Key Features of the Autonomous Underwater Vehicles for Marine Surveillance Missions

Abstract

This paper gives an overview of autonomous underwater vehicles’ (AUVs’) applications, shapes due to the specific kinetic and dynamic requirements, state estimation, control, navigation, and communication principles. The emphasis is put on AUVs deployed within EU Horizon 2020 COMPASS 2020 (Coordination of Maritime assets for Persistent and Systematic Surveillance 2020) project for marine surveillance and reconnaissance missions in European seas. Basic data facts on the AUVs delivered by ECA Group are given, along with some general directions for further research in the field with the aim of achieving more efficient and environmental-friendly underwater missions in the future.

Full text

Key Features of the Autonomous Underwater Vehicles
for Marine Surveillance Missions
Sanja Bauk1,2, Nexhat Kapidani2 , Jean-Philippe Boisgard 3 Žarko Lukšić2
1Durban University of Technology, Maritime Studies, Durban, South Africa
bsanjaster@google.com
2Administration for Maritime Safety and Port Management of Montenegro,
Montenegro
nexhat.kapidani@pomorstvo.me
zarko.luksic@pomorstvo.me
3ECA Robotics SAS, France
boisgard.jp@ecagroup.com
Abstract. This paper gives an overview of autonomous underwater vehicles’
(AUVs’) applications, shapes due to the specific kinetic and dynamic
requirements, state estimation, control, navigation and communication
principles. The emphasize is put on AUVs deployed within EU Horizon 2020
COMPASS2020 (Coordination Of Maritime assets for Persistent And
Systematic Surveillance 2020) project for marine surveillance and
reconnaissance missions in European seas. Basic data facts on the AUVs
delivered by ECA Group are given, along with some general directions for
further research in the filed with the aim of achieving more efficient and
environmental friendly underwater missions in the future.
Keywords: Autonomous Underwater Vehicles (AUVs), key features.
1 Introduction
Two main types of unmanned underwater vehicles are: (i) remotely operated
underwater vehicles (ROV) and (ii) autonomous underwater vehicles (AUV). The
ROVs are controlled from the surface by a wired connection. These can do many
different tasks, but the wired connection restricts their maneuverability and
capacities to reach remote areas. The AUVs navigate autonomously due to the
dedicated navigation algorithms and collect surrounding information. Once
launched, they collect data and come back to the surface after completion of their
specific task. Since AUVs are not connected via wire to the ship or ground they
have high maneuverability, powered by battery or fuel cell, they can reach remote
locations, follow narrow composite pathways, avoiding at the same time human
fatigue and reducing operation expenditures.

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In this paper, emphasize will be put on AUVs. These are very versatile
autonomous systems and can be used for numerous purposes as: (i) military
(surveillance, anti-submarine warfare, mine countermeasures, site inspection,
inspection of wreckage, payload delivery to ocean floor, search and rescue, aircraft
crash investigation, i.e. black-box search and retrieval during the investigation,
ocean exploration and bathymetric study, mapping of ocean floor, locating and
retrieval of dumped illegal loads, etc.); (ii) scientific (marine biology studies, close-
up observations of aquatic life without disturbance, geological survey,
archeological survey, underwater environmental monitoring in rivers and lakes,
track oil-spill and gas leakage, etc.); (iii) industry (repair and maintenance, track
and repair underwater cables and pipelines, underwater structure inspection,
etc.); and (iv) other (underwater video footage collection, fishing, entertainment,
sports, tourism, etc.) [1].
Within the COMPASS2020 project UAVs are used for environmental
recognition, sensing, mapping and localization [2]. More precisely, in the combat
with narcotic smugglers, illicit narcotic bundles (of cannabis, for instance) might be
dumped from the smugglers’ speed vessels and police and/or military forces have
to locate them and retrieve afterwards. Namely, once located, the positions of the
crates and/or bags with narcotics are communicated to the authorities for their
efficient retrieval. It is to be mentioned that COMPASS2020 can be treated as a
kind of follow up of the SWARM (Smart and Networking UnderWAter Robots in
Cooperation Meshes) project, which main objective was to develop an integrated
platform for autonomous maritime and underwater operations including AUV,
aerial autonomous vehicles (AAVs), ROVs and unmanned surface vehicles (USV)
performing dangerous missions [3;4] in multimodal modes. Similar is with
COMPASS2020 project, which has to integrate several AAVs as Zephyr, AR5 Life
Ray Evolution, AR3 Net Ray, operating at different altitudes and providing in such
manner broader coverage at different resolution levels [5]; sea surface speed
patrol vessel; and, AUVs.
The rest of the paper is organized as follows: Section 2 contains key features
of AUVs including their technical detail, shape, navigation and communication
principles; Section 3 provides short description of AUVs deployed within
COMPASS2020 project; while Section 4 gives some conclusion remarks and direc-
tions for further research work in this domain.
2 Key features of AUVs
The idea of designing and developing AUVs is not a new one. The first AUV, or the
self propelled underwater research vehicle was developed by Murphy and Fran-
cois in 1957 in the Applied Physics Laboratory at the University of Washington
(USA). This craft operated at 2-2.5 m/s up to a depth of 3600 m. In the 1970s few

