Closed‐loop one‐way‐travel‐time navigation using low‐grade odometry for autonomous underwater vehicles

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of FIeld Robotics 35 (2018): 421-434, doi:10.1002/rob.21746.This paper extends the progress of single beacon one‐way‐travel‐time (OWTT) range measurements for constraining XY position for autonomous underwater vehicles (AUV). Traditional navigation algorithms have used OWTT measurements to constrain an inertial navigation system aided by a Doppler Velocity Log (DVL). These methodologies limit AUV applications to where DVL bottom‐lock is available as well as the necessity for expensive strap‐down sensors, such as the DVL. Thus, deep water, mid‐water column research has mostly been left untouched, and vehicles that need expensive strap‐down sensors restrict the possibility of using multiple AUVs to explore a certain area. This work presents a solution for accurate navigation and localization using a vehicle's odometry determined by its dynamic model velocity and constrained by OWTT range measurements from a topside source beacon as well as other AUVs operating in proximity. We present a comparison of two navigation algorithms: an Extended Kalman Filter (EKF) and a Particle Filter(PF). Both of these algorithms also incorporate a water velocity bias estimator that further enhances the navigation accuracy and localization. Closed‐loop online field results on local waters as well as a real‐time implementation of two days field trials operating in Monterey Bay, California during the Keck Institute for Space Studies oceanographic research project prove the accuracy of this methodology with a root mean square error on the order of tens of meters compared to GPS position over a distance traveled of multiple kilometers.This work was supported in part through funding from the Weston Howland Jr. Postdoctoral Scholar Award (BCC), the U.S. Navy's Civilian Institution program via the MIT/WHOI Joint Program (JHK),W. M. Keck Institute for Space Studies, and theWoods Hole Oceanographic Institution

Synchronous-clock range-angle relative acoustic navigation: a unified approach to multi-AUV localization, command, control, and coordination

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rypkema, N., Schmidt, H., & Fischell, E. Synchronous-clock range-angle relative acoustic navigation: a unified approach to multi-AUV localization, command, control, and coordination. Journal of Field Robotics, 2(1), (2022): 774–806, https://doi.org/10.55417/fr.2022026.This paper presents a scalable acoustic navigation approach for the unified command, control, and coordination of multiple autonomous underwater vehicles (AUVs). Existing multi-AUV operations typically achieve coordination manually by programming individual vehicles on the surface via radio communications, which becomes impractical with large vehicle numbers; or they require bi-directional intervehicle acoustic communications to achieve limited coordination when submerged, with limited scalability due to the physical properties of the acoustic channel. Our approach utilizes a single, periodically broadcasting beacon acting as a navigation reference for the group of AUVs, each of which carries a chip-scale atomic clock and fixed ultrashort baseline array of acoustic receivers. One-way travel-time from synchronized clocks and time-delays between signals received by each array element allow any number of vehicles within receive distance to determine range, angle, and thus determine their relative position to the beacon. The operator can command different vehicle behaviors by selecting between broadcast signals from a predetermined set, while coordination between AUVs is achieved without intervehicle communication by defining individual vehicle behaviors within the context of the group. Vehicle behaviors are designed within a beacon-centric moving frame of reference, allowing the operator to control the absolute position of the AUV group by repositioning the navigation beacon to survey the area of interest. Multiple deployments with a fleet of three miniature, low-cost SandShark AUVs performing closed-loop acoustic navigation in real-time provide experimental results validated against a secondary long-baseline positioning system, demonstrating the capabilities and robustness of our approach with real-world data.This work was partially supported by the Office of Naval Research, the Defense Advanced Research Projects Agency, Lincoln Laboratory, and the Reuben F. and Elizabeth B. Richards Endowed Funds at WHOI

An Acoustic Network Navigation System

This work describes a system for acoustic‐based navigation that relies on the addition of localization services to underwater networks. The localization capability has been added on top of an existing network, without imposing constraints on its structure/operation. The approach is based on the inclusion of timing information within acoustic messages through which it is possible to know the time of an acoustic transmission in relation to its reception. Exploiting such information at the network application level makes it possible to create an interrogation scheme similar to that of a long baseline. The advantage is that the nodes/autonomous underwater vehicles (AUVs) themselves become the transponders of a network baseline, and hence there is no need for dedicated instrumentation. The paper reports at sea results obtained from the COLLAB–NGAS14 experimental campaign. During the sea trial, the approach was implemented within an operational network in different configurations to support the navigation of the two Centre for Maritime Research and Experimentation Ocean Explorer (CMRE OEX) vehicles. The obtained results demonstrate that it is possible to support AUV navigation without constraining the network design and with a minimum communication overhead. Alternative solutions (e.g., synchronized clocks or two‐way‐travel‐time interrogations) might provide higher precision or accuracy, but they come at the cost of impacting on the network design and/or on the interrogation strategies. Results are discussed, and the performance achieved at sea demonstrates the viability to use the system in real, large‐scale operations involving multiple AUVs. These results represent a step toward location‐aware underwater networks that are able to provide node localization as a service

