Autonomous underwater vehicles for scientific and naval operations

Autonomous underwater vehicles for scientific and naval operations

AUTONOMOUS UNDERWATER VEHICLES FOR SCIENTIFIC AND NAVAL OPERATIONS E. Bovio *,1 F. Baralli * and D. Cecchi ** * NATO Undersea Research Centre, Viale ...

1MB Sizes 0 Downloads 45 Views

AUTONOMOUS UNDERWATER VEHICLES FOR SCIENTIFIC AND NAVAL OPERATIONS E. Bovio *,1 F. Baralli * and D. Cecchi **

* NATO Undersea Research Centre, Viale San Bartolomeo

400, 19138 La Spezia (SP), ITALY ISME, Interuniversity Centre of Integrated System for Marine Environment c/o DSEA University of Pisa, Via Diotisalvi 2, 56126, Pisa, Italy

**

Abstract: Recognizing the potential of autonomous underwater vehicles for scientific and military applications, in 1997 MIT and the NATO Undersea Research Centre initiated a Joint Research Project (GOATS), for the development of environmentally adaptive robotic technology applicable to Mine Counter Measures (MCM) and Rapid Environmental Assessment in coastal environments. The August 2001 GOATS Conference marked the end of this 5 years project, but did not mark the end of the work. The Centre initiated in 2002 a new long term programme to explore and demonstrate the operational benefits and limitations of AUV for covert preparation of the battlespace. Recently the work addressed the evaluation of COTS (Commercial Off- The- Shelf) AUV technology for MCM operations in response to terrorist mining of port. The paper summarizes the work performed and refers to the scientific publications derived from the AUV programme at the NATO Undersea Research Centre. Copyright © IFAC 2004 Keywords: Autonomous vehicles, Marine systems, Guidance, Navigation, Control, Accuracy

1. INTRODUCTION

The NATO Undersea Research Centre 2, located in La Spezia, Italy, performs basic and applied research and development to fulfill NATO's operational requirements in undersea warfare. The results of the Centre's research that can be seen at sea in many ships and submarines of the Alliance, have contributed to NATO's military capabilities over the past 41 years. Unique in its international makeup, the Centre functions as the "hub" in a virtual laboratory which brings great synergy [email protected] Following the change in NATO command structure, the SACLANT Undersea Research Centre has been recently renamed NATO Undersea Research Centre 1

2

CAMS 2004

to the research process and shortens timelines between research and development (R&D) and military applications. The Centre's own resources are therefore multiplied by collaboration and Joint Research Projects (JRP). In response to NATO advanced planning that anticipates significant use of Autonomous Underwater Vehicles (AUVs) for Mine Counter Measures (MCM) and Rapid Environmental Assessment (REA), the Centre and the Massachusetts Institute of Technology (MIT) initiated in 1997 a 5 years joint research project, designated GOATS (Generic Oceanographic Array Technology Systerns), for the development of environmentally adaptive AUV technology applicable to MCM and REA in coastal environments. The GOATS

1

JRP grew in membership and scope and it was joined by an international host of collaborators who shared the notion that AUVs were ready to graduate from their role as research objects to a new supporting role for advanced ocean monitoring and maritime military tactics. Between 1997 and 2001 the GOATS JRP explored and expanded the state of the art for networks of robotic ocean observers, supporting new approaches to battlespace preparation and mine hunting. The programme included a sequence of three field experiments with the participation of 14 institutions. The August 2001 GOATS Conference (Bovio et al. 2001) marked the end of this JRP, but not the end of the work. Building on the success of the GOATS JRP, the Centre initiated in 2002 a new long term programme called Battlespace Preparation (BP) with A UVs to explore and demonstrate the operational benefits and limitations of AUVs for military battlespace preparation. Similarly to the GOATS series of experiments, the programme organizes multi- national, multi- disciplinary sea trials addressing the utilization of AUVs in coastal waters. The first experiment of the BP series took place in May-June 2002 in the Tyrrhenian and Ligurian seas. The results of this experiment have been reported during the Maritime Recognized Environmental Picture (MREP) Conference (Bovio et al. 2003) held in La Spezia in May 2003. This paper summarizes the work performed and refers to the scientific publications derived from the AUV programme.