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AUVs were developed in MIT and also in the Soviet Union [1]. These early under-
water robots were heavy, expensive and inefficient. Today’s AUVs can have six de-
grees of freedom, travel faster than 20 m/s, accurately detect obstacles and map
ocean floor at depths of up to 6000 m. They are more sophisticate, less expensive
and consequently accessible for wider exploitation like fishing, sports, tourism, en-
tertainment, etc. However, AUVs have yet to go a long way in terms of becoming
fully autonomous, capable to explore deep and hazardous underwater habitats. In
Table 1 are given some basic data on actual AUVs producers, AUVs’ applications
and key technical features.
Table 1. Actual AUVs types, producers, applications and basic features [1;5;6].
Heading level
Applications
Dimensions
Depth
AE1000, Japan
Inspection of underwater telecommunicati on
cables 2.3 m x 2.8 m x 0.7 m 1000 m
Maya AUV, NIO,
Goa, India Oceanography study 1.742 m, dia. 0.234 m 200 m
Theseus AUV,
Canada Under-ice bathymetric survays 10.7 m, dia. 0.127 m 2000 m
Autosub 6000,
AUVAC, USA Scientific survey and mapping 5.50 m x 0.90 m x 0.90 m 6000 m
HUGIN, Kongsberg
Seabed mapping, pipeline inspection, mine
reconnaissance 5.2-6.4 m, dia. 0.75 m
3000-
4500 m
REMUS-6000,
Kongsberg
Maritime
Oceanography study, monitoring, surveillance,
reconnaissance, etc. 3.96 m, dia. 0.71 m 6000 m
AUV-150, CMERI,
India
Oceanography study, mapping, surveillance,
reconnaissance, etc. 4.85 m, dia. 0.5 m 150 m
D. Allan B, MBARI,
USA Seafloor mapping 5.18 m, dia. 0.54 m 6000 m
SOTAB, Osaka
University, Japan Track of leakage from oil mines 3.0 m, dia. 0.27 m 200 m
AE 2000A, Japan
Under-ice survey
3.0 m x 0.7 m x 0.7 m
2000 m
Tri-TON 2,
University of
Tokyo, Japan
Estimate ore resources in underwater
hydrothermal deposits 1.4 m x 0.7 m x 1.4 m 2000 m
SeaCat, Germany
Autonomous inspection of underwater
structures 2.5 m x 0.58 m x 0.67 m 600 m