Energy efficient navigational methods for autonomous underwater gliders in surface denied regions

Autonomous underwater gliders routinely perform long duration profiling missions while characterizing the chemical, physical and biological properties of the water column. These measurements have opened up new ways of observing the ocean’s processes and their interactions with the atmosphere across time and length scales which were not previously possible. Extending these observations to ice-covered regions is of importance due to their role in ocean circulation patterns, increased economic interest in these areas and a general sparsity of observations. This thesis develops an energy optimal depth controller, a terrain aided navigation method and a magnetic measurement method for an autonomous underwater glider. A review of existing methods suitable for navigation in underwater environments as well as the state of the art in magnetic measurement and calibration techniques is also presented. The energy optimal depth controller is developed and implemented based on an integral state feedback controller. A second order linear time invariant system is identified from field data and used to compute the state feedback controller gains through an augmented linear quadratic regulator. The resulting gains and state feedback controller methodology are verified through field trials and found to control the depth of the vehicle while losing less than one percent of the vehicle’s propulsive load to control inputs or lift induced drag. The terrain aided navigation method is developed based on a jittered bootstrap algorithm which is a type of particle filter that makes use of the vehicle’s deadreckoned navigation solution, onboard altimeter and a local digital parameter model (DPM). An evaluation is performed through post-processing offline location estimates from field trials which took place in Holyrood Arm, Newfoundland, overlapping a previously collected DPM. During the post-processing of these trials, the number of particles, jittering variance and DPM grid cell size were varied. Online open loop field trials were performed through integrating a new single board computer. In these trials the localization error remained bounded and improved on the dead reckoning error, validating the filter despite the large dead-reckoned errors, single beam altitude measurements, and short test duration. Terrain aided navigation methods perform poorly in regions of flat terrain or in deep water where the seafloor is beyond the range of the altimeter. Magnetic measurements of the Earth’s main field have been proposed previously to augment terrain aided navigation algorithms in these regions. To this end a low power magnetic instrumentation suite for an underwater glider has been developed. Two calibration methodologies were also developed and compared against regional digital models of the magnetic field. The calibration methods include one for which the actuators in the vehicle were kept in fixed locations and a second for which the calibration coefficients were parameterized for the actuator locations. Both methods were found to agree with the low frequency content in the a-priori regional magnetic anomaly grids

Cooperative localisation in underwater robotic swarms for ocean bottom seismic imaging.

Spatial information must be collected alongside the data modality of interest in wide variety of sub-sea applications, such as deep sea exploration, environmental monitoring, geological and ecological research, and samples collection. Ocean-bottom seismic surveys are vital for oil and gas exploration, and for productivity enhancement of an existing production facility. Ocean-bottom seismic sensors are deployed on the seabed to acquire those surveys. Node deployment methods used in industry today are costly, time-consuming and unusable in deep oceans. This study proposes the autonomous deployment of ocean-bottom seismic nodes, implemented by a swarm of Autonomous Underwater Vehicles (AUVs). In autonomous deployment of ocean-bottom seismic nodes, a swarm of sensor-equipped AUVs are deployed to achieve ocean-bottom seismic imaging through collaboration and communication. However, the severely limited bandwidth of underwater acoustic communications and the high cost of maritime assets limit the number of AUVs that can be deployed for experiments. A holistic fuzzy-based localisation framework for large underwater robotic swarms (i.e. with hundreds of AUVs) to dynamically fuse multiple position estimates of an autonomous underwater vehicle is proposed. Simplicity, exibility and scalability are the main three advantages inherent in the proposed localisation framework, when compared to other traditional and commonly adopted underwater localisation methods, such as the Extended Kalman Filter. The proposed fuzzy-based localisation algorithm improves the entire swarm mean localisation error and standard deviation (by 16.53% and 35.17% respectively) at a swarm size of 150 AUVs when compared to the Extended Kalman Filter based localisation with round-robin scheduling. The proposed fuzzy based localisation method requires fuzzy rules and fuzzy set parameters tuning, if the deployment scenario is changed. Therefore a cooperative localisation scheme that relies on a scalar localisation confidence value is proposed. A swarm subset is navigationally aided by ultra-short baseline and a swarm subset (i.e. navigation beacons) is configured to broadcast navigation aids (i.e. range-only), once their confidence values are higher than a predetermined confidence threshold. The confidence value and navigation beacons subset size are two key parameters for the proposed algorithm, so that they are optimised using the evolutionary multi-objective optimisation algorithm NSGA-II to enhance its localisation performance. Confidence value-based localisation is proposed to control the cooperation dynamics among the swarm agents, in terms of aiding acoustic exteroceptive sensors. Given the error characteristics of a commercially available ultra-short baseline system and the covariance matrix of a trilaterated underwater vehicle position, dead reckoning navigation - aided by Extended Kalman Filter-based acoustic exteroceptive sensors - is performed and controlled by the vehicle's confidence value. The proposed confidence-based localisation algorithm has significantly improved the entire swarm mean localisation error when compared to the fuzzy-based and round-robin Extended Kalman Filter-based localisation methods (by 67.10% and 59.28% respectively, at a swarm size of 150 AUVs). The proposed fuzzy-based and confidence-based localisation algorithms for cooperative underwater robotic swarms are validated on a co-simulation platform. A physics-based co-simulation platform that considers an environment's hydrodynamics, industrial grade inertial measurement unit and underwater acoustic communications characteristics is implemented for validation and optimisation purposes