2. THE GOATS JRP The GOATS JRP combined theory and modelling of the 3- D environmental acoustics with three experiments (1998, 1999, 2000) involving AUV and sensor technology. The objective of the 1998 sea trial was to use acoustic arrays deployed on the sea floor or mounted on an AUV to characterize the spatial and temporal characteristics of the 3-D scattering from seabed targets and the associated reverberation, including the effects of multipaths. This effort was aimed at establishing the environmental acoustics foundation for future sonar concepts exploring 3- D acoustic signatures for combined detection and classification of proud and buried targets in very shallow water. The GOATS 98 experiment provided a unique data set of three dimensional scattering and reverberation in shallow water, which has been essential for model validation and identification of features of the 3-D acoustic field. In addition, the experiment showed that small and inexpensive AUVs such as the MIT Odyssey can be reliably deployed, operated and recovered in shallow water

2

from a surface vessel. It was also demonstrated that AUVs are an excellent acoustic platform for new sonar concepts for littoral MCM (Schmidt et al. 1998, Schmidt and Bovio 2000, Moran 1999). The comprehensive acoustic and environmental datasets acquired during the GOATS 98 experiment have generated several scientific publications . The first papers resulting from the experiment described the physics underlying seabed penetration at sub-critical angles (Maguer et al. 2000b, Maguer et al. 2000a). Several papers deal with the processing of the bistatic synthetic aperture data acquired by the AUV, demonstrating the concept of bistatic SAS autofocusing and imaging (LePage and Schmidt 2002a, Edwards et al. 2001, Schmidt et al. 2000). The JRP has lead to several new developments in regard to modelling of acoustic interaction with the seabed. Specifically a unique modelling capability has been developed, providing a consistent prediction of 3-D scattering from sea bed roughness and volume inhomogeneities, validated by the GOATS datasets (Veljkovic and Schmidt 2000, LePage and Schmidt 2000c, LePage and Schmidt 2002b, LePage and Schmidt 2000a, LePage and Schmidt 2000b). Following the success of the GOATS 98 experiment, the Centre organized a workshop in January 1999 to extend the scope of the JRP to REA applications. In addition, it was also decided to assess the performance of non traditional AUV navigation algorithms based on a priori knowledge of the bottom topography. This required a thorough survey of Procchio bay, Island of Elba, the site of the GOATS 2000 experiment. Traditional instruments (side scan sonar, sub bottom profiler, multibeam echo sounder, underwater video camera, expandable penetrometer) were deployed from Manning and seafloor samples collected during the GOATS 99 experiment. The data provided a rich data set that characterizes the bathymetry and the composition of the seafloor of the area and forms the ground truth reference for comparison with data collected subsequently by AUVs . The GOATS 2000 experiment demonstrated the capabilities of AUVs as REA platforms in shallow and very shallow water. The Ocean Explorer (OEX) equipped with a colour video camera and the Edgetech dual frequency DF- lOOO side scan sonar and the Taipan equipped with the Applied Microsystem CTD were launched from R/V Alliance, to transect the bays to the east of Procchio to acquire side scan sonar data and to measure water mass properties such as current, salinity, density and temperature, for use by the nested oceanographic models. The side scan sonar data were used to generate geo-referenced acoustic images for comparison with ground truth data collected in the same area during previous experiments. The environmental information measured by the AUVs was fused in the Centre GIS

CAMS 2004

3. BATTLESPACE PREPARATION WITH AUVS Building on the success of the GOATS JRP, the Centre initiated in 2002 a new long term programme called Battlespace Preparation (BP) with A UVs to explore and demonstrate the operational benefits and limitations of AUVs for battlespace preparation. Similarly to the GOATS series of experiments, the programme organizes multi- national, multi-disciplinary sea trials addressing the utilization of AUVs in coastal waters for military applications. Each year the experiments are prepared at a planning meeting in January and take place in the Mediterranean sea in May- June. Initial results are discussed in the fall and every second year the Centre organizes a scientific conference to report the findings. The first experiment of the BP series took place in May-June 02 in the Tyrrhenian and Ligurian seas with three broad objectives: Oceanography, REA, MCM. The results have been reported at the MREP conference (Bovio et al. 2003). Figure 1. Boundary between sand and Poseidonia oceanica (aerial image and unsupervised seafioor segmentation).

