Ship Hull Inspection with the HAUV: US Navy and NATO Demonstrations Results

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Philip Johns
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Robotics and MIT over the past three years, under Office of Naval Research and PMS- EOD funding.

1 Ship Hull Inspection with the HAUV: US Navy and NATO Demonstrations Results J. Vaganay, M. Elkins, D. Esposito, W. O Halloran (1) F. Hover, M. Kokko (2) Bluefin Robotics Corporation (1) Massachusetts Institute of Technology (2) Cambridge, MA - USA Abstract- The HAUV is a ship hull inspection vehicle prototype jointly developed by Bluefin Robotics and MIT over the past three years, under Office of Naval Research and PMS- EOD funding. The HAUV employs a unique DVL-based hullrelative navigation and control approach, which allows closerange sonar imaging, without recourse to any external navigation aid and without preparation of the ship being inspected. This paper presents results obtained with the vehicle during two demonstrations: the US Navy s HULSFest 2006 and NATO s Harbor Protection Trials I. INTRODUCTION The HAUV is a novel underwater robot that combines the maneuverability of an ROV with the flexibility of autonomous operations, so as to efficiently perform detailed surveys of large marine structures such as floating vessels. What distinguishes the HAUV from many other vehicles is its use of Doppler velocimetry along the hull to achieve fully hullrelative navigation and control. This attribute means that the vehicle can be operated without having to prepare the hull or to board the ship being inspected. Additionally, there is no need to install any kind of equipment on the ship or to deploy an LBL transponder or LBL array for navigation. Rather than follow preplanned tracklines in an LBL array, the HAUV maintains constant attitude and range to the hull, and dead reckons relative to it. The DVL is used for both of these purposes; a short stand-off distance (one meter) allows close, image-based inspection of the hull with the vehicle s Dual Frequency Identification Sonar (DIDSON). To follow the hull curvature, both the DVL and DIDSON are mounted on separate pitch actuators; the DVL can be pointed normal to the hull, and the DIDSON can operate at the shallow grazing angle that provides optimal sonar images. Eight hub-less bi-directional DC brushless thrusters, A Main Electronics Housing (MEH) containing IMU, GPS. depth sensor, compass, power boards, fiber optic tether board, PC104 stack, and Ethernet switch, An oil-filled Junction Box containing the thruster control board, A pressure tolerant, rechargeable, 1.5 kwh lithium polymer battery, Two pitch actuators; one for the DVL and one for the DIDSON, An integrated GPS/strobe antenna, An RF communications antenna, A 1200 khz RD Instrument DVL, A Sound Metrics DIDSON imaging sonar, Floatation foam, and Ballast weight. This paper contains a description of the HAUV and presents the results obtained with the vehicle during HULSFest 06 and HPT 06. II. SYSTEM DESCRIPTION A. Vehicle The HAUV weighs 82 kg and measures 98 x 71 x 38 cm. It is made up of the following components (Fig. 1): Figure 1: HAUV (with and without floatation foam)

Several components of the vehicle are standard Bluefin products that can be found in Bluefin12 survey vehicles (MEH, antennas, battery, and Huxley mission software).

MIT designed the overall physical vehicle around the existing components, developed the pitch actuators, and furnished the low-level flight control algorithms and software.

A joystick, allows the operator to move the vehicle around on the surface; underwater joystick control is also possible over the WiFi / fiber optic link.

