A quick look at the latest AUV-related articles published in JOE
31 July 2020
An autonomous underwater vehicle, or AUV, is a self-propelled, unmanned, untethered underwater vehicle capable of carrying out simple activities with little or no human supervision .
AUVs are heavily used in ocean exploration. Since they can access the depths of the ocean from up-close, they allow us to obtain better-quality data from these regions that are hard to access via other means. They can be used, for example, for obtaining high-resolution maps of the seafloor , or as survey platforms to characterize physical, chemical, or biological properties of the water [1, 2, 3]. AUVs or swarms of AUVs may also be used for monitoring pollution , harbour patrolling for ship guidance, security and surveillance, and resource assesment [3, 4, 5, 6].
Technology development and occasional scientific use of AUVs started since the 1960s and 70s [1, 3]. Since then, advancements in the efficiency, size, and memory capacity of computers have enhanced their potential , and their routine use for science has been observed the last few years . AUVs are likely to become ubiquitous tools for ocean exploration and sampling, and are an increasingly important tool for oceanographic research [2, 7].
In its April 2020 issue, the IEEE Journal of Oceanic Engineering published nine articles on AUVs, amongst other topics. We list here the articles and abstracts of these papers, representing the cutting edge of research on AUVs.
Articles and abstracts:
Global Exponential Tracking Control for an Autonomous Surface Vessel: An Integral Concurrent Learning Approach - Z. I. Bell, J. Nezvadovitz, A. Parikh, E. M. Schwartz, W. E. Dixon
In this paper, an adaptive controller is developed for a fully actuated marine vehicle where the rigid body and hydrodynamic parameters are unknown. A data-based integral concurrent learning method is used to compensate for the uncertain parameters. A Lyapunov-based analysis is presented to show that the closed-loop system is globally exponentially stable and the uncertain parameters are identified exponentially without the requirement of persistence of excitation. Experimental results on an autonomous surface vessel operating on a lake illustrate the controller's ability to track figure-8 trajectories in environments with small disturbances.
Station-Keeping Underwater Gliders Using a Predictive Ocean Circulation Model and Applications to SWOT Calibration and Validation - E. B. Clark, A. Branch, S. Chien, F. Mirza, J. D. Farrara, Y. Chao, D. Fratantoni, D. Aragon, O. Schofield, M. M. Flexas, A. Thompson
Instrumented ocean moorings are the gold standard for gathering in situ measurements at a fixed location in the ocean. Because they require installation by a ship and must be secured to the seafloor, moorings are expensive, logistically difficult to deploy and maintain, and are constrained to one location once installed. To circumvent these issues, previous studies have attempted to utilize autonomous underwater gliders as platforms for virtual moorings, but these attempts have yielded comparatively large station-keeping errors due to the difficulty of glider control in dynamic ocean currents. We implemented an adaptive planner using a vehicle motion model and a predictive ocean circulation model to improve station-keeping performance by incorporating anticipated currents into glider control. We demonstrate improved station-keeping performance using our planner in both simulation and in-field deployment results, and report smaller average station-keeping error than the Monterey Bay Aquarium Research Institute's M1 mooring. Finally, we utilize our simulation framework to conduct a feasibility study on using an array of autonomous gliders as virtual moorings to conduct critical calibration and validation (CalVal) for the upcoming National Aeronautics and Space Administration, Surface Water and Ocean Topography (SWOT) Mission, instead of using permanent moorings. We show that this approach carries several advantages and has potential to meet the SWOT CalVal objectives.
Hydrodynamic Parameter Estimation for Autonomous Underwater Vehicles - S. B. Gibson and D. J. Stilwell
This paper experimentally evaluates various hydrodynamic damping models for streamlined tail-controlled autonomous underwater vehicles (AUVs). We seek damping models that can be used to accurately predict the motion of a streamlined AUV, but do not possess unnecessary complexity. Additionally, we investigate the efficacy of estimating forces and moments due to control surfaces with the same data from which damping parameters are estimated. We then directly compare the results of estimated control surface forces and moments with that obtained using high-fidelity software tools. We use an offline least-squares method and an adaptive identifier method to approximate model coefficients from data attained from field trials. Field trials were conducted using two AUVs, and the experimental results are presented. The overall goal of this paper is to determine the form of a dynamic model that can be identified from data acquired during field trials.
