressures. Joining rings are visible between the yellow fairing segments on the lower figure. These allow the vehicle to be separated along its axis, allowing replacement or addition of hull sections. This allows reconfiguration of the vehicle with new payloads, and if desired, with new batteries. The propulsion system on this vehicle is a ducted thruster capable of being tilted both vertically and horizontally, to steer the vehicle in the vertical and horizontal planes. Courtesy of Farley Shane, MBARI.

sonars. The anatomy of an AUV typically includes the following subsystems:

• • • • • •

software and computers capable of managing vehicle subsystems to accomplish specific tasks and even complete missions in the absence of human control; energy storage to provide power; propulsion system; a system for controlling vehicle orientation and velocity; sensors for measuring vehicle attitude, heading, and depth; pressure vessels for housing key electrical components;

• • • • •

navigation sensors to determine the vehicle position; communication devices to allow communication of human operators with the AUV; locating devices to allow operators to track the vehicle and locate it for recovery or in the case of emergencies; devices for monitoring vehicle health (e.g., leaks or battery failure); emergency systems for ensuring vehicle recovery in the event of failure of primary systems.

The mechanical design of an AUV must address issues such as drag, neutral buoyancy, the highly dynamic nature of launch and recovery, and the need

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to protect many delicate electrical components from seawater. The desire to operate large numbers of sensors for long distances encourages the construction of larger vehicles to hold the necessary equipment and batteries. However, the need for ease of handling and minimizing logistical costs encourages the design of smaller vehicles. Operational demands will also create constraints on vehicle design; for example, launch and recovery factors will impose the need for lift points and discourage external appendages that will be easily broken. The need to service vehicle components imposes a requirement that internal components be easily accessible for servicing and testing, and when necessary, replacement. In addition, a host of supporting software and hardware are required to operate an AUV. Depending on the nature of the operations, supporting equipment will include:

• • • • • •

software and computers for configuring vehicle mission plans, and for reviewing vehicle data; systems for communicating with the vehicle both on deck and when deployed; systems for recharging and monitoring vehicle batteries; handling gear for transporting, deploying, and recovering AUVs; devices for detecting locating devices on the AUV; acoustic tracking systems for monitoring the location of the vehicle when in the vicinity of a support vessel.

AUV Mission Software

Functionally, AUV software must address a variety of needs, including: allowing human operators to specify objectives, managing vehicle subsystems to achieve mission objectives, logging data for subsequent review, and ensuring safety of the vehicle in the event of failures or unexpected circumstances. The software must be capable of managing vehicle sensors and control systems to maintain a set heading, speed, and depth. The software might also need to support interacting with a human operator during a mission. In addition to software on the vehicle itself, AUV operators rely on a suite of software applications to configure and validate missions, to maintain vehicle subsystems such as batteries, to review data generated by the vehicle, to prepare mission summaries, and when possible, to track and manage the vehicle while underway. The exponential growth of computational power available for both onboard and off-board computers, as well as the increasingly pervasive nature of the Internet, are

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supporting a steady increase in software capabilities for AUVs. Most AUV missions involve sequential tasks such as descending from the surface to a set depth, then transiting to a survey location at a set speed, and then conducting a survey which might involve flying a lawn-mower pattern. The vehicle may be commanded to maintain constant altitude over the bottom if the vehicle is mapping the seafloor. A water-column mission might require the vehicle profile in the vertical plane, moving in a saw-tooth pattern called a yo-yo. The mission will likely include a transit from the end of the survey to a recovery location, with a final ascent to the surface for recovery. During the mission, the vehicle will monitor the performance of onboard subsystems, and in the event of detection of anomalies, like a low battery level, or a failed mission sensor, may abort the mission and return to the recovery point early. A more catastrophic failure might lead to the vehicle shutting down primary systems, and dropping a drop weight so as to float to the surface, and calling for help via satellite or direct radio frequency (RF) communications. More complex vehicle missions can involve capabilities such as adapting survey operations to obtain better measurements, or managing tasks such as AUV docking. An example of the first might be as simple as a yo-yo mission which cues its vertical inflections from water temperature in order to follow a thermocline. Also in the category of adaptive, but more demanding, surveys, is the capability of following a thermal plume to its source, for example, when an AUV is used to search for hydrothermal vents. The docking of an AUV with an underwater structure encompasses yet a different type of complexity, created by the large number of steps in the process, and the high likelihood that individual steps will fail. For example, docking involves homing on a docking structure, orienting for final approach, engaging the dock, and making physical connections to establish power and communication links. Any one of these steps might fail due to external perturbations; for example, currents or turbulence in the marine environment might cause the vehicle to miss the dock. The vehicle must be able to detect failures and execute a process to recover and try again. Docking is representative of the increasingly complex capabilities AUVs are expected to master with high reliability. Navigation