3.1 Oceanography

database. The tiled side scan sonar images were processed with unsupervised segmentation algorithms that demonstrated the capability to distinguish in a quantitative way between different types of seabeds. Figure 1 shows the Poseidonia oceanica to sand boundary detected by side scan sonar survey plotted over an aerial picture of the same area (Spina et al. 2001). The video images collected by the OEX were organized in a geographical database using the See Track software. A field of proud and buried targets at the main test site in Biodola Bay was insonified by the TOPAS 3 parametric sound source at a variety of incident and aspect angles. The Odyssey AUV sampled 3- D reverberation and target echoes obtaining data for validation of numerical models of mono- and bi- static seabed reverberation . A second field of proud targets including exercise mines such as the MP80, Manta and Rockan, was imaged at different aspects by the OEX instrumented with the 390 kHz Edgetech side scan sonar and video camera. The experiment demonstrated the potential of high frequency side scan sonar at mUltiple aspects for classification of proud targets. The results of the GOATS 2000 experiment are reported in (Bovio et al. 2001).

Ocean forecasting is essential for effective and efficient use of AUVs in the littoral environment. The first part of the BP02 sea trial was dedicated to carry out and quantitatively evaluate a multiscale real time forecasting experiment in support of long range AUV missions. A two- way nested HOPS 4 model was run at Harvard University to predict oceanographic parameters in local (such as around Elba) and far field (eastern Ligurian sea) regions. Adaptive sampling patterns have been determined on short notice based on forecast results for both R/V Alliance and Remus. The AUV run missions up to 8 hrs at a speed of 3- 4 kt . As shown in Figure 2, acoustic communication was maintained at rendez- vous points by the WHOI 5 Utility Modem deployed from Alliance. The acoustic link allowed real- time data retrieval at a reduced rate and on- line programming of the vehicle mission . Remus executed CTD sampling in yo-yo mode and ADCP sampling in a depth range of 0100 m. Vehicle navigation was accomplished by dead reckoning, with GPS updates when surfaced. Heading information was obtained with a magnetic compass. Velocity information was obtained from the ADCP when in bottom lock range. When the vehicle was not in range of the bottom, velocity was based on an estimated speed derived from its propeller's rotation rate. The characteristics of the Remus used in BP02 are shown in Figure 3. Oceanographic data acquired by Remus were 4

3

TOpographic PArametric Sonar

CAMS 2004

5

Harvard Ocean Prediction System Woods Hole Oceanographic Institution

3

Veblcle REMUS III ADM#I Daner

Sensors Ocean Sensor.; CID 2000 Wet Labs LSS 1.2 M Hz ADCP - up/down 900 kHz Sidescan sonar Acoustic Communication

Diametu/Ltnetb (cm) Vehicle - 19/158 Shipping Ca.<;c: 38 x 38 x 178 Auxiliary Case: 38)( 38 )( 178

Wel!!bttk21 36 67,6 62.6

Vehicle - 19/158 Shipping Case: 38 x 38 xl78 Auxiliary Case: 38 x 38 x 178

36

GrS Ocean Sensors ern 2000 Wet Labs LSS 1.2 Mliz AOCP- up/down 600 kHz Sidc5c3n S(1I1ar Ocean Sensor.; Cl' 2000 Wet Labs LSS 1.2 MHz ADCP - up/down 900 kHz S idescan sonar DIDSON Sonar Acoustic Communication Two radio buoys

REMlJS #2 EDM 5 Gmdgen REMllS #3 EDM6

PARADIGM Tracking System

WHOllJtility Acoustic Modem Acomms Radio Buoy Shipboard Acoustic Receive

ACOUS lic

Communication

Array Too.ls and Electronics Miscellaneous electronics and mcch'

Support Equipment

67.6

62.6

Vehicle - 19/158 Shipping Case: 38 x 38 )( 178 Auxiliary Case: 38 x 38 x 178

36

Shipping Ca.~e (2) 53.3 x 109 x 68.6 Shipping Case ( I ) 53.3 x 109 x 68.6 Shipping Case (t) 25x25x150 Shipping Case (2) 30x50x9() Shipping Case (2) 53.3 x 109 x 68.6

63.5 each

67,6 62.6

65

35 35 each 65 each

Figure 3. The Remus AUVs used in BP02. Remus#1 has been used for Oceanographic, REA, MCM, and communication studies. Remus#3 has been used for target ID , Remus#2 has been kept as hot spare. fused with with XBTs 6 and CTDs collected by R/V Alliance and available meteorological information. The fused data set was transmitted via Internet to the modelling team. The oceanographic team onboard Alliance coordinated the assimilation of oceanographic data collected by the various sources. The modelling code was run at Harvard. The model output was made available via Internet to R / V Alliance to perform adaptive sampling and optimize long range AUV missions . 20

40

Kilometers

Figure 2. Oceanographic experiment in deep water. The Remus track is shown in light grey and the black marks indicate the locations where control information, vehicle status and oceanographic data were exchanged acoustically between vehicle and R/V Alliance. Typical modem range were 800- 1500 m, depending on vehicle depth.