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Bluefin21, 2016,
General Dynamics,
USA
Search and explore, oceanography, mine
countermeasures 5 m, dia. 0.53 m 4500 m
A27, ECA Group,
France
enduring vehicle capable of carrying a large
payload in atmospheric housing 4.7 m x 0.730 m 300 m
A9, ECA Group,
France
High resolution data acquisition, 3D data
acquisition, shallow waters, harbor and coastal
survey
2m, dia. 0.23 m 300 m
Inspired mainly from submarines, AUVs are generally torpedo shape. These are
highly maneuverable and can exactly travel in complex pathways and access re-
mote areas, without engendering human life. Some AUVs are of hydrofoil shape,
while some other mimicked aquatic animals as snakes, turtles, beetles and crabs.
So called, fish robots are mostly popular among the bio-mimetic AUVs. As an ex-
ample SoFi (Soft Robotic Fish) can be given (Fig. 1a/b). It is designed and developed
by the team from MIT’s Computer Science and Artificial Intelligence Laboratory.
SoFi is made of silicone rubber and enables closer study of aquatic life. In fact, it
gets closer to marine life than humans can get on their own [7;8].
a. SoFi in searching elusive marine environment b. SoFi’s key modules
Fig. 1. SoFi UAV (Source: Web)
The AUVs are often equipped with different acoustic sensors like side scan
sensors, forward looking sensor, or multi-beam echo sounder, etc. They are usually
of modular structure, containing propulsion, sensing, controlling, navigation,
communication and other modules. These modules can be easily and quickly
replaced in the case of malfunction and/or for the purpose of different missions.
The AUVs usually produce low level of noise (or no noise at all in some cases) and
consequently don’t disturb aquatic ecosystem.

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2.1 Navigation principles
The AUVs navigate underwater autonomously based on predefine plan. Localiza-
tion is of key importance in navigation, since it enables AUV to follow the prede-
fined path precisely and reach the final destination. As Global Positioning System
(GPS) does not function underwater and high frequency radio signals propagation
in the underwater environment is suppressed, localization and navigation are very
challenging for AUVs. When using GPS, AUV has to resurface in intervals. In gen-
eral, methods of AUVs navigation can be broadly divided into inertial, acoustic and
geophysical.
Inertial navigation. An embedded inertial navigation system (INS) is a navigation
device, based on submarine of worldwar, that uses a computer, motion sensors
(accelerometers) and rotation sensors (gyroscopes) to continuously estimate by
dead reckoning the position, the orientation, and the velocity (direction and speed
of movement) of a moving object (here AUV) without the need for external refer-
ences [9]. INS is usually used for small, inexpensive UAV, since over the time it can
accumulate errors generated by accelerometer and gyroscope [1]. An regular
recognition is needed to compensate the drifting.
Acoustic navigation. When it comes to acoustic navigation, the range is estimated
from the time of travel of the acoustic signal from AUV to the external transducers
(devices, which generate and receive sound waves) and backward. The AUV posi-
tion is know in real time thanks to calculating on the principle of triangulation.
Three different types of acoustic navigation are briefly described below:
(a) In the case of Ultra-Short Baseline (USBL) the AUV is positioned relative to a
surface vehicle fitted with an array of acoustic transducers (Fig. 2.b). Relative dis-
tance is calculated from the time of travel of the acoustic signal and direction from
the phase difference of the signal received by different transducers. Here the
transducers are placed close to one-another and major disadvantage is precise
range detection.
(b) In the case of Short Baseline (SBL) the transducers are placed in front and back
of the surface vessel (Fig. 2.b). Therefore the baseline is limited to the length of
the vessel, which limits the positional accuracy of the AUV.
(c) In the case of Long Baseline (LBL) the transducers are widely placed over the
mission area on the seabed (Fig. 2.c). Localization is done by triangulating the
range estimated by acoustic transducers. The major limitation is the huge cost and
time involved in placing the transducers on the seabed [1].

6
Fig. 2. Principles of acoustic navigation (Source: [1])
Geophysical navigation. When it comes to geophysical navigation, external envi-
ronmental features are used as landmarks for positioning. Optical and sonar are
two main modes of geophysical navigation. Simultaneous localization and map-
ping is predominantly used for it [1]. In the case of optical navigation, monocular
or stereo cameras can be used to take images of the underwater environment and
features extracted from the images can be used for simultaneous localization and
mapping (SLAM). In such setting different visual odometry1 techniques are used.
On another side, high-power SOund NAvigation and Ranging (SONAR) is a device
for detecting and locating objects especially underwater by means of sound waves
sent out to be reflected by the objects2. Sonar is a commonly used technique for
communication, detection of objects, and navigation by using sound propagation.
A comprehensible description of Sonar can be found in [10] and it states: “When
AUV3 is used to map the topography of the ocean’s floor, it sends out sound pulses,
often referred to as pings, towards the bottom of the ocean within its vicinity. As
these sound pulses travel downwards they will encounter physical features such
as hills, valleys, rock, etc. These sound pulses are subsequently reflected back up
towards the AUV, having been modified by the objects along their path. These re-
flected pulses are often called echoes. Receivers on the AUV that detect these ech-
oes can than reconstruct the topology of the region from which the echoes
bounced off”. Sonar is very like the echosounder. The difference is that the sound
beam can be steered in the desired directions and present images of the bottom
topography on suitable display. Synthetic Aperture Sonar (SAS) is a relatively new
principle in hydroacoustics. Together with advanced image processing the method
can produce very detailed images of sea bed and objects. It operates in such way
1 Odometry is the use of data from motion sensors to estimate change in position of an
object (here AUV) over time. It is used in robotics by some robots (for AUV, too) to estimate
their position relative to a starting location. The word odometry is composed from the
Greek words odos (meaning "route") and metron (meaning "measure").
2 Marriam Webster Dictionary. Retrieved from:
https://www.merriam-webster.com/dictionary/sonar (last access: 10th
April 2020).
3 Originally submarine.