The ability for an AUV to determine its location on the Earth is essential for most scientific applications.

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However, navigation in the subsea environment is complicated by the opacity of seawater to all but very low frequency electromagnetic radiation, rendering ineffective the use of commonly used technologies such as the Global Positioning System (GPS) and other radio-based navigation techniques. Consequently, navigation underwater relies primarily on various acoustic and dead-reckoning techniques and the occasional excursion to the surface where radiobased methods can be used. There is no single method of underwater navigation that satisfies all operational needs, rather a variety of methods are employed depending on the circumstances. Dead-reckoning methods integrate a vehicle’s velocity in time to obtain an updated location. In order to dead-reckon, the vehicle must know both the direction and speed of its travel. The simplest methods use a magnetic compass to determine direction, and use speed through the water as a proxy for Earth-referenced speed. However, the large number of error sources for magnetic compasses make measurement of heading to better than a degree accuracy technically challenging. Currents pose even more of a problem, as they may be comparable to the vehicle speed in amplitude, yet are not sensed by a water-relative measurement. Dead-reckoning is improved by measuring velocity relative to the seafloor, for example, using a Doppler velocity log (DVL) or a correlation velocity log. A DVL is commonly used by AUVs to measure velocity by measuring the Doppler shift of sound reflected off the seafloor. Correlation velocity logs are more complex in concept, involving measurement of the correlation of two pulses of sounds transmitted by the vehicle, reflected off the seafloor, and received by a hydrophone array. In practice, DVLs are used when a vehicle operates close to the seafloor, perhaps within 200 m, while correlation velocity logs are used when the vehicle is operating in mid-water columns or near the surface in deep water. Inertial navigation system (INS) technology is well developed, as it is widely used for platforms like aircraft and missiles. However, INS units appropriate for underwater use are expensive enough that they are used only when navigation requirements are stringent, for example, for producing high-accuracy maps. A modern INS includes an array of accelerometers for measuring acceleration on three axes and a laser or fiber optic gyroscope for measuring changes in orientation. Additionally, an INS will include a GPS for initializing the unit’s location and orientation, and a computer for acquiring and processing data from INS component sensors. The position reported by an INS will have an error which will grow in time, and thus it is important to constrain INS

error with ancillary measurements of velocity and position. For example, combining an INS with a DVL for constraining velocity can result in a system which provides navigation accuracies better than 0.05% of distance traveled. The two acoustic navigation methodologies most frequently used in AUV operations are ultrashort baseline navigation (USBL) and long baseline (LBL) navigation. A USBL system uses an array of hydrophone separated by a distance comparable to the wavelength of sound to measure the direction of propagation of an acoustic signal. Most often, a USBL system is mounted on a ship, and used to track a vehicle relative to the ship. With knowledge of the ship’s location and orientation, the location of the AUV can also be determined. In contrast, LBL navigation acoustically measures the range between the vehicle and an array of widely separated devices of known location. A common LBL approach is to place transponders on the seafloor, and let the vehicle range off the transponders. The process of determining location using ranges from known locations is called spherical navigation, as the vehicle should be located at the intersection of spheres with the measured radius, centered on the respective transponders. An alternative LBL navigation method is to track a vehicle which pings at a preset time to an array of hydrophones at known locations. If the time of the ping is not known, the problem of solving for the vehicle location is called hyperbolic navigation, as only the difference in time of arrival of the ping at the various hydrophones can be determined, and this knowledge constrains the vehicle to be on a hyperbola between the respective receivers. If the time of the ping is known, perhaps triggered at a preselected time by a carefully calibrated clock, then the problem reduces to spherical navigation. In practice, a wide variety of USBL and LBL systems have been implemented for underwater navigation. They must all address the challenges of acoustic propagation in the ocean, which include the absorption of sound by seawater, diffraction by speed of sound variations in the underwater environment, scattering by reflecting surfaces, and acoustic noise generated by physical, geological, biological, and anthropogenic processes. Other methods of navigation include using geophysical parameters, for example, water depth, to constrain the vehicle location in the context of known maps. These geophysically based navigation methods, similar to terrain contour mapping (TERCOM) navigation used by cruise missiles, depend on having good maps ahead of time. There are software approaches in development that simultaneously build maps and use those same maps for navigation.