Autonomous Underwater Vehicle Homing With a Single Range-Only Beacon - J. R. Keane, A. L. Forrest, H. Johannsson, and D. Battle
Homing behavior for autonomous underwater vehicles (AUVs) is vital for autonomous docking and indispensable for recovery of vehicles in logistically difficult or hazardous conditions. Homing to a single acoustic beacon is a low-logistics solution to this engineering challenge. A homing application has been developed in C++ that applies a multilateration-based localization algorithm to estimate transponder location for homing. Mission oriented operating suite interval programming (MOOS-IvP) was implemented as a backseat driver on a Teledyne Gavia AUV to enhance the AUV with adaptive maneuvering capabilities; thus, enabling mission waypoints to be dynamically updated by the homing application (pHomeToBeacon) through the MOOS database and a developed iGavia crewmember. To demonstrate MOOS-IvP-GAVIA and homing capabilities using this first-principles approach to localization, field trials were undertaken in Kópavogur, Iceland, in June 2015 and proved consistent homing to a single beacon within 15 m accuracy. These trials were an industry-first of deploying a user-developed application on MOOS-IvP-GAVIA and of having a Gavia enhanced with adaptive maneuvering capabilities for homing. This new capability enables Gavia AUV to be used as a platform for future developer-led autonomy and applications. Ultimately, pHomeToBeacon will enable any AUV enhanced with MOOS-IvP to use acoustics to home to a surface vessel (stationary or underway) in preparation for autonomous subsea docking and recovery.
Simulation-Driven Optimization of Underwater Docking Station Design - B. R. Page and N. Mahmoudian
This paper presents the optimization of a novel docking design for docking and charging of autonomous underwater vehicles. The docking design has been optimized to maximize the capture envelope and minimize the maximum contact force. Two design parameters, sweep angle and ramp angle, were optimized as was the velocity during terminal homing and capture. The optimization was an exhaustive optimization with 5600 unique simulations completed that included the vehicle hydrodynamics, impact dynamics, and controller. Unique to the presented docking design is the ability to support a wide variety of vehicles from different size classes through its simplified funnel design and use of a docking adapter as validated in simulation with a Dolphin II AUV and Bluefin SandShark. The only part of the docking system that contacts the vehicle is a standardized docking adapter that is meant as a drop-in replacement for an antenna mast. The presented docking system is low-cost, compact, and can be deployed in a wide variety of situations including mobile docking.
Theoretical and Experimental Investigations on the Design of a Hybrid Depth Controller for a Standalone Variable Buoyancy System—vBuoy - T. Ranganathan, V. Singh, A. Thondiyath
Design of controllers for underwater vehicles is challenging due to their nonlinear dynamics, time-varying model parameters, and environmental disturbances, which are difficult to measure or estimate. Conventional linear controllers sometimes fail to handle these issues effectively and hence it is necessary to design special controllers that are robust under such circumstances. Variable buoyancy (VB) engines are used in many underwater vehicles and standalone buoyancy modules are being developed for multiple underwater applications. Design and analysis of a hybrid depth controller for a single degree of freedom, standalone VB module, vBuoy, is presented in this paper. The design and mathematical model of the vBuoy is presented along with its open-loop performance analysis. A hybrid controller, which captures the best characteristics of a proportional-integral-derivative controller, a linear quadratic regulator, and a sliding mode controller, is designed for the depth control of the module. Based on the desired transient and steady-state behavior of the system, a supervisory controller is used to switch between the conventional controllers. The comparison of simulation results between the proposed hybrid controller and the conventional controllers shows a significant improvement in the closed-loop performance. The performance is evaluated using the parameters such as rise time, percentage overshoot, settling time, and root mean square error. The same has been implemented in an experimental vBuoy prototype to verify the performance of the hybrid controller and also to validate the robustness of the controller. Based on the simulation and experimental results, it was observed that the hybrid controller improves the trajectory tracking performance by 28%-33%.
Improving Steady and Starting Characteristics of Wireless Charging for an AUV Docking System - C. Yang, M. Lin, D. Li
The study of extending navigation range of autonomous underwater vehicles (AUVs) is popular for ocean exploration. A common method is to use the underwater docking station to recover and recharge AUVs. This paper uses the simple but effective inductive power transmission (IPT) system to realize underwater wireless charging for an AUV docking system. A design procedure is provided to select the optimal underwater operating frequency of the IPT system in consideration of eddy-current loss in seawater. To solve the power failure problem of the control power system, an inrush current limiter (ICL) is proposed on the basis of the dynamic model of the IPT system. The test results in the laboratory experiment and sea trial both verify the advantages of the frequency design method and the effectiveness of the ICL.