4

3.2 REA The REA experiment demonstrated the capabilities of AUVs as REA platforms in shallow water. The information collected included acoustic and video images, bathymetry and water

6

eXpandab le BathyTermography

CAMS 2004

mass properties such as current, salinity, density and temperature. The AUVs were launched from R/V Alliance, and surveyed the bays of Levanto, Bonassola and Framura, Italy, to acquire environmental information in preparation for the MCMFORMED's Percentage Clearance (PC) trial which took place in February 2003. The OEX operated the dual frequency (150/600 kHz) Marine Sonic and the video camera, the Remus operated the 900 kHz Marine Sonic and the DIDSON acoustic lens. All vehicles performed several missions a day, controlled from Alliance by acoustic and/or radio frequency communication. The sonar and video images were downloaded at the end of each mission and stored in the Centre GIS 7 database. Unsupervised segmentation software developed at the Centre divided the seafloor :nto areas of similar characteristic (Spina and Grasso 2003). Objects with dimensions similar to a mine were automatically extracted and marked on the GIS map. All data contributed to the prod uction of seabed classification maps according to ATP 24 standards that were provided to the NATO mine hunters participating to the February 03 PC trial with the objective to measure the value of a priori environmental information in planning and conducting a PC trial. The GESMA 8 ship R/V Thetis equipped with the interferometric Klein 5400 side scan sonar conducted an independent survey of the area. The ship acquired co- registered imagery and bathymetry that has been compared with that acquired by Manning equipped with DF-lOOO side scan and EM- 3000 multi beam sonar during previous experiments. Work is in progress to assess the bathymetric capability of the sonar as an alternative to a multibeam (Zerr et al. 2003).

side scan sonar. Sonar images were downloaded from the vehicle upon return and analysed by the WHOI team using the Marine Sonic software. Mine like objects were successively identified with the Remus vehicle equipped with the DID SON acoustic camera that provides high resolution video images and with the Centre vehicle Ocean Explorer equipped with sonar and video. The OEX that was deployed for the first time is shown in Figure 4. Theiis surveyed both areas with redundant tracks providing multiple aspect of targets. The ship did not cover the north west corner of the Framura area, which was too shallow for safe towing of the Klein. Sonar images were received and processed in real time. Targets were detected and classified using multiple views of the objects. Figure 5 shows the performance of the three systems. Numana detected classified and identified one Manta and two MK36 in Framura and two MK36 in Levanto. Two MK36 in Framura and one MK36 in Levanto were undetectable because they were concealed by the vegetation or masked by rocks. Remus detected, classified and identified two Manta and three MK36 in Framura and did not operate in Levanto. Theiis detected and classified two Manta and one MK36 in Framura and two MK36 in Levanto. Due to water depth limitations, Theiis did not survey the northern corner of Framura area where three mines were present. Remus and OEX showed great potential for MCM operations and the Klein demonstrated the good performance of a state-of- the- art commercial sonar. 4. PORTS/HARBORS SAFETY

3.3 MCM

The Italian Navy laid a field of exercise mines (8 MK36 and 2 Manta) in two lanes selected to include a variety of different bottom types (rocks, Poseidonia oceanica, sand, mud) and portions of highly cluttered areas (wrecks, man made objects laid to protect cables and sewage pipes). In order to compare the performance of the experimental systems with that of the Italian Navy mine hunter Numana, the position of the mines was not known to all teams. Numana surveyed Framura and Levanto lanes with SQQ14 sonar for detection and classification and performed visual identification with the Pluio ROV. Remus operated only in Framura due to weather. The AUV surveyed the area with "lawn mower" tracks using the 900 kHz Marine Sonic 7

8

Geographic Information Systems Groupe d'Etude Sous- Marine d e l'Atlantique

CAMS 2004

Recently, responding to a request by SACLANT, a new project was started to evaluate the applicability of COTS (Commercial Off-The-Shelf) AUV technology to MCM operations in response to t errorist mining of ports. Four demonstrations have been successfully conducted in La Spezia and Stranraer and one more is planned in Rotterdam. Current AUV technology is sufficiently mature to complement existing MCM assets (Mine Hunters and EOD 9 divers) and improve their limitations. Of particular interest is the capability to ship overnight small AUV s anywhere a crisis might occur and to place the appropriate sensors (sonar, optical, magnetic) in close proximity of mines without risking human lives. The limited cost of COTS AUV (compared with traditional MCM assets) allows to deploy fleets of specialized vehicles to achieve large area coverage. During exercise Northern Light 03, the OEX 9