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that one moves sonar along a line and therefore illustrates stationary objects from
several directions. The transmitting antenna’s synthetic aperture in relation to the
object will then be the length the sonar has moved (Fig. 3). These systems that are
now in use can give resolution of 2x1 cm, which is typically 10 times better than
what ordinary sonars can give. Kongsber produces an SAS (HISAS-1030), which is
used at AUV Hugin (Fig. 4). It works at 70-100 kHz and can be delivered with Focus
software [11].
Fig. 3. Principle of Synthetic Aperture
Sonar
(Source: [11, p.4-40])
Fig. 4. AUV Hugin; Image from 1000 m
depth; The tops that are shown on the map
are 30-40 m high
(Source: [11, p.4-40])
Some AUVs should have ability to carry out long-distance missions fully autono-
mously and without supervision from surface ship. Combined with inertial naviga-
tion, the use of one or several transponders on the seabed is an accurate and cost-
effective approach towards achieving this [12;13]. An extensive description of ac-
tual advanced AUVs’ propulsion solutions, control systems and their key compo-
nents, state estimation methods, path planning models and techniques along with
object detection and obstacle avoidance can be found in [1;14].
2.2 Communication principles
Underwater wireless communications are implemented using communication
systems based on acoustic, radio frequency, and optical (light and laser) waves.
Underwater acoustic wireless communications have been one of the most used
technologies since they can provide connection over rather long distances (Fig. 5).
However, acoustic waves have many drawbacks as scattering, high delay due to

8
the low propagation speeds, high attenuation and low bandwidth. Additionally,
acoustic signals generated by communication systems and sonar devices have
harmful impact on the underwater mammals and fishes. Therefore, research has
been carried out in the past to use low frequency radio waves (30-300 Hz). These
waves have numerous disadvantages like high attenuation, low data rate, adverse
effect of shallow areas, long antennas, etc. For worldwide communications with
submarines, e.g., for depths up to a few 10 m very low frequency (VLF) transmitters
from 10-30 kHz are used. In oppose to acoustic and radio waves, optical waves can
provide high-speed underwater optical communications at low latencies, thanks
to high propagation speed and high data rate in return for a limited
communication range (tens of meters). In Table 2 are given key features of
underwater acoustic, radio and optical wireless communications.
Table 2. Underwater acoustic, radio and optical communications features [15, p.3].
Feature
Acoustic
Radio
Optical
Range
< 20 km
< 100 m
100-200 m
Attenuation factors Conductivity
Conductivity and
frequency
Distance vs. inherent
optical properties
Speed
1500 m/s
2.25x108 m/s
2.25x108 m/s
Power
 10 W
 100 W
 1 W
Cost
High
High
Low
Data rate
< 10 Kbps
< 0.1 Gbps
< 10 Gbps
Antenna size
0.1 m
0.5 m
0.1 m
Latency
High
Moderate
Low