Cooperative localization for autonomous underwater vehicles

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2009Self-localization of an underwater vehicle is particularly challenging due to the absence of Global Positioning System (GPS) reception or features at known positions that could otherwise have been used for position computation. Thus Autonomous Underwater Vehicle (AUV) applications typically require the pre-deployment of a set of beacons. This thesis examines the scenario in which the members of a group of AUVs exchange navigation information with one another so as to improve their individual position estimates. We describe how the underwater environment poses unique challenges to vehicle navigation not encountered in other environments in which robots operate and how cooperation can improve the performance of self-localization. As intra-vehicle communication is crucial to cooperation, we also address the constraints of the communication channel and the effect that these constraints have on the design of cooperation strategies. The classical approaches to underwater self-localization of a single vehicle, as well as more recently developed techniques are presented. We then examine how methods used for cooperating land-vehicles can be transferred to the underwater domain. An algorithm for distributed self-localization, which is designed to take the specific characteristics of the environment into account, is proposed. We also address how correlated position estimates of cooperating vehicles can lead to overconfidence in individual position estimates. Finally, key to any successful cooperative navigation strategy is the incorporation of the relative positioning between vehicles. The performance of localization algorithms with different geometries is analyzed and a distributed algorithm for the dynamic positioning of vehicles, which serve as dedicated navigation beacons for a fleet of AUVs, is proposed.This work was funded by Office of Naval Research grants N00014-97-1-0202, N00014-05-1-0255, N00014-02-C-0210, N00014-07-1-1102 and the ASAP MURI program led by Naomi Leonard of Princeton University

A Virtual Ocean framework for environmentally adaptive, embedded acoustic navigation on autonomous underwater vehicles

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2021.Autonomous underwater vehicles (AUVs) are an increasingly capable robotic platform, with embedded acoustic sensing to facilitate navigation, communication, and collaboration. The global positioning system (GPS), ubiquitous for air- and terrestrial-based drones, cannot position a submerged AUV. Current methods for acoustic underwater navigation employ a deterministic sound speed to convert recorded travel time into range. In acoustically complex propagation environments, however, accurate navigation is predicated on how the sound speed structure affects propagation. The Arctic’s Beaufort Gyre provides an excellent case study for this relationship via the Beaufort Lens, a recently observed influx of warm Pacific water that forms a widespread yet variable sound speed lens throughout the gyre. At short ranges, the lens intensifies multipath propagation and creates a dramatic shadow zone, deteriorating acoustic communication and navigation performance. The Arctic also poses the additional operational challenge of an ice-covered, GPSdenied environment. This dissertation demonstrates a framework for a physics-based, model-aided, real-time conversion of recorded travel time into range—the first of its kind—which was essential to the successful AUV deployment and recovery in the Beaufort Sea, in March 2020. There are three nominal steps. First, we investigate the spatio-temporal variability of the Beaufort Lens. Second, we design a human-in-the-loop graphical decision-making framework to encode desired sound speed profile information into a lightweight, digital acoustic message for onboard navigation and communication. Lastly, we embed a stochastic, ray-based prediction of the group velocity as a function of extrapolated source and receiver locations. This framework is further validated by transmissions among GPS-aided modem buoys and improved upon to rival GPS accuracy and surpass GPS precision. The Arctic is one of the most sensitive regions to climate change, and as warmer surface temperatures and shrinking sea ice extent continue to deviate from historical conditions, the region will become more accessible and navigable. Underwater robotic platforms to monitor these environmental changes, along with the inevitable rise in human traffic related to trade, fishing, tourism, and military activity, are paramount to coupling national security with international climate security.Office of Naval Research (N00014-14-1-0214) — GOATS’14 Adaptive and Collaborative Exploitation of 3-Dimensional Environmental Acoustics in Distributed Undersea Networks Draper Laboratory Incorporated (SC001-0000001039) — Positioning System for Deep Ocean Navigation (POSYDON) Office of Naval Research (N00014-16-1-2129) — MURI: The Information Content of Ocean Noise: Theory and Experiment Office of Naval Research (N00014-17-1-2474) — Environmentally Adaptive Acoustic Communication and Navigation in the New Arctic Office of Naval Research (N00014-19-1-2716) — TFO: Assessing Realism and Uncertainties in Navy Decision Aids Department of Defense, Office of Naval Research — National Defense, Science, and Engineering Graduate Fellowshi