Explosive Ordinance Disposal

5

Length: Diameter: Weight in air; Buoyancy: Maximum Depth: Operation Depth:

4.5-5.5 m .5rn 600-800 kg

-+0.5 kg 300rn 200 m

Survey Speed: Survey Endurance: Butteries: Line Keeping: Altitude Keeping:

2-4 knots 8 hours (at 3 knots) Nickel Mctul Hidrale +1- 2 meters +1- .5 meter

Figure 4. The Ocean Explorer (OEX) is designed to accommodate various sonar, camera, and oceanographic systems in modular sections. The length and weight of the vehicle depend on the payload configuration.

Framura ~" """""---------"""

Thetis & Klein '~MK36

t-_

~"

I

-\MK36

.. O·MI
- -

-

\ ; , . 3-MK36

~-MANTA

~" . . O$:QC1ed

"5~TA

.NoI 0\Itedfr.)

... NotCo<'"""
... N,,, ,"
.N~Sl,lfV~

. """""'"

\.,

/

~ ~ IAK6

&Unoctr:CI>lt::te

.U\'Kld~!l1t

Levanto Thetis & Klein

Numana

.-

"'Nct~ed

&U"""""",", A HctWI'\'tY!l
.-

MK36

& NctOolt<'.od

... u~ .N«'ur\'~

'"

.,.

...

Figure 5. Results of PC trial. Due to weather Remus operated only in Framura. Due to water depth limitations, Thetis did not survey the top corner of Framura lane where three mines were laid. Two mines in Framura and one in Levanto were concealed by vegetation or masked by rocks. The experiment clearly demonstrated the potential of Remus and Klein for MCM operations.

6

CAMS 2004

Figure 7. Working areas in La Spezia harbor. launched from Stranraer pier, and the Remus, operated by Royal Navy Fleet Diving Unit 2 (FDU2), surveyed the final part of Loch Ryan, where 4 exercise Manta mines had been deployed. The AUVs covered the 3000m by 300m area with three detection missions followed by a number of classification missions. Remus navigated in a network of acoustic transponders and imaged the seafloor with 900 kHz Marine Sonic side scan sonar. OEX navigated with a GPS tow float and imaged the seafloor with 600 kHz Marine Sonic side scan sonar and with a digital video camera. The side scan sonar data acquired by the vehicles were analyzed to determine the nature of the contacts and to provide their location to FDU2 divers for identification and disposal. A team of only 5 FDU2 divers successfully completed in 3 days a task that, if performed with traditional means, would have required 20 divers working 20 days 12 hrs/day. The purpose of the sea trial in La Spezia harbor (March 2004) was to demonstrate the effectiveness of AUVs and ROVs in support to mine hunters and EOD divers, to counter terrorist mining of La Spezia harbor. The exercise measured the effectiveness of AUVs in detecting, classifying and correctly geo-referencing targets for further prosecution by EOD divers. Remus, provided by Hydroid, was configured with Marine Sonic 900 kHz side scan sonar. The vehicle launched and retrieved from a rib boat navigated within a network of

CAMS 2004

Figure 6. Remus vehicle communicating with the LBL. acoustic long base line (LBL) transponders deployed by Leonardo (see figure 6). The Remus covered the assigned channel and the anchorage areas with orthogonal lines (see figure 7) in order to obtain multiple aspect insonification of all targets. Line spacing were designed to ensure full bottom coverage of the side scan sonar. All targets were detected and localized within 5 m of their true location. At present Remus communicates in real time via acoustic modem only status information. In the near future the vehicle will be able to transmit side scan sonar images of targets to a communication buoy that will relay the information to a ship or a shore installation.