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Fig. 5. Average achievable transmission distance by various commercial acoustic modems
(Source: [15, p.2])
All three considered underwater wireless communication modes have certain ad-
vantages and disadvantages dependant of various underwater conditions. The
subject remains open and further research is necessary for conceiving and imple-
menting more practicable and accurate communication, networking and localiza-
tion schemes [15].
3 The AUVs deployed in COMPASS2020 project
One of the COMPASS2020 project main goals is to develop an integral platform for
efficient simultaneous deployment of unmanned aerial vehicles (Zephyr, AR5 Life
Ray Evolution, AR3 Net Ray), offshore patrol vessel (OPV), and underwater auton-
omous vehicles (A27 and A9) for preventing and combating trafficking of narcotics
over European borders. To illustrate the impact of narcotics in Europe, it is esti-
mated that every year approximately 125 tonnes of cocaine are consumed. The
majority of it comes from Latin America to Europe on transatlantic routes. How-
ever, in recent years transhipments from large vessels to various forms of
transport (including leisure sailing vessels, fishing vessels, merchant vessels and
fast speedboats) have started occurring in sea waters along Northern and Eastern
African coast. These new forms of transport target mainly Spain and Portugal as
points of entry, while the most traditional forms target Belgium and the Nether-
lands (major European shipping ports) [16]. When it comes to interception of nar-
cotics smugglers – the OPV, the Zephyr and the AUV are in action in the border
area. The Naval Group Mission System (MS) is running onboard the OPV and it is
always connected with its replica at Marine Operations Center (MOC) ashore.
Zephyr is launched from MOC and it has to collect an overall picture of the area

10
that is being surveyed. In addition, the AUVs should be previously deployed from
the OPV into a strategic location that is coincident to the traffickers’ typical routes.
The AUVs are programmed to follow specific trajectories in the area of interest,
navigating underwater at low depth in order to remain undetected from the smug-
glers and at the same time staying closely enough to the surface in order to opti-
mize the possibility of detecting the target. The low noise AUVs carry of a streamer
of hydrophones4 wide bandwidth that enable detecting speed boats. After detec-
tion of the target, the AUVs can communicate to the Zephyr, thanks to the OPV
which is used as a communication relay in the system. The Zephyr sends automat-
ically an alert to MS onboard OPV and its replica in the MOC. Once the MOC re-
ceives the alert, the officers proceed with the deployment of an AR-5 platform [5].
The AR-5 has to come close to the vessel and acquire more detailed information
about it. In accordance to this information, the officer onboard OPV can decide
how to intercept the threat and act efficiently. If the smugglers try to get rid of the
cargo, UAV and AUVs have the capacity of searching for it by making use of sonars5
[2]. In the following two subsections, short descriptions and some basic data on
the AUVs employed within COMPASS2020 will be given.
4 A hydrophone is a microphone designed to be used underwater for listening to
underwater sound. Most hydrophones are based on a piezoelectric transducer that
generates an electric potential when subjected to a pressure change, such as a sound wave
(in this case caused by narcotic smugglers’ vessel / the author’s comment)[Source:
Wikipedia].
5 Side-scan sonar is a category of sonar system that is used to efficiently create an image of
large areas of the sea floor. Side-scan sonar imagery is also a commonly used tool to detect
debris items and other obstructions on the seafloor that may be hazardous to shipping or
to seafloor installations by the oil and gas industry. In addition, the status of pipelines and
cables on the seafloor can be investigated using side-scan sonar (in this case its used for
detecting abandoned bundles with narcotics / the author’s comment) [Source: Wikipedia].

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3.1 The A27 AUV
The A27 is a development of ASEMAR of ECA Group Autonomous Underwater Ve-
hicle family (Fig. 6). Big Size AUV with long endurance and high payload capability
can be used for both the defense and to commercial purposes. It performs auton-
omous missions up to 300 m depth, and is easily transportable by plane for over-
seas missions. Due to its large endurance, very high area coverage rate
(2km2/hour) and payload capacity, it is able to host high performance payloads
according to the mission’s requirements: Synthetic Aperture Sonar (SAS), video,
forward looking sonar (FLS), multi-beam echo sounder, and others [17]. For navi-
gation it uses Inertial Navigation System (INS), Doppler Velocity Log (DVL), military
global navigation satellite system (GNSS) and Global Positioning System (GPS) pe-
riodically, after resurfacing. It can communicate via WiFi, Ethernet, Iridium and/or
acoustic wireless communication channel. Its average speed is 3-5 knots (and max
6 knots). Key payloads are Sonar and Conductivity, Temperature and Depth (CTD)
sonde. It withstands harsh environmental conditions and offers a greater stability
when encountering heavy turbulence from waves. The high degree of stability en-
ables this AUV to capture high-resolution images. The information obtained by the
platform is post-processed in the command centre [18].
Fig. 6. The A27 AUV
(Source: COMPASS2020 documtation)