Underwater & out of sight: towards ubiquity in underwater robotics

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2019.The Earth's oceans holds a wealth of information currently hidden from us. Effective measurement of its properties could provide a better understanding of our changing climate and insights into the creatures that inhabit its waters. Autonomous underwater vehicles (AUVs) hold the promise of penetrating the ocean environment and uncovering its mysteries; and progress in underwater robotics research over the past three decades has resulted in vehicles that can navigate reliably and operate consistently, providing oceanographers with an additional tool for studying the ocean. Unfortunately, the high cost of these vehicles has stifled the democratization of this technology. We believe that this is a consequence of two factors. Firstly, reliable navigation on conventional AUVs has been achieved through the use of a sophisticated sensor system, namely the Doppler velocity log (DVL)-aided inertial navigation system (INS), which drives up vehicle cost, power use and size. Secondly, deployment of these vehicles is expensive and unwieldy due to their complexity, size and cost, resulting in the need for specialized personnel for vehicle operation and maintenance. The recent development of simpler, low-cost, miniature underwater robots provides a solution that mitigates both these factors; however, removing the expensive DVL-aided INS means that they perform poorly in terms of navigation accuracy. We address this by introducing a novel acoustic system that enables AUV self-localization without requiring a DVL-aided INS or on-board active acoustic transmitters. We term this approach Passive Inverted Ultra-Short Baseline (piUSBL) positioning. The system uses a single acoustic beacon and a time-synchronized, vehicle-mounted, passive receiver array to localize the vehicle relative to this beacon. Our approach has two unique advantages: first, a single beacon lowers cost and enables easy deployment; second, a passive receiver allows the vehicle to be low-power, low-cost and small, and enables multi-vehicle scalability. Providing this new generation of small and inexpensive vehicles with accurate navigation can potentially lower the cost of entry into underwater robotics research and further its widespread use for ocean science. We hope that these contributions in low-cost underwater navigation will enable the ubiquitous and coordinated use of robots to explore and understand the underwater domain.This research was funded and supported by a number of sponsors; we gratefully acknowledge them below. Defense Advanced Research Projects Agency (DARPA) and SSC Pacific via Applied Physical Sciences Corp. (APS) under contract number N66001-11-C-4115. SSC Pacific via Applied Physical Sciences Corp. (APS) under award number N66001-14-C-4031. Air Force via Lincoln Laboratory under award number FA8721-05-C-0002. Office of Naval Research (ONR) via University of California-San Diego under award number N00014-13-1-0632. Defense Advanced Research Projects Agency (DARPA) via Applied Physical Sciences Corp. (APS) under award number HR0011-18-C-0008. Office of Naval Research (ONR) under award number N00014-17-1-2474

Contributions to automated realtime underwater navigation

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2012This dissertation presents three separate–but related–contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field–some have been demonstrated in all three arenas. The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors. The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current–the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework–without altering the filter structure or requiring any ad-hoc adjustments. The end result is a mathematically principled treatment of the delay that leads to more consistent estimates with lower error and uncertainty. Field results from dead reckoning aided by acoustic positioning systems demonstrate the applicability of this approach to real-world problems in underwater navigation.I have been financially supported by: the National Defense Science and Engineering Graduate (NDSEG) Fellowship administered by the American Society for Engineering Education, the Edwin A. Link Foundation Ocean Engineering and Instrumentation Fellowship, and WHOI Academic Programs office

Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks

[EN] In underwater acoustic modem design, pure asynchrony can contribute to improved wake-up coordination, thus avoiding energy-inefficient synchronization mechanisms. Nodes are designed with a pre-receptor and an acoustically adapted Radio Frequency Identification system, which wakes up the node when it receives an external tone. The facts that no synchronism protocol is necessary and that the time between waking up and packet reception is narrow make pure asynchronism highly efficient for energy saving. However, handshaking in the Medium Control Access layer must be adapted to maintain the premise of pure asynchronism. This paper explores different models to carry out this type of adaptation, comparing them via simulation in ns-3. Moreover, because energy saving is highly important to data gathering driven by underwater vehicles, where nodes can spend long periods without connection, this paper is focused on multi-hop topologies. When a vehicle appears in a 3D scenario, it is expected to gather as much information as possible in the minimum amount of time. Vehicle appearance is the event that triggers the gathering process, not only from the nearest nodes but from every node in the 3D volume. Therefore, this paper assumes, as a requirement, a topology of at least three hops. The results show that classic handshaking will perform better than tone reservation because hidden nodes annulate the positive effect of channel reservation. However, in highly dense networks, a combination model with polling will shorten the gathering time.Blanc Clavero, S. (2020). Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks. Sensors. 20(5):1-16. https://doi.org/10.3390/s20051407S116205Roy, A., & Sarma, N. (2018). Effects of Various Factors on Performance of MAC Protocols for Underwater Wireless Sensor Networks. Materials Today: Proceedings, 5(1), 2263-2274. doi:10.1016/j.matpr.2017.09.228Awan, K. M., Shah, P. A., Iqbal, K., Gillani, S., Ahmad, W., & Nam, Y. (2019). Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges. Wireless Communications and Mobile Computing, 2019, 1-20. doi:10.1155/2019/6470359Rudnick, D. L., Davis, R. E., Eriksen, C. C., Fratantoni, D. M., & Perry, M. J. (2004). Underwater Gliders for Ocean Research. Marine Technology Society Journal, 38(2), 73-84. doi:10.4031/002533204787522703Petritoli, E., & Leccese, F. (2018). High Accuracy Attitude and Navigation System for an Autonomous Underwater Vehicle (AUV). ACTA IMEKO, 7(2), 3. doi:10.21014/acta_imeko.v7i2.535Nam, H. (2018). Data-Gathering Protocol-Based AUV Path-Planning for Long-Duration Cooperation in Underwater Acoustic Sensor Networks. IEEE Sensors Journal, 18(21), 8902-8912. doi:10.1109/jsen.2018.2866837Sun, J., Hu, F., Jin, W., Wang, J., Wang, X., Luo, Y., … Zhang, A. (2020). Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences. Sensors, 20(3), 893. doi:10.3390/s20030893Wahid, A., Lee, S., Kim, D., & Lim, K.-S. (2014). MRP: A Localization-Free Multi-Layered Routing Protocol for Underwater Wireless Sensor Networks. Wireless Personal Communications, 77(4), 2997-3012. doi:10.1007/s11277-014-1690-6Sánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2012). An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks. Sensors, 12(6), 6837-6856. doi:10.3390/s120606837Li, S., Qu, W., Liu, C., Qiu, T., & Zhao, Z. (2019). Survey on high reliability wireless communication for underwater sensor networks. Journal of Network and Computer Applications, 148, 102446. doi:10.1016/j.jnca.2019.102446Jiang, S. (2018). State-of-the-Art Medium Access Control (MAC) Protocols for Underwater Acoustic Networks: A Survey Based on a MAC Reference Model. IEEE Communications Surveys & Tutorials, 20(1), 96-131. doi:10.1109/comst.2017.2768802Chirdchoo, N., Soh, W., & Chua, K. C. (2008). RIPT: A Receiver-Initiated Reservation-Based Protocol for Underwater Acoustic Networks. IEEE Journal on Selected Areas in Communications, 26(9), 1744-1753. doi:10.1109/jsac.2008.081213Zenia, N. Z., Aseeri, M., Ahmed, M. R., Chowdhury, Z. I., & Shamim Kaiser, M. (2016). Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: A survey. Journal of Network and Computer Applications, 71, 72-85. doi:10.1016/j.jnca.2016.06.005Khasawneh, A., Latiff, M. S. B. A., Kaiwartya, O., & Chizari, H. (2017). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks, 24(6), 2061-2075. doi:10.1007/s11276-017-1461-xSánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2015). An Acoustic Modem Featuring a Multi-Receiver and Ultra-Low Power. Circuits and Systems, 06(01), 1-12. doi:10.4236/cs.2015.6100