2 Several components of the vehicle are standard Bluefin products that can be found in Bluefin12 survey vehicles (MEH, antennas, battery, and Huxley mission software). The junction box was designed by Bluefin specifically for the vehicle. MIT designed the overall physical vehicle around the existing components, developed the pitch actuators, and furnished the low-level flight control algorithms and software. The tether system was specified and put together by SPAWAR Systems Center San Diego [1]. A joystick, allows the operator to move the vehicle around on the surface; underwater joystick control is also possible over the WiFi / fiber optic link. This capability allows the vehicle to operate in a manual mode in complex areas, such as the running gear. This is, however, an area of work that we have not investigated very much, preferring to focus on autonomous operations. B. Topside Equipment The topside equipment is typically distributed between a support boat and an operator station located on a dock. The operator station equipment consists of a laptop, an Ethernet switch, a WiFi access point, and an RF communication transceiver, all packaged in a ruggedized case. The boat equipment consists of the vehicle s fiber optic tether spool, a WiFi access point and a power source if needed. Setting up the operator station and boat can be done in a matter of minutes. In the simplest case, the fiber tether can connect directly with the operator laptop. C. Vehicle Capabilities The HAUV is capable of waypoint navigation to transit close to the ship. Once within DVL range from the ship, the vehicle can autonomously find the hull, approach it to the desired standoff distance, and start the inspection survey [2]. The vehicle can execute two main types of hull inspection surveys, referred to as horizontal surveys and vertical surveys (Fig. 2). moves vertically along the hull, following curvature, again maintaining a level and fixed distance to the hull. In both cases, the vehicle s bearing is maintained by using both the DVL and the IMU. Horizontal surveys are used to image the side of a ship for hull inclinations up to 45º from vertical. Vertical surveys are used for higher inclination and to go under a ship (90º inclination with respect to the vertical). III. HULSFEST 2006 A. Introduction The HULSFest demonstration was organized by the US Navy EOD Program Office (PMS-EOD), the Naval Explosive Ordnance Disposal Technology Division (NAVEODTECHDIV), and SPAWAR Systems Center San Diego (SPAWAR SCSD). It was held at SPAWAR SCSD from February 20 th to March 3 rd, The objective was to evaluate the candidate technologies for conducting underwater ship hull inspection and localization missions, in support of the Navy EOD Hull Unmanned underwater Vehicle Localization System (HULS) program. Thirteen companies and institutions were part of this demonstration; entries included AUVs, ROVs, pole mounted sensors, and data processing software. Each participant was given two 2.5-hour windows on two consecutive days to demonstrate their technology. B. Target Ship The target ship was the flat bottom boat Acoustic Explorer (Fig.3). Mine shapes consisting of ammunition boxes had been placed at various undisclosed locations on the hull by EOD divers. The area that we inspected with the HAUV was the ship s middle section delimited by the red lines in Fig. 4. Figure 3. The Acoustic Explorer (Photo courtesy of SPAWAR Systems Center SD) Figure 2: HAUV inspection patterns. The DVL is controlled to remain pointed normal to the hull. The DIDSON is controlled to point at the hull with the best grazing angle (about 20º). In a horizontal survey, the vehicle sways at the desired depth while remaining level, normal to the hull and at the desired standoff distance. In a vertical survey, the vehicle Figure 4: CAD model of the Acoustic Explorer. The hull section inspected by the HAUV is delimited by the red lines (image courtesy of Seabotix)

C. Mode of Operation The operator station was set up in a tent on the dock, next to the Acoustic Explorer.

The vehicle was handled from a Zodiac that carried a car battery and inverter, the fiber optic spool, and a box with the spool and WiFi electronics (Fig. 5).

At the start of each demonstration period, the vehicle went through a series of in-air checks.