7

5. CONTROL AND NAVIGATION: BASIC TOOLS FOR SUCCESSFUL MISSIONS The success of the AUVs missions showed in previous sections depends strongly on the good performances of the control and navigation systems. Seafioor classification and mines detection are only possible when side scan sonar acquires good quality images. This requires that the vehicles are able to follow pre-progammed paths, maintain a constant heading, speed altitude or depth especially in very shallow water. The AUV position during the missions is required with the highest precision in order to georeference all detected targets with minimal error typically less than 5m. '

5.1 Control System Typical requirements for the control system in AUV missions are: • • • •

course keeping constant depth constant altitude noise and disturbances rejection

The first three items are satisfied when the vehicle heading, pitch, depth and altitude control loops are stable and well tuned . Moreover the controller is requested to be insensitive to sensors noise (high frequency noise) and system parameters variations and robust to external disturbances. Example of external disturbances is the presence of Poseidonia oceanica on the sea bottom that causes wrong altitude measurements and affects the altitude controller's behavior. The problem is more evident when the AUV passes the border between clean seafioor and Poseidonia oceanica navigating in constant altitude mode. It is possible that a sudden variations in altitude is measured and the controller reacts rapidly running the risk to touch the bottom depending on vehicle length and altitude. Different strategies could be adopted for the control system design that are basically model- based or model-independent (Fossen 2002). The first approach requires the knowledge of at least reduced vehicle model and allows for the controller design, modification and first approximation tuning, by simulation. A drawback of this approach is that vehicle description could change with different payloads, so more vehicle models are needed and perhaps, different tuning of the controller is nec~ essary using different pay loads. It is often a hard task to obtain an accurate vehicle model with tests and identification work. Model- independent controllers are, in general, not so simple to tune but have the advantage of being robust to payloads changes.

8

Figure 8. Vehicle oscillations: heading angle (speed = 3 knots). The autopilots design can be approached in various methods. A standard decoupled PlO controller is proposed in (Jalving 1994), multivariable sliding mode controllers are presented in (Healey and Lienard 1993) , optimal controllers for AUVs are showed in (Juul et al. 1994, Feng and AlIen 2002) (LQG/LTR and Hoo methods), a self- tuning autopilot is proposed in (Goheen and Jeffreys 1990) and fuzzy logic based controllers can be found in (Craven et al. 1998, Song and Smith 2000). The control system of the OEX- C AUV available at the NATO Undersea Research Centre is modelindependent, it is a Fuzzy Sliding Mode Controller (FSMC) (Song and Smith 2000). The vehicle dynamic was estimated through open loop at sea tests and consequently a nonlinear controller, robust to system parameters variations , have been designed. The switching curve of the sliding mode controller can be obtained by at sea measurements and then approximated by fuzzy logic. When the controllers are well tuned, the vehicle is able to track desired paths with minimum oscillations in heading (highly desirable for side scan sonar acquisitions), in pitch and in depth/altitude (depending on the mission) . The consequences of ineffective controllers can be seen in figures 8 and 9 that show oscillations in heading and pitch. The problem is more evident looking at side scan sonar images (figures 10 and 11): in figure 10 two targets are visible (highlighted with circles) and the image is good quality; in figure 11 only one of the targets is recognizable and the quality of the image is less than the previous one.

5.2 Navigation System Navigation accuracy is a key factor in the use of the AUV. As part of the global Guidance, Navigation and Control (GNC) system (Fig. 12), the choice of the navigation subsystem should be

CAMS 2004

3 ..... . .

o

,...

; -, !

i' "-2

.

based on the global performances achieved by all the other vehicle subsystems. It is important to note that extremely high accuracy, though desirable, is not required by all the possible missions. The navigation accuracy required for an AUV collecting Oceanographic data (CTD) would be much smaller than for an AUV used for MCM or REA missions (Jalving et al. 2003). Like the control system, navigation accuracy has a significant influence on the payload sensor performance, because the vehicle position is used to georefence the collected data as well as the attitude and velocity can be used to process and compensate sensor data.

Figure 9. Vehicle oscillations: pitch angle (speed = 3 knots).

lligh· /e\:'f'1 CtW1WI..l4ltds

Actuators

Plant

Sensors

Figure 10. View of target (good control).

Figure 12. Block diagram of a typical GNC system For multi-purpose AUVs the best approach to the navigation problem is the use of an Aided Inertial Navigation System (AINS), taking advantage of the reliability and high bandwidth of an Inertial Measurement Unit (IMU), using external (aiding) sensor to reduce its typical low- frequency errors. Navigation sensor data are fused using an Error State Kalman Filter rather than estimating the desired quantities (velocity, position and attitUde), this filter estimates errors in measures and computed quantities. Figure 13 shows the typical scheme of an AINS, where position, velocity and attitude are calculated from IMU data (Navigation Equation) and than compensated for the errors estimated by the Kalman Filter comparing them with aiding sensor measurements. The basic sensor set for an AINS system includes:

Figure 11. View of target (vehicle oscillating).