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These methods are called SLAM for simultaneous localization and mapping.

Using AUVs for Ocean Science Mapping the Seafloor

AUVs are becoming the platform of choice for highresolution seafloor maps. Obtaining high-resolution maps requires operating mapping sonars near the seafloor. Alternatives to an AUV include crewed submersibles and tethered platforms. Crewed submersibles are too valuable for routine mapping, and are reserved for other uses which require the presence of humans. Towed vehicles are used for sonar mapping, but have disadvantages as compared with AUVs, especially in deeper water. The principal problem is the high drag of the cable used for a tow sled, which in water depths of several thousand meters will limit speeds to approximately half a meter per second. Even at these slow speeds, a towed platform will stream behind the towing ship, creating several problems. Controlling the position of the towed vehicle over the bottom is very difficult, even when running on a constant heading. When surveying a defined area on the seafloor in a series of passes, the turns between passes may take longer than the actual survey passes themselves, as it is necessary to turn slowly to maintain control of the

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towed body. If ultrashort baseline acoustic navigation techniques are used to determine the vehicle position, then layback of the towed body behind the ship introduces significant errors as compared with having the ship directly over the sonar platform. For this reason, some commercial use of towed sonar platforms use two ships, one to tow the sonar platform, and one positioned directly over the platform to determine its precise location. Finally, surface motion of the ship will be efficiently coupled to the tow body by the tow cable. Thus, even near the seafloor, the tow body will be subject to sea state experienced by the ship. Consequently, attraction of the use of AUVs includes more economical operations and high data quality. Figure 3 shows a cost comparison of a commercial deep-water towed survey and an equivalent AUV survey. Sonar systems used on AUVs for mapping include multibeam sonar, side scan sonar, and sub-bottom profilers. Multibeam sonars, operating at frequencies of hundreds of kilohertz in the case of AUV-mounted systems, allow measurement of range to the seafloor in multiple sonar beams and are used to build up three-dimensional maps such as that in Figure 4. Side scan sonars used by AUVs also typically operate at frequencies of hundreds of kilohertz, and are used to image seafloor features. Side scan sonars are particularly useful for finding objects, for example, looking for a shipwreck resting Report preparation

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AUV

Figure 3 A comparison of the economics of deep survey taken from costs of a survey with a towed vehicle, and projected costs of the same survey with an AUV. The principal cost saving derives from the ability of the AUV to turn much faster than a deep-towed vehicle, reducing the total survey time. Also, the AUV can be acoustically tracked by its mother ship, while a towed vehicle requires a second ship for tracking because the towed vehicle will trail far behind the tow ship. Finally, mobilization and demobilization costs for the AUV can also be lower, although this depends on the size of the AUV employed.