3 C. Mode of Operation The operator station was set up in a tent on the dock, next to the Acoustic Explorer. A large monitor was connected to the operator laptop to display the real-time sonar data for the observers. The vehicle was handled from a Zodiac that carried a car battery and inverter, the fiber optic spool, and a box with the spool and WiFi electronics (Fig. 5). The dockside operator communicated with the vehicle over the WiFi-fiber optic link; the RF link was available but not used. At the start of each demonstration period, the vehicle went through a series of in-air checks. It was then put in the water, connected to the fiber optic tether, and checked for ground faults and fiber/wifi Ethernet connectivity. The Zodiac then towed the vehicle to the ship. Before starting a mission, the boat operator would locate the vehicle at a start position on the surface, about two meters from the hull, roughly normal to it. The topside operator remotely started all missions from this condition. The vehicle would then dive and run the mission completely autonomously. increments towards the inboard side between each slice. Dive to 3.5-meter depth Move out from under the hull Surface During the entire survey the DIDSON pitch angle was automatically controlled by an aiming algorithm that tries to equalize the brightness across the DIDSON s field of view to provide the best possible image. The spacing of one meter was chosen to ensure 100% DIDSON coverage of the bottom of the hull with overlap. E. DIDSON Imaging The HAUV collected DIDSON images of good quality, showing the hull bottom to have many features (Fig. 6). Figure 5: Left: Topside setup. Right: Small boat setup. (Photos courtesy of SPAWAR Systems Center SD) D. Mission Description Our objective was to search the area delimited by the red lines in Fig. 4. The inboard side of that section, however, could not be searched because there was not enough clearance between the ship and the dock as shown in Fig. 3. The typical mission consisted of the following autonomous elements: Submerge to one meter depth Find and approach the side of the hull Execute a twelve-meter long horizontal slice to HAUV starboard with the DIDSON looking down, in order to image the bottom of the ship s side. Dive to 1.5 meter depth Execute a twelve-meter long horizontal slice to HAUV port with the DIDSON looking up, in order to image the top of the ship s side Go under the ship by performing the following steps: o Rotate the DVL 90º up in order to lock on the bottom of the hull o Dive to 3.5-meter depth o Move forward and under the hull Execute a survey of the bottom of the hull, consisting of 12-meter slices along the hull, with one-meter Figure 6: DIDSON images showing cooler pipes, an anode, and a sea chest F. Post-Mission Analysis The post-mission analysis consisted of: Reviewing the DIDSON files to select Mine Like Objects (MLO) or other features Aligning the DIDSON data with the navigation data using time stamps Projecting the MLO and feature positions in threespace, using navigation data and feature positions within the DIDSON frames Displaying the MLO location with respect to the other features numerically and graphically In the absence of prior information about the DIDSON representation of true MLO s, the vessel s anodes were our focus point. Only two mine shapes were located within the area inspected: right at the point where the vehicle would transition from the side to the bottom and at the stern-most end of the survey. Fig. 7 shows images of these two mine shapes on the bottom of the Acoustic Explorer. Fig. 8 shows an example of a MLO and feature map created with our PMA tool and data from one run. The black lines are contours of the coolers on the bottom of the hull. The black line at -3 meters on the port/starboard axis is the keel weld line, which could clearly be seen in the DIDSON images. The blue

dots show our MLO s. Groupings can be observed when the same MLO was seen several times on separate slices - during the same mission. Fig.

Figure 10: Layover of 10 similar HAUV missions. MLO clusters show the consistency of the vehicle s navigation. Figure 7: Left: Mine shape at the center of the image.

slices with a two-meter-long DIDSON field of view). In these conditions, the vehicle achieved a coverage rate of about 700 m 2 / hour. H.

A super-resolution algorithm run on several successive images of the same feature substantially improves the image quality (Fig. 11).

Figure 8: MLO map relative to the coolers. Numbers indicate DIDSON frames. Figure 11: Super-resolution rendering of the raw images in Fig. 6.

The other colors represent the points of impact of the four DVL beams on the hull (one color per beam) G. MLO Localization Consistency and Coverage Rate Fig.

4 dots show our MLO s. Groupings can be observed when the same MLO was seen several times on separate slices - during the same mission. Fig. 9 shows the reconstructed hull shape and vehicle trajectory for this run. bottom survey. The second mine shape was to the right hand side boundary of the survey. Figure 10: Layover of 10 similar HAUV missions. MLO clusters show the consistency of the vehicle s navigation. Figure 7: Left: Mine shape at the center of the image. Right: Mine shape at the bottom-right corner of the image We used a very conservative overlap to ensure 100% coverage of the bottom of the hull (one-meter spacing between slices with a two-meter-long DIDSON field of view). In these conditions, the vehicle achieved a coverage rate of about 700 m 2 / hour. H. DIDSON Mosaicking Sound View Systems, Inc. processed data from one of the HAUV missions. A super-resolution algorithm run on several successive images of the same feature substantially improves the image quality (Fig. 11). Sound View Systems also provided us with a preliminary mosaic [3] of the section of the hull bottom inspected by the HAUV (Fig. 12). Figure 8: MLO map relative to the coolers. Numbers indicate DIDSON frames. Figure 11: Super-resolution rendering of the raw images in Fig. 6. Figure 9: 3D view of the reconstructed hull shape. The vehicle trajectory is shown in cyan. The other colors represent the points of impact of the four DVL beams on the hull (one color per beam) G. MLO Localization Consistency and Coverage Rate Fig. 10 shows the MLO locations superimposed for ten successful HAUV missions, over the two days of tests. In most cases, all the locations are within a 0.5 m diameter circle for a given cluster. Note that these clusters are based on the open-loop Doppler odometry; only a single translation and rotation where used to generate the overlays. The red crosses identify the location of the mine shaped shown in Fig. 7. The first mine shape was right before where the vehicle started the Figure 12: Mosaic and MLO map for one mission (mosaic courtesy of Sound View Systems)

