Fleet Of Autonomous Underwater Vehicles Research Articles

The multi-AUV time-varying formation reconfiguration control based on rigid-graph theory and affine transformation

This paper studies the time-varying formation reconfiguration control for multiple underactuated autonomous underwater vehicles (AUVs) with an Euler–Lagrange-like model. The goal is to control a fleet of AUVs to achieve any desired formation shape using a distance-based graph rigidity and affine transformation (GR-AT) algorithm. Firstly, the distance-based graph rigidity with backstepping technology is utilized to solve the formation controlproblem, and we acquire the initial nominal formation. In the sequel, we transform the nominal formation into any desired formation shape using the properties of the affine transformation (including translation, scaling, rotation, shearing, or a combination of them). Even the geometric shapes formed can be constantly changed. The Lyapunov stability theory can ensure the uniform ultimate boundedness of whole distance errors. Finally, several simulation examples with formation reconfiguration are given to validate the efficacy of the designed control methods. Moreover, some experimental results are presented to confirm the validity and applicability of the scheme with four real bionic robot fish.

A NOVEL TIME-VARYING FORMATION OBSTACLE AVOIDANCE ALGORITHM FOR MULTIPLE AUVs, 194-207.

In this paper, a time-varying formation reconfiguration andobstacle avoidance strategy are investigated for a fleet ofautonomous underwater vehicles (AUVs) in the three-dimensional(3-D) ocean environment.

Spread Spectrum Modulation with Grassmannian Constellations for Mobile Multiple Access Underwater Acoustic Channels.

The objective of this study is to evaluate Grassmannian constellations combined with a spread spectrum multiple access scheme for underwater acoustic mobile multiple access communication systems. These communication systems enable the coordination of a fleet of Autonomous Underwater Vehicles (AUVs) from a surface or bottom control unit, e.g., a boat. Due to its robustness against phase rotation, the demodulator of Grassmannian constellations uses non-coherent detection, and the main advantage of such modulation lies in the spectrum efficiency gain with respect to conventional differential modulation. The communication system under study in this paper consists of (i), at the transmitter side, a Grassmannian modulation used in an orthogonal spread spectrum multiple access scheme called Multiuser Hyperbolic Frequency Modulation (MU-HFM) and (ii), at the receiver side, a non-coherent array decoder. The modulation and demodulation are presented as well as the considered spreading sequences. Finally, performances of the proposed transmission scheme are evaluated over replayed underwater acoustic channel responses collected at sea by a multi-sensor acoustic acquisition system.

A Scoping Study to Determine the Location-Specific WEC Threshold Size for Wave-Powered AUV Recharging

The aim of this study is to determine the threshold wave energy converter (WEC) type and size to charge a fleet of U.S. Navy autonomous underwater vehicles (AUVs) in various geographic locations of interest. The U.S. Navy deploys AUVs in locations around the world that must be charged manually, decreasing their operational endurance and creating operational limitations. Ocean waves are a potential power source that can be converted into electricity using a WEC and stored using a battery. It would be beneficial to develop a WEC that could autonomously charge AUVs offshore. Numerous locations were analyzed to determine the minimum size of a WEC capable of providing sufficient charging power and offering a strategic advantage. By predicting the WEC efficiency (based on empirical equations) and wave resource (based on available data), electrical power generation across numerous WEC types and locations was compared in MATLAB. The generalized process developed here could be used to determine the required size and type of WECs to charge a fleet of AUVs in different locations around the world.

Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method

This paper presents an optimization method for the design of the layout of an autonomous underwater vehicles (AUV) fleet to minimize the drag force. The layout of the AUV fleet is defined by two nondimensional parameters. Firstly, three-dimensional computational fluid dynamics (CFD) simulations are performed on the fleets with different layout parameters and detailed information on the hydrodynamic forces and flow structures around the AUVs is obtained. Then, based on the CFD data, a back-propagation neural network (BPNN) method is used to describe the relationship between the layout parameters and the drag of the fleet. Finally, a genetic algorithm (GA) is chosen to obtain the optimal layout parameters which correspond to the minimum drag. The optimization results show that (1) the total drag of the AUV fleet can be reduced by 12% when the follower AUV is located directly behind the leader AUV and (2) the drag of the follower AUV can be reduced by 66% when it is by the side of the leader AUV.

Remote sensing for bottom inversion

The scenarios of interest for estimating bottom and sub-bottom physical properties now encompass both deep and shallow, or very shallow, coastal waters, for the deployment of renewable energy platforms (e.g., wind farms and wave/tidal energy plants). This new paradigm, together with the continuous requirement for reducing survey time (and cost), spinned out the concept of a distributed and reconfigurable seismic survey system composed of a fleet of autonomous underwater vehicles (AUV) carrying acoustic sensing arrays. Such system poses a number of technical as well as scientific challenges, among which that of sensor positioning for optimal bottom inversion performance in a given scenario. The present work addresses this issue through the eye of the sensor configuration that maximizes diversity and proposes sampling incoherence bounds for 1, 2, and 3D array systems. Random sampling is a concept that favors diversity and allows for the usage of low-complexity inversion schemes such as those based on compressed sensing. Simulations on realistic environments illustrate the proposed concept. [This work is part of project WiMUST—Widely Scalable Mobile Underwater Sonar Technology funded under program H2020 of the European Union.]