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Figure 4 A bathymetric survey produced by an AUV at a depth of about 1000 m. Note the very small size of the survey area and high resolution of the bathymetry. Courtesy of Dave Caress, MBARI.

on the seafloor. Sub-bottom profilers use lowerfrequency sound, ranging from 1 kHz to tens of kilohertz in the case of an AUV-mounted system, to penetrate into the seafloor. Depending on the bottom type (e.g., sandy, muddy, or rock), a subbottom system might penetrate tens of meters. Cumulatively sonar payloads will consume comparatively large amounts of energy, perhaps hundreds of watts. Mapping also requires high-fidelity navigation, and thus sonar-equipped AUVs will often also use more sophisticated navigation approaches, like inertial navigation. Consequently, mapping AUVs of today are larger, more sophisticated AUVs. Observing the Water Column

AUVs provide a relatively new tool for observing the physical, chemical, and biological properties of the

ocean. The smaller, buoyancy-driven gliders are unique in their combination of mobility and endurance, moving at about a quarter of a meter per second for periods of months. Larger vehicles carry more comprehensive payloads at higher speeds, but for shorter periods. Such vehicles might operate at 1.5 m s1 for a day. A common flight profile is to fly the vehicle on a constant heading, while moving between two depth extremes in a saw-tooth pattern. Often the upper depth extreme will be close to the surface. This strategy allows the production of vertical sections of ocean properties, such as those in Figure 5. Variations of this strategy might have the vehicle moving in a lawn-mower or zigzag pattern in the horizontal plane, to develop a full threedimensional map of ocean properties. Figure 6 shows a visualization of an internal wave interacting with a phytoplankton layer using such a three-dimensional mapping strategy.

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Figure 5 Vertical sections of water properties obtained by an Odyssey AUV operating in Massachusetts Bay. The y-axis of each figure is depth, in meters, and the x-axis is horizontal distance in meters. The top section shows temperature in degrees Celsius, the middle shows chlorophyll fluorescence in arbitrary units, and the bottom shows optical backscatter, also in arbitrary units. The path of the vehicle is shown as a white line, and the interpolated values of the measured property are plotted in color. The vehicle alternated between obtaining high-resolution observations of the thin layer of organisms at the thermocline with full water column profiles.

All AUVs are limited by the availability of sensors. Temperature, salinity, currents, dissolved oxygen, nitrate, optical backscatter properties, and chlorophyll fluorescence are examples of the growing in situ sensing capabilities available for AUVs. However, many important properties, for example, pH, dissolved carbon dioxide, and dissolved iron, cannot be measured reliably from a small moving platform. Furthermore, detection of marine organisms is usually accomplished by proxy; for example, chlorophyll fluorescence provides an indicator for phytoplankton abundance. In situ methods which directly detect, classify, and quantify marine organism abundance are not available, yet are increasingly important for understanding the structure and dynamics of ocean ecosystems. Operations in Ice-covered Oceans

AUVs offer unique operational capabilities for science in ice-covered oceans. Successful under-ice

operation has been carried out with AUVs in both the Arctic and Antarctic. Sea ice poses special operational challenges for seagoing ocean scientists. For example, ships with ice-breaking capability can operate in the ice pack, but will typically not be able to hold station, or even assure that tethers and cables deployed over the side will not be severed. AUVs are attractive in that they provide horizontal mobility under ice, and the ability to conduct operations near the seafloor without the complications intrinsic in tether management. Challenges of operating AUVs under ice revolve around the need to assure return of the AUV to the ship for recovery, the process of recovering the AUV through the ice onto the ship, the potential for having an AUV fail and become trapped under ice, and the difficulty of carrying out tasks that would normally be accomplished having an AUV surface (e.g., obtaining a GPS update). Most safety strategies for AUVs in ice-free oceans default to bring

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Monterey Bay

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Figure 6 Interaction of layer of phytoplankton with an internal wave in Monterey Bay. Both physical and biological properties were measured by an Odyssey AUV, which moved in a horizontal zigzag pattern across the survey volume, while profiling constantly in the vertical plane. The phytoplankton layer, shown in green, was detected by a chlorophyll fluorescence sensor on the AUV. The cyan surface shows deflection of a level of constant density of seawater by a passing internal wave. Courtesy of John Ryan, MBARI.