IV. NATO HARBOR PROTECTION TRIALS 2006 A.

It was held in La Spezia (Italy) between April 3 rd and 6 th, 2006.

Three institutions were involved in the hull inspection component of the demonstration: Ocean Module s Diver Hull Imaging and Navigation System (DHINS), Atlas Elektronik s CSCOUT AUV, and Bluefin/MIT

time display of the sonar data, but the vehicle kept going and completed its mission before the power came back up.

5 IV. NATO HARBOR PROTECTION TRIALS 2006 A. Introduction HPT 06 was organized by the Mine Countermeasures Forces Command (COMFORDRAG), NATO Undersea Research Center (NURC) and other Italian Navy local Commands. It was held in La Spezia (Italy) between April 3 rd and 6 th, The aim of HPT 06 was to test and evaluate the effectiveness of new technologies in facing the terrorist threat in harbor and very shallow waters. Three institutions were involved in the hull inspection component of the demonstration: Ocean Module s Diver Hull Imaging and Navigation System (DHINS), Atlas Elektronik s CSCOUT AUV, and Bluefin/MIT s HAUV. B. Target Ship The ship to be inspected was a moored, decommissioned SAURO-class submarine (Fig. 13). time display of the sonar data, but the vehicle kept going and completed its mission before the power came back up. Fortunately the vehicle logs all the sonar and navigation data onboard so that nothing got lost. Figure 13: SAURO-class submarine moored in La Spezia harbor. The red marks show the section of the hull inspected by the HAUV C. Mode of Operation The operator station was set up on the deck of a nearby docked MCM ship. A Zodiac was used to handle the vehicle near the submarine (Fig. 14). Here also the Fiber optic / WiFi link was used for communications between the operator station and the vehicle. Figure 15: 3D view of reconstructed hull shape. The vehicle trajectory is shown in cyan. The other colors represent the points of impact of the four DVL beams (one color per beam) E. DIDSON Imaging The hull was covered in marine growth and was featureless. The mine shape, located on the side of the submarine s keel, appeared at the edge of the DIDSON field of view (Fig. 16). Figure 14: Operator station on the MCM ship and Zodiac near the submarine D. Mission Description Due to the symmetry of the hull and to avoid the running gear, we limited the inspection to one side and to the 30 first meters of the hull starting from the bow. The two red marks in Fig. 13 show the approximate start and end of the survey, which consisted of 5 horizontal slices at different depths. In some of the slices the DIDSON was looking up, in others it was looking down. One mine shape had been placed in the area to be inspected by Italian EOD divers. Fig. 15 shows the hull of the submarine reconstructed using the vehicle s navigation data. The curvature of the hull along the length of the submarine can clearly be seen. Note that the power went down on the MCM ship 5 minutes before the end of the demonstration mission. We lost the real Figure 16: Mine shape in DIDSON images F. DIDSON Mosaicking SeeByte Ltd post-processed the demonstration data set and generated a 3D mosaic that they rendered on the reconstructed hull shape generated from the vehicle s navigation data [4] (Fig. 17). Figure 17: 3D mosaic on reconstructed hull shape. The vehicle s trajectory is shown as a solid white line (image courtesy of SeeByte Ltd)