CAMS 2004

• Inertial Measurement Unit (IMU) • Speed sensor, typically a Doppler Velocity Log (DVL)

9

Ir--w---~---.--~~-~-~--.I I

, i ,,

~s~

I

I

I I

, I

H'-~I5IL.t)-.....I E=~!:a fitter

m 'o1sl

estimates lof • .-n;nin

.rm n ,

.ng. Underwater transponder

......... -.d_ NYipltiM

"",

*"""

posftJoning

highly successful and demonstrated the clear advantage of using autonomous vehicles for a variety of REA and MCM missions (Bovio et al. 2003). In particular COTS AUV technology has been evaluated in MCM operations against terrorist mining of ports. Four experiments demonstrated that current AUV technology is sufficiently mature to complement existing MCM assets (Mine Hunters and EOD divers) and improve their limitations. Of particular interest is the capability to ship overnight small AUVs anywhere a crisis might occur and to place the appropriate sensors (sonar, optical, magnetic) in close proximity of mines without risking human lives. The work will continue in the following years in cooperation with the research partners and NATO navies to reach the final goal of assessing the value of AUV networks for operational use.

Figure 13. Aided Inertial Navigation System Structure • Depth/Pressure Sensor • Independent Position sensor, typically a GPS for initialization and sporadic error resets The accuracy of the speed sensor and the availability of frequent position updates together with IMU characteristics are key factors on the overall system performances. The availability of further aiding sensor (CVL 10 , Terrain Navigation, Transponders) based on advanced techniques extends the capabilities of the AUVs to perform a wider range of missions, however the choice of the sensor set should always be a tradeoff between the desired accuracy, the system complexity and the mission requirements (covertness, environmental factors, mission duration).

6. CONCLUSIONS Autonomous Underwater Vehicles (AUV) have reached sufficient maturity to be considered for military applications. After the successful completion of the GOATS Joint Research Procrramme (Bovio et al. 2001), the Centre has initiated a long term programme to explore and demonstrate the operational benefits and limitations of AUVs for battlespace preparation. This activity is based on multi-national, multi-disciplinary sea trials to evaluate the performance of commercially available AUVs in comparison with current military assets for MCM and REA applications. In addition, similarly to the GOATS series of experiments, the Centre studies with research partners the key technologies required for successful AUV deployment . The experiments carried out during the first test at sea, that took place in May- June 2002 in the Tyrrhenian and Ligurian seas, have been 10 Correlation

10

Velocity Log

REFERENCES Bovio, E., Coelho, E. and Tyce, R, Eds.) (2003). Maritime Recognized Environmental Picture (MREP) Conference Proceedings. number CP-47. NATO Undersea Research Centre. La Spezia, Italy. Bovio, E., Tyce, Rand Schmidt, H., Eds.) (2001). A utonomous Underwater Vehicle and Ocean Modelling Networks: GOATS 2000 Conference Proceedings. number CP-46. NATO Undersea Research Centre. La Spezia, Italy. Craven, P.J., R. Sutton and M. Kwiesielewicz (1998). Neurofuzzy control of a nonlinear multivariable system. In: UKACC International Conference on Control. Vo!. 1. pp. 531536. Edwards, J.R, H. Schmidt and K.D. LePage (2001). Bistatic synthetic aperture target detection and imaging with an AUV. IEEE Journal of Oceanic Engineering 26, 690- 699. Feng, Z. and R AlIen (2002). Hoc autopilot design for an autonomous underwater vehicle. In: Proceedings of the 2002 International Conference on Control Applications. Vo!. 1. pp. 350354. Fossen, T.!. (2002). Marine Control Systems. Marine Cybernetics. Trondheim, Norway. Goheen, K.R and E.R Jeffreys (1990). Multivariable self- tuning autopilots for autonomous and remotely operated underwater vehicles. IEEE Journal of Oceanic Engineering 15(3), 144-151. Healey, A.J. and D. Lienard (1993). Multivariable sliding mode control for autonomous diving and steering unmanned underwater vehicles. IEEE Journal of Oceanic Engineering 18(3),327- 339 . Jalving, B. (1994). The NDRE- AUV flight control system. IEEE Journal of Oceanic Engineering 19(4), 497- 501.