A supervisory control policy over an acoustic communication network

This paper presents a supervisory multi-agent control policy over an acoustic communication network subject to imperfections (packet dropout and transmission delay) for localisation of an underwater flow source (e.g., source of chemical pollution, fresh water, etc.) with an unknown location at the bottom of the ocean. A two-loop control policy combined with a coding strategy for reliable communication is presented to perform the above task. A simulator is developed and used to evaluate the trade-offs between quality of communication, transmission delay and control for a fleet of autonomous underwater vehicles supervised over a noisy acoustic communication network by an autonomous surface vessel. It is illustrated that without compensation of the effects of severe random packet dropout, localisation of an unknown underwater flow source is not possible for the condition simulated just by implementing a two-loop control policy. But a two-loop control policy combined with a strategy for reliable communication locates the unknown location of flow source.

Hybrid Baseline Localization for Autonomous Underwater Vehicles

This paper presents a hybrid baseline (HBL) navigation method for autonomous underwater vehicles (AUVs). In this approach, a floating acoustic transponder is used to augment moving short baseline (MSBL) navigation, in which two transponders are mounted on a source ship. Kinematic information regarding the floating buoy and source ship are communicated via acoustic messages to the AUV fleet. Simultaneously, clock synchronization and a predefined broadcast cycle enables transponder-to-AUV range estimates based on the acoustic message time-of-flight. Using the extended Kalman (EKF) filter formulation, the broadcasted kinematic information and acoustic ranges are combined onboard each AUV in the fleet to estimate the states of the source ship, the floating transponder, and the AUV itself. Simulation was used to optimize the configuration and performance of the HBL navigation, and field tests were performed to evaluate the navigational performance. In post-processing, high-accuracy position and timing data for the source ship and floating buoy was added to the onboard navigation data in an EKF to recreate the path of the AUV. The accuracy of this post-mission localization was evaluated relative to AUV positions independently measured by an acoustic tracking array at the test facility. The resulting AUV position estimation showed a mean error of 1.59 m, an improvement over the previous result (using MSBL navigation only) of 3.30 m.

Field Testing of Moving Short‐baseline Navigation for Autonomous Underwater Vehicles using Synchronized Acoustic Messaging

This paper presents the results from field testing of a unique approach to the navigation of a fleet of autonomous underwater vehicles (AUVs) using only onboard sensors and information provided by a moving surface ship. The approach, considered moving short‐baseline (MSBL) navigation, uses two transponders mounted on a single surface ship that alternately broadcast acoustic messages containing one of the parameters of the kinematic state of the surface ship. The broadcasts are initiated according to a predefined schedule so that the one‐way travel time (OWTT) of the acoustic messages may be used to determine the range to the transponder. Each AUV in the fleet uses the surface ship state measurements and ranges provided by the acoustic messages in two extended Kalman filters (EKFs) for state estimation. The first EKF merges the intermittent surface ship state measurements with a kinematic model to estimate the state of the surface ship. This is necessary because the presented approach uses 13‐bit acoustic messages as opposed to the more commonly used 32‐byte messages, which allow the full state to be encoded in a single broadcast. The second EKF uses the current surface ship state estimate to properly interpret the acoustic ranges, combining them with a kinematic model to estimate the state of the AUV itself. Numerous MSBL navigation experiments were compared against a more traditional approach using a long‐baseline (LBL) array of transponders and OWTT acoustic ranging. The results of all tests were verified by independent LBL measures of position.

Autonomous and Adaptive Underwater Plume Detection and Tracking with AUVs: Concepts, Methods, and Available Technology

An autonomous underwater vehicle (AUV) equipped with environmental sensors and an on-board autonomy system can greatly increase the efficiency of environmental data collection and the synopticity of the data set collected simply by autonomously adapting its motion to changes it senses in its local environment. One application of this is tracking ocean features in an unknown ocean environment. This can be accomplished with one or multiple AUVs collaborating in near-real-time using acoustic communications. To further explore one example of this application, this paper focuses on using multiple AUVs to track underwater plumes. We evaluate various types of plumes (e.g., hydrothermal vent plumes, algal blooms, oil leaks), how each plume type may be detected and its spatial extent determined, what types of sensors can be used, and how AUVs can be employed to autonomously and adaptively track these dynamic plumes. Since AUVs vary significantly in design, mobility, deployment duration, on-board processing power, etc., it is also necessary to consider the best choice of AUV (or combination of AUVs) to track a plume. Thus, an operator/scientist's choice of AUV type(s) will likely depend the type of plume to be tracked, or vice versa. Since most underwater plumes are highly spatiotemporally dynamic, employing environmentally adaptive autonomy to track them with a fleet of AUVs is one of the most efficient ways to do so, given today's technology.