6 V. LESSONS LEARNED In preparation for HULSFest, we had been working on a barge somewhat similar in shape to the Acoustic Explorer s mid-section (vertical sides and flat bottom). In San Diego, we were then able to start running the inspection mission we had planned right away, with only minor modifications to the mission plan. This allowed us to run many missions and collect a lot of data. Finding a submarine hull shape, however, is not as simple and we never had a chance to practice with the vehicle on that specific hull shape. Therefore, when we first ran the vehicle on the submarine in Italy, we found out that the curvature of the hull was causing some problems; not for the control of the vehicle but for the control of the DIDSON grazing angle. The DIDSON field of view settings that we had used on ships with lower hull curvatures were not well-suited to a submarine hull. This made it difficult for the aiming algorithm to maintain the desired DIDSON grazing angle. We then spent quite some time looking for the best settings and managed to find a working configuration just before the time scheduled for the demonstration. We found out that WiFi communications near Navy ships can be unreliable, which caused our real time sonar display to be sometimes intermittent. Since real time display is important so we will need to address this problem. Although not very strong (1 knot maximum), underwater currents during HULSFest caused some problems during the open-loop transition around the ship s chine. To prevent the vehicle from unknowingly drifting, we have to make sure that we keep the DVL locked on the hull all the time, even during transition maneuvers. Fast generation of a mission report containing the list of targets and their location is critical. We were somewhat unprepared on that front, having spent most of our time making sure that the vehicle would collect valuable data. We will then work on better post-mission analysis tools and aim for real time generation of the target list using Computer Aided Detection algorithms. Another lesson learned (or rather confirmed) is that obtaining a temporary export license and shipping equipment between the US and Italy is a nightmare. The HAUV barely made it on time for the Italian demonstration... VI. CONCLUSION The HAUV participated in two successful demonstrations in the US and in Italy. Except for minor problems easily solved in the field, the vehicle ran reliably without hardware failure. Navigation, control, and imaging of a flat bottom boat and a cylindrical submarine hull have been demonstrated. The vehicle collected good DIDSON images and was able to send sonar data to the surface for real time display. Good navigation accuracy has been demonstrated over short duration missions on the Acoustic Explorer. The HAUV is still a prototype and a lot of work remains to be done to use it to its full potential. The key features desired from a ship hull inspection system are: 100% coverage, fast coverage rate, real-time generation of the contact list, and fully autonomous operations. To reach that goal, we are now going to focus on fully autonomous operations on noncomplex parts of the hull. This entails acoustic communications, automatic control of the vehicle s trajectory ensuring minimum overlap in the sonar data, onboard Computer Aided Detection (CAD), mission re-direction for close inspection of detected features, onboard Computer Aided Classification (CAC), and generation of sonar snippets to be sent over the acoustic link together with navigation information. Since this is a difficult goal to reach, we will go through an intermediate supervisory control phase where the operator will perform the tasks that are still difficult to implement automatically, such as the detection of suspicious features in the DIDSON data, the control of the vehicle s motion for classification of the detected feature (joystick-type of control of some of the vehicle s degrees of freedom), etc. This will obviously require the development of an integrated operator interface. In parallel to supervisory control, image processing algorithms (CAD/CAC, mosaicking) will be developed and tested in real time on the topside sonar data. Once mature enough, they will be ported into the vehicle. Work will also be done to address the inspection of the complex parts of the hull (e.g. running gear) by using an approach based on integrated control and Simultaneous Localization and Mapping (SLAM). Ultimately, all the capabilities will be brought together, giving the HAUV the ability to inspect an entire ship hull. REFERENCES [1] J. Buescher, A Fiber-Optic Tether for the Hull Search UUV, Technical document 3203, SPAWAR Systems Center San Diego, Feb [2] J. Vaganay, F.S. Hover, et al., Ship Hull Inspection by Hull-Relative Navigation and Control, Proceedings of IEEE/MTS Oceans [3] K. Kim, N. Neretti, and N. Intrator, "Mosaicing of Acoustic Camera Images," IEEE Proc. Radar, Sonar & Navigation, 152 (4), pp [4] S. Reed, A. Cormack, K. Hamilton, I. Tena Ruiz, and D. Lane. Automatic Ship Hull Inspection using Unmanned Underwater Vehicles, Proceedings from the 7th International Symposium on Technology and the Mine Problem. Monterey, USA. May, 2006.

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