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3.2 The A9-E AUV
The A9-E AUV is the configuration of ECA Group for environmental monitoring (Fig.
7). In addition to the seabed image acquisition, it can record bathymetric data as
well as environmental information such as water turbidity, conductivity, tempera-
ture, fluorescence, dissolved oxygen and/or pH. Mission planning and monitoring
are done through user friendly software which allows operator to follow the vehi-
cle at any time during its mission. This underwater drone has been designed to
meet STANAG 1364 requirement, i.e. its acoustic and magnetic signatures are min-
imized in order not to trigger any underwater mines when doing the mine warfare
survey. As part of early trials for the SWARM project, ECA Group’s A9 AUV fitted
with the interferometer side-looking sonar demonstrated ability to conduct sur-
veys in a shallow water environment of 50m depth. It uses a phase differencing
bathymetric sonar that increases area coverage by close to 200% over conven-
tional multi-beam echo sounders in shallow water [19]. For navigation it uses INS,
DVL, GPS and for communication purposes radio (UHF), WiFi, Ethernet and the
acoustic wireless communications. Its payload consists of, but it is not limited to:
Interferometer Side Scan (ISS) sonar, video, CTD, environmental sensors (turbidity,
pH, fluorescent Dissolved Organic Matter (fDOM) / waste water discharge), etc
[20].
Fig. 7. The A9-E AUV
(Source: ECA Group Web site)
4 Conclusion
The paper gives an overview of some key determinants of AUV. These systems
have a variety of military, scientific, industrial and other applications. They can be
very complex and expensive, but there are some that are available for educational
and recreational purposes. It is a common opinion in the literature that these sys-
tems have been developed to a very high standard, but that there is plenty of room
for further research and improvement when it comes to: better adaptive control

13
techniques using neuro-fuzzy techniques, more accurate localizing using improved
INS non-linear Kalman filters, cooperative localization (swarm intelligence), artifi-
cial intelligence vision and object detection, odometry, underwater wireless com-
munications, high-density battery power supply, energy harvesting methods, etc.
By improving all these dimensions, AUVs will become fully autonomous long-range
underwater robots, capable to explore the deepest, inapproachable and harsh cor-
ners of the seabed. In the case of considered COMPASS 2020 underwater autono-
mous vehicles have to be integrated into the complex system composed of auton-
omous aerial vehicles (Zephyr, AR5 and AR3), sea surface vehicle (OPV), including
Naval Group mission system (MS) ondoard OPV and shore based marine opera-
tions center (MOC). At the moment, the experts’ team within the project is design-
ing algorithms for seamless data acquisition, analysis, storage and presentation.
This research work is based on the experts’ knowledge, skills and experiences ac-
quired through several realistic case studies and recent test-beds in European seas.
Following research work should target harmonizing actions of all involved man and
unmanned vehicles and optimizing relevant data/information flow schemes. In
parallel, improving bidirectional communication links between all involved parties
in the case of emergency are to be further explored.
Acknowledgement
This work has been partially funded by the EU Research and Innovation program
HORIZON 2020, COMPASS2020 project - Grant Agreement No: 833650.
References
1. Avilash Sahoo, Santosha K. Dwivedy, P.S. Robi, Advancement in the field of autonomous
underwater vehicle, Ocean Engineering 181 (2019) 145-160.
2. Sanja Bauk, Nexhat Kapidani, Žarko Lukšić, Filipe Rodrigues, Luís Sousa, Autonomous
marine vehicles in sea surveillance as one of the COMPASS2020 project concerns,
Journal of Physics: Conference Series, Volume 1357, 2020,
https://iopscience.iop.org/article/10.1088/1742-6596/1357/1/012045.
3. Isabell Leblond, Sebastian Tauvry, Marc Pino, Sonar image registration for swarm AUVs
navigation: Results from SWARM project, Journal of Computational Science 36 (2019)
101021.
4. Enrica Zereik et al., Challenges and future trends in marine robotics, Annual Review in
Control 46 (2018) 350-368.
5. Sanja Bauk, Nexhat Kapidani, Žarko Lukšić, Filipe Rodrigues, Luís Sousa, Review of
Unmanned Aerial Systems for the Use as Maritime Surveillance Assets, Proc. of the 24th
International Conference on Information Technology (IT), Zabljak, Montenegro, 18-22
February 2020 (to appear).
6. Kongsberg, HUGIN Autonomous Underwater Vehicle (AUV). Retrieved from:
https://www.kongsberg.com/globalassets/maritime/km-
products/product-documents/hugin-product-specification (last