CAMS 2004

Jalving, B., K. Gade and E. Bovio (2003). Integrated inertial navigation systems for AUVs for REA applications. In: Maritime Recognized Environmental Picture (MREP) Conference Proceedings (E. Bovio, E. Coelho and R. Tyce, Eds.). number CP-47. NATO Undersea Research Centre. La Spezia, Italy. Juul, D.L., M. McDermott, E.L. Nelson, D.M. Barnett and G.N. Williams (1994). Submersible control using the linear quadratic gaussian with loop transfer recovery method. In: Proceedings of the 1994 Symposium on A utonomous Underwater Vehicle Technology. pp. 417- 425. LePage, K.D. and H. Schmidt (2000a). Laterally monostatic backscattering from 3-D distributions of sediment inhomogeneities. In: Proceedings of the 5th European Conference on Underwater Acoustics (M.E. Zakharia, P. Chevret and P. Dubail, Eds.). Lyon, Hawaii. pp. 1253-1258. LePage, K.D. and H. Schmidt (2000b). Spectral integral representations of multistatic scattering from sediment volume inhomogeneities. In: 140th ASA Meeting/NOISE-CON 2000, Newport Beach, CA, USA . Abstract published in Journal of the Acoustical Society of America, vol. 108, p. 2564. LePage, K.D . and H. Schmidt (2000c). Spectral integral representations of volume scattering in sediments in layered waveguides. Journal of the Acoustical Society of America 108, 1557- 1567. LePage, K.D. and H. Schmidt (2002a). Bistatic synthetic aperture imaging of proud and buried targets using an AUV. IEEE Journal of Oceanic Engineering 27, 471- 483. LePage, K.D. and H. Schmidt (2002b). Spectral integral representations of monostatic backscattering from three-dimensional distributions of sediment volume inhomogeneities. Journal of the Acoustical Society of America 113, 789- 799. Maguer, A., E. Bovio, W.L.J. Fox and H. Schmidt (2000a). In situ estimation of sediment sound speed and critical angle. Journal of the Acoustical Society of America 108, 987- 996. Maguer, A. , W.L.J. Fox, H. Schmidt, E. Pouliquen and E. Bovio (2000b). Mechanisms for subcritical penetration into a sandy bottom: Experimental and mode ling results. Journal of the Acoustical Society of America 107, 12151225. Moran, B.A. (1999). GOATS 98 AUV network sonar concepts for shallow water mine countermeasures. In: Proceedings of the 11 th international symposium on unmanned untethered submersible technology. Durham, NH. Schmidt, H., A . Maguer and E. Bovio (1998). Generic oceanographic array technologies

CAMS 2004

(GOATS) 98 - bistatic acoustic scattering measurements using an autonomous underwater vehicle. Technical Report SR-302. NATO Undersea Research Centre. La Spezia, Italy. Schmidt, H. and E. Bovio (2000). Underwater vehicle networks for acoustic and oceanographic measurements in the littoral ocean. In: MCMC2000: 5th IFAC Conference on Maneuvering and Control of Marine Crafts. Aalborg, Denmark. Schmidt, H., J .R. Edwards and K.D. LePage (2000). Bistatic synthetic aperture sonar concept for MCM AUV networks. In: International Workshop on Sensors and Sensing Technology for Autonomous Ocean Systems. Kona, Hawaii. Song, F. and S.M. Smith (2000). Design of sliding mode fuzzy controllers for an autonomous underwater vehicle without system model. In: OCEANS 2000 MTS/IEEE Conference and Exhibition. Vol. 2. pp. 835-840. Spina, F . and R. Grasso (2003) . Unsupervised sea bottom classification from side-scan sonar images using multi-resolution transform features. Technical Report SR- 372. NATO Undersea Research Centre. La Spezia, Italy. Spina, F ., E . Bovio and G. Canepa (2001). Seaftoor classification for MCM with AUV mounted sensors. In: Autonomous Underwater Vehicle and Ocean Modelling Networks: GOATS 2000 Conference Proceedings (E. Bovio, R. Tyce and H. Schmidt, Eds.). pp. 237- 246. Veljkovic, 1. and H. Schmidt (2000) . Experimental validation of numerical models of 3-D target scattering and reverberation in very shallow water. In: 140th ASA Meeting/NOISE-CON 2000, Newport Beach, CA, USA. Abstract published in Journal of the Acoustical Society of America, vol. 108, p. 2485. Zerr, B., E. Bovio and F. Spina (2003). Bathymetric sidescan sonar for covert and accurate MCM REA. In: Proceedings of the UDT 2003 Conference. Malmoe, Sweden.

11