Better understanding of the loss mechanisms and higher confidence in material data for piezoelectric materials are very important for transducer manufacturers. In this paper, a method is described to characterize these loss mechanisms using a global optimization algorithm, a 1-D equivalent circuit, and a simple experimental measurement. Two different cost functions were used in the optimization algorithm, one based on impedance and the other based on admittance. The sensitivities of these cost functions to the parameters being characterized are shown to be nonuniform. The results are compared to the results obtained from a local optimization method to show the advantage of using a global optimization algorithm. A way to quantify the uncertainty of the results is introduced by looking at the difference between the results obtained from the two different cost functions. It is shown here that the more ambient noise there is in the data, the wider the gap between the results found by the two cost functions. However, although the results from the individual cost functions diverge from the correct values with increasing noise, the average of the two cost function results remains within 5% of the original value. Hence, even with noise in the measured data, the use of two cost functions can yield accurate material parameters.
An Optical Image Transmission System for Deep Sea Creature Sampling Missions Using Autonomous Underwater Vehicle - J. Ahn, S. Yasukawa, T. Sonoda, Y. Nishida, K. Ishii, T. Ura
The exploration of oceans using autonomous underwater vehicles (AUVs) is necessary for activities, such as the sustainable management of fishery resources, extraction of seafloor minerals and energy resources, and inspection of underwater infrastructure. As the next step in ocean exploration, AUVs are expected to employ end-effectors to make physical contact with seafloor creatures and materials. We propose a scenario for realizing a sampling mission using an AUV that is equipped to sample marine life. In this scenario, the sampling AUV observes the seafloor while concurrently transmitting the observed images to a surface vessel for inspection by the AUV operators. If the received images show an object of interest, the object is selected as a candidate of sampling target by the operators, who send a sampling command to the AUV. After receiving the command, the AUV returns to the target area and attempts to sample it. In this paper, we propose a system for transmitting images of the seafloor as part of the sampling-mission scenario. The proposed image transmission system includes a process for enhancing images of the deep seafloor, a process for selecting interesting images, and processes for compressing and reconstructing images. The image enhancement process resolves imaging problems resulting from light attenuation, such as color attenuation and uneven illumination. The process for selecting interesting images selects those that contain interesting objects, such as marine life. The selection process prevents the transmission of meaningless images that contain only flat sand on the seafloor. The proposed image compression method, which is based on color depth compression, reduces the amount of data. The combined process of selecting an interesting image and compressing it reduces various problems in acoustic communication, such as low information density and data loss. Instead of an overall image, part of an overall image is transmitted by a set of data packet, and each received data packet is reconstructed onboard the vessel. Because of image compression, the colors of a reconstructed image differ from those of an enhanced image. However, the reconstructed image contains similar colors, and the structural similarity index was found to be 91.4% by evaluating images that were subjected to a 4-b color compression. The proposed image transmission system was tested in the Sea of Okhotsk, and these tests were performed four times in different sea areas (minimum depth 380 m, maximum depth 590 m). The results show that the size of the data for a single image was reduced by a factor of 18 using the proposed image compression process, with each image taking 3.7 s to be transmitted via an acoustic modem (20 kb/s). Of the automatically selected images, 63% contained marine life, and the total transmission success rate was 22%.
 J.G. Bellingham, "Platforms: Autonomous Underwater Vehicles", in Encyclopedia of Ocean Sciences (Second Edition), 2009, https://www.sciencedirect.com/science/article/pii/B978012374473900730X, Accessed 25th July 2020
 J Hwang, N Bose, S Fan, "AUV adaptive sampling methods: A review"- Applied Sciences, 2019 - mdpi.com
 "AUV Navigation and Localization: A Review", Liam Paull, Sajad Saeedi, Mae Seto, and Howard Li, IEEE Journal of Oceanic Engineering, VOL. 39, NO. 1, JANUARY 2014
 "Chemical plume tracing via an autonomous underwater vehicle", J.A. Farrell, Shuo Pang and Wei Li, IEEE Journal of Oceanic Engineering, Volume: 30 , Issue: 2 , April 2005
 Huet, C., Mastroddi, F. Autonomy for underwater robots—a European perspective. Auton Robot 40, 1113–1118 (2016). https://doi.org/10.1007/s10514-016-9605-x
 "Acoustic Assessment of Polymetallic Nodule Abundance Using Sidescan Sonar and Altimeter", W. L. Jie, B. Kalyan, V. N. Hari and M. Chitre, IEEE Journal of Oceanic Engineering, doi: 10.1109/JOE.2020.2967108.
 Monterey Bay Aquarium Research Institute, "Autonomous underwater vehicles", https://www.mbari.org/at-sea/vehicles/autonomous-underwater-vehicles/, Accessed 25th July 2020