14
access: 11th April 2020)
7. MIT News, Soft robotic fish swims alongside real ones in coral reefs, published by Adam
Conner-Simons (CSAIL) on March 21, 2018. Retrieved from:
http://news.mit.edu/2018/soft-robotic-fish-swims-
alongside-real-ones-coral-reefs-0321 (last access: 10th April 2020).
8. Ursula K. Verfuss et al., A review of unmanned vehicles for the detection and monitoring
of marine fauna, Maritime Pollution Bulletin 140 (2019) 17-29.
9. Seminar on inertial navigation systems Tampere University of Technology, Basic
Principles of Inertial Navigation. Retrieved from:
http://www.aerostudents.com/courses/avionics/InertialNavig
ationSystems.pdf (last access: 10th April 2020).
10. Study.com, What is Sonar? - Definition, Uses & Examples. Retrieved from:
https://study.com/academy/lesson/what-is-sonar-definition-uses-examples.html (last
access: 10th April 2020).
11. Norvald Kjerstad, Electronic and Acoustic Navigation Systems for Maritime Studies, 1st
Edition, NTNU Norwegian University of Science and Technology, Alesund, Norway,
2016.
12. Kongsberg, Autonomous Underwater Vehicle – AUV – The HUGIN Family. Retrieved
from: https://www.kongsberg.com/globalassets/maritime/km-
products/product-documents/hugin-family-of-auvs (last access: 11th
April 2020).
13. Øyvind Hegrenæs, Kenneth Gade, Ove Kent Hagen and Per Espen Hagen, Underwater
Transponder Positioning and Navigation of Autonomous Underwater Vehicles, Proc. of
the MTS/IEEE oceans conference and exhibition, BILOXI, 2009. Retrieved from:
https://www.navlab.net/Publications/Underwater_Transponder
_Positioning_and_Navigation_of_Autonomous_Underwater_Vehic
les.pdf (last access: 11th April 2020).
14. Caoyang Yu et al., Onboard system of hybrid underwater robotic vehicles: Integrated
software architecture and control algorithm, Ocean Engineering 187 (2019) 106121.
15. Nasir Saed et al., Underwater optical wireless communications, networking, and
localizing: A survey, Ad Hoc Networks 94 (2019) 101935.
16. COMPASS2020 – Coordination of Maritime assets for Persistent And Systematic
Surveillance, Project internal documentation (Boosting the effectiveness of the Security
Union, H2020-SU-SEC-2018-2019-2020), pp. 1-70.
17. Naval Technology, A18-M Autonomous Underwater Vehicle. Retrieved from:
https://www.naval-technology.com/projects/a18-m-
autonomous-underwater-vehicle/ (last access: 9th April 2020).
18. ECA Group, A18-M/AUV/Autonomous Underwater Vehicle, Data Sheet. Retrieved from:
https://www.ecagroup.com/en/solutions/a18-m-auv-
autonomous-underwater-vehicle (last access: 12th April 2020).
19. ECA Group, A9-E/AUV/Autonomous Underwater Vehicle, Data Sheet. Retrieved from:
https://www.ecagroup.com/en/solutions/a9-e-auv-autonomous-
underwater-vehicle (last access: 12th April 2020).
20. Shephard news, Unmanned vehicles - A9-E AUV demos side-looking sonar, November
2016. Retrieved from: https://www.shephardmedia.com/news/uv-
online/a9-auv-demos-side-looking-sonar/ (last access: 9th April 2020).