Cooperative Search and Survey Using Autonomous Underwater Vehicles (AUVs)

In this work, we study algorithms for cooperative search and survey using a fleet of Autonomous Underwater Vehicles (AUVs). Due to the limited energy, communication range/bandwidth, and sensing range of the AUVs, underwater search and survey with multiple AUVs brings about several new challenges since a large amount of data needs to be collected by each AUV, and any AUV may fail unexpectedly. To address the challenges and meet our objectives of minimizing the total survey time and traveled distance of AUVs, we propose a cooperative rendezvous scheme called Synchronization-Based Survey (SBS) to facilitate cooperation among a large number of AUVs when surveying a large area. In SBS, AUVs form an intermittently connected network (ICN) in that they periodically meet each other for data aggregation, control signal dissemination, and AUV failure detection/recovery. Numerical analysis and simulations have been performed to compare the performance of three variants of SBS schemes, namely, Alternating Column Synchronization (ACS), Strict Line Synchronization (SLS), and X Synchronization (XS). The results show that XS can outperform other SBS schemes in terms of the survey time and the traveled distance of AUVs. We also compare XS with nonsynchronization-based survey and the lower bound on the survey time and traveled distance. The results show that XS achieves a close to optimal performance.

Performance considerations for continuous-wave and pulsed laser line scan (LLS) imaging systems

Extended range underwater optical imaging techniques can be classified into one of two broad categories; those which use synchronously scanned narrow source and receiver paths to restrict both back-scattered and forward-scattered light reaching the receiver (continuous-wave laser line scan); and those which use pulsed sources and time-gating to remove back-scatter noise (pulsed laser line scan and pulse-gated laser line scan). Laser line scan systems are observed to perform at up to 5 to 6 optical attenuation lengths, but greater standoff distances are desirable for seabed imaging using the growing fleet of autonomous underwater vehicles (AUVs). Currently, a moderate physical separation between laser and receiver is necessary to reject near-field multiple back-scatter, which imposes restrictions on AUV miniaturization. Recent experiments and theoretical modeling reveal that significant imaging improvements are possible over the existing continuous-wave laser line scan systems (LLS), by using a pulsed-gated version of the LLS (PG-LLS). However, the use of such a technique has a greater advantage in reducing the overall form factor over conventional LLS imaging system, as well as providing greater depth-of-field. In this paper, we present experimental results comparing both LLS and PG-LLS systems for several source-receiver separations and standoff distances. These results compare favorably with images obtained from validated LLS image simulation tools, and indicate the potential for reducing the source-receiver separation and therefore the system size.

Cooperative control of underwater glider fleets by fault tolerant decentralized MPC

A fleet of Autonomous Underwater Vehicles (AUVs) moving together in a prescribed pattern can form an efficient data acquisition network. The problem is to control several AUVs such that after transients, they form a required formation and move along a desired trajectory. The capability to accomplish the mission even in case of faults, is a fundamental requirement for these kind of missions. A completely decentralized predictive control and FDI strategy is here proposed for allowing cooperation. Trough an underwater communication channel, each vehicle broadcasts its position, its future behavior and its actuator/sensor fault situation. Based both on the local and the received information, each vehicle selects the desired formation to keep and plans its future actions. Simulation results are provided to validate the approach.

Development of Regional Coastal Ocean Observatories and the Potential Benefits to Marine Sanctuaries

A network of coastal observatories is being built around the United States. While the motivations for developing these systems do not originate from marine sanctuaries per se, the sanctuaries stand to gain an unprecedented opportunity to benefit from real-time data and nowcasting/forecasting models. The construction of the observatories is being fueled by the rapid development in three enabling observational technologies. These technologies include (1) data acquisition systems that track the international constellation of IR and ocean color satellites; (2) nested grids multi-static SeaSonde surface current radars; and (3) a growing fleet of autonomous underwater vehicles. These observational assets are coupled to nowcast/forecast data assimilative models. These systems will allow the mean behavior in marine ecosystems to be defined while also providing real-time data that will allow adaptive sampling. The ability to adaptively sample the environment will allow scientists to make shrewd decisions about when and where to sample. Given this, developing the new approaches to measure critical biological processes and the geographic boundaries of those processes should be a key focus for the marine biology community. This will alter how scientists approach scientific questions in coastal waters.

Control architecture and operator interface for a free-flying robotic vehicle

Space and underwater vehicles with robotic arms can severely tax the capability of conventional control systems. Submersible vehicles used in neutral buoyancy simulation are subject to even greater demands since they must simulate the dynamics of spacecraft in orbit as well as function as a remotely-operated underwater vehicle. In this report, the onboard control architecture, human-machine interface, and vehicle/operator communications are described for one such vehicle in operation at the University of Maryland Neutral Buoyancy Research Facility (NBRF). The Ranger Neutral Buoyancy Vehicle (RNBV) exemplifies the high-dimensional, computationally intensive nature of the current fleet of autonomous underwater vehicles while its complement of four manipulators exceeds the capabilities of most remotely operated vehicles in service today. The sensor-based, embedded onboard control system is described, and its implementation using multiple control stations is discussed.