the vehicle directly to the surface, for example, by dropping a weight. In the Arctic or Antarctic, this strategy could result in the vehicle becoming trapped under very thick ice, making the vehicle harder to find and potentially impossible to recover. The usual surface location devices such as RF beacons, strobes, and combinations of RF communication and satellite navigation will not work. Clearly AUV operations within the ice pack entail higher risk and a more sophisticated vehicle. Observation Systems, Observatories, and AUVs

An understanding of power consumption of AUVs provides insight to the attractiveness of employing multiple vehicles for certain ocean observation problems. In some circumstances a survey must be accomplished within a set period. In oceanography,

time-constrained surveys are most often encountered when surveying a dynamic process. For example, if the temporal decorrelation of ocean fields associated with upwelling off Monterey Bay is about 48 h, attempts to map the ocean fields need to be accomplished within that time frame. Scales of spatial variability will also determine acceptable separation of observations: for example, decorrelation lengths in Monterey Bay are on the order of 20 km, so observations need to be spaced significantly closer to minimize errors in reconstructing the ocean field. How does this relate to the number of vehicles required to accomplish such a survey? Consider a grid survey of a 100 km  100 km area with a resolution of 10 km. A single vehicle would have to travel c. 1000 km at a speed of nearly 6 m s1, traveling in a lawn-mower pattern. Using the example vehicle values from the ‘Basics of AUV

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performance’ section, the AUV would consume about 3500 W if it were capable of operating at such a high speed. In contrast, six of the same vehicles operating at their optimum speed would consume a total of 270 W. In other words, the six vehicles would consume 12 times less energy for the complete 48-h survey. Autonomous mobile platforms are making observation of the interior of the ocean more affordable and more flexible, enabling the practical realization of coupled observation–prediction systems. For example, in late summer 2003, a diverse fleet of AUVs was deployed to observe and predict the evolution of episodic wind-driven upwelling in the environs of Monterey Bay. Over 21 different autonomous robotic systems, three ships, an aircraft, a coastal ocean dynamics application radar (CODAR), drifters, floats, and numerous fixed (moored) observation assets were deployed in the

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Autonomous Ocean Sampling Network (AOSN) II field program (Figure 7). Gliding vehicles, with an endurance of weeks to months, provided a continuous presence with a minimal sensor suite. A few propeller-driven vehicles provided observations of chemical and biological ocean parameters, allowing tracking of ecosystem response to the upwelling process. Observations were fed to two oceanographic models, which provided synoptic realization of ocean fields and predicted future conditions. Among the many lessons are an improved knowledge of the scales of variability of upwelling processes, an understanding of how to scale observation systems to these processes, and insights to strategies for adaptive sampling of comparatively rapidly changing processes with comparatively slow vehicles. These lessons are particularly relevant today, given the present emphasis on developing oceanobserving systems.

Figure 7 Example of a distributed observing system using AUVs. This diagram depicts an AOSN deployment in Monterey Bay.

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See also Gliders. Remotely Operated Vehicles (ROVs).

Further Reading Allmendinger EE (1990) Submersible Vehicle Systems Design. New York: SNAME. Bradley AM (1992) Low power navigation and control for long range autonomous underwater vehicles. Proceedings of the Second International Offshore and Polar Conference, pp. 473–478. Fossen T (1995) Guidance and Control of Ocean Vehicles. New York: Wiley. Griffiths G (ed.) (2003) Technology and Applications of Autonomous Underwater Vehicles. London: Taylor and Francis.

IEEE (2001) Special Issue: Autonomous Ocean Sampling Networks. IEEE Journal of Oceanic Engineering 26(4): 437--446. Jenkins SA, Humphreys DE, Sherman J, et al. (2003) Underwater glider system study. Scripps Institution of Oceanography Technical Report No. 53. Arlington, VA: Office of Naval Research. Rudnick DL and Perry MJ (eds.) (2003) ALPS: Autonomous and Lagrangian Platforms and Sensors, Workshop Report, 64pp. http://www.geo-prose.com/ ALPS (accessed Mar. 2008).

Relevant Website http://www.mbari.org – Monterey Bay 2003 Experiment, Autonomous Ocean Sampling Network, MBARI.