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Integrating Autonomous Underwater Vehicle Capability into Hydrographic Operations
Susan Sebastian
Lawrence Haselmaier
R. Wade Ladner
Naval Oceanographic Office
Hydrographic Department
Canadian Hydrographic Conference
18 May 2016
The inclusion of names of any specific commercial product, commodity or service in this
presentation does not imply endorsement by the U. S. Navy or NAVOCEANO. The views
expressed in this presentation are those of the authors and do not necessarily reflect the
official policy or position of the Department of Navy, Department of Defense, nor the U.S.
Government.
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Topics
1. Introduction to the Littoral Battlespace Sensing-
Autonomous Underwater Vehicle (LBS-AUV)
2. Operational methods required to meet
hydrographic standards
3. Understand the function of the onboard sensors
4. Horizontal and Vertical accuracy methods
5. Calibration and Mission Planning
6. Overall process flow
7. Conclusions
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LBS-AUV REMUS 600
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Emphasize bathymetric data collection to support hydrographic and
mine warfare survey requirements
Developed with the shallow water Kongsberg EM3002 multibeam sonar and
positioning capability to meet stringent accuracy requirements
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Survey Operation
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Parameters to consider include:
• the sortie duration (in time and distance)
• vehicle altitude and swath width
• number of lines and turns
• where and how many UTP transponders are needed (for
position updates)
• orientation of lines
• frequency of position updates
• speed of advance
• water depth
• vehicle altitude
• maximizing swath width, and other factors
Mission Planning Parameters
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Acoustic Positioning
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• Long Baseline multiple transponders
of known locations are pinged and
those slant ranges are used to
triangulate the vehicle position
• Ultra-Short Baseline (USBL) range and
bearing measurements are obtained
between a single transducer on a
surface vessel, such as the High
Precision Acoustic Positioning System
(HiPaP) and the vehicle multi-element
transducer
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Underwater Transponder Positioning
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• Complement to USBL acoustic positioning
• Key: tight integration between the range
measurements and the inertial navigation
system significantly improves the real-time
accuracy
• As few as one UTP transponder can be
deployed, centrally located
• Deploy multiple transponders to increase
range of survey area
• Position error increases between position
updates; drift limit controls line length
Covariance ellipse of
position error compresses in
vicinity of UTP transponderHegrenaes, et al. 2009
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DVL-Aided INS
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• Inertial navigation degrades, or drifts,
very rapidly with distance from the last
known location
• Inaccurate vehicle velocity and heading
are the primary obstacles to position
accuracy
• Doppler Velocity Log provides an
independent and reliable measurement
of the vehicle velocity to aid the INS in
detecting and mitigating the inertial
measuring unit (IMU) velocity error
http://www.rdinstruments.com/navigator.aspx
Teledyne RD
Instruments Workhorse
Navigator Doppler
Velocity Log
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Position Drift Error Limit
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Intended main line
Max.
allowable
drift error
• Vehicle must encounter a position update BEFORE exceeding the
allowable cross-track error
• Max. drift limit is primary parameter affecting length of the lines and
transponder placement
UTP
Transponder 1
UTP
Transponder 2
Last known
location
Acquire known
location after driftposition update
radius position update
radius
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Mission Pattern
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• Maneuvering has a significant impact on the drift
error
• Velocity error in the IMU becomes observable when
the measured acceleration can be compared to the
predicted centripetal acceleration
• Cancelling effect increases for shorter lines with
turns
Jalving, B., E. Bovio, Gade, K, 2003
Testing has demonstrated position drift of 0.1% of distance travelled
or 1m per kilometer! Remember this number!
7] Jalving Bjorn, Kenneth Gade, Kristian Svartveit, Are Willumsen, Robert Sorhagen, 2004,
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UTP Transponder Layout
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• Ensure 2km position update radius is commensurate with the
specific environmental conditions
• The transponders positioned with the HiPaP
• Position drift error bounds the survey line length (0.1% dist.
travelled, or 1m/km)
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Real Time Position Accuracy: NavP
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Jalving Bjorn, Kenneth Gade, Kristian Svartveit, Are Willumsen, Robert
Sorhagen, “DVL Velocity Aiding in the HUGIN 1000 Integrated Inertial
Navigation System,” 2004
• Rigorous real-time navigation
solution provided by Kongsberg
Navigation Processing Suite
(NavP)
• Provides complete time
synchronization and integration
of onboard navigation and
environmental sensors
• NavP can be remotely initialized,
monitored, and supplied with
surface position via modem
• Uses the tight coupling between
the INS with the UTP as well as
all navigation and environmental
sensor inputs
• Real-time Kalman filter improves
the best accuracy for position
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Navigation Post-Processing NavLab
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Backward/forward processing
can significantly improve the
final solution
Navigation Laboratory (NavLab)
is a powerful and versatile tool to
estimate the vehicle’s position,
attitude and velocity
NavLab uses all measurements
and applies the optimal
smoothing algorithm in the
NavLab Kalman filterGade, Kenneth “NAVLAB, a Generic Simulation and Post-processing
Tool for Navigation,” European Journal of Navigation, Volume 2,
Number 4, November 2004, The Netherlands
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Navigation Post-Processing Result
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Position accuracy data from the 2011 test period in Sidney, Canada show DVL-
aided INS (without UTP) before and after post-processing
Saw tooth pattern of error (blue line) is typical where position error ramps up
rapidly from known positions, and then falls sharply when an updated position is
obtained or as a result of vehicle maneuvers
[3] Cronin, Doug, Dave Small, Shannon Byrne, 20-24 February 2012, New Zealand
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Tide Measurement Options
GPS Buoy: records changes in water levels relative to the
ellipsoid; tide data must be continuous throughout AUV operations
Liquid Robotics Wave Glider SHARC
(Sensor Hosting Autonomous Remote Craft): long-duration
Unmanned Surface Vehicle (USV) that utilizes wave energy
for propulsion and solar panels for energy;
in addition to sending position updates to AUV,
can act as a GPS buoy
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Virtual Tide Corrector (VTC) from nearby
vessel: promising technique under
development
Challenge: Measure tides without
land-based tide gauge![11] Haselmaier, Lawrence, September 2015
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Twofold Calibration
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Cal1: Bias in pressures between vehicle
and deck-mounted barometer Calibrations required prior to
data collection!
Barotroll mounted at deck level
Weatherpak mounted on mast
Baro
me
tric
Pre
ss
ure
(m
b)
Time (days)
Cal2: Multibeam Patch
Test for sensor
alignment error
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Constant Altitude & Swath Width
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Advantage of the AUV data collection
• Vehicle stays at constant height
• Swath width remains the same whether the
depths grow deeper or shallower.
• Up and down slope vice parallel to depth
contours
• No data gaps between swaths; very
efficient
<50m
>200m
Entire swath constant 120m
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Sortie and Mission Planning
Vehicle stamina: 24 hours
During 20 hours on-line, six lines of data can be acquired each sortie
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Main-Line Development
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• Multiple sorties may be stacked to reduce the amount of transponder
repositioning
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Cross-Line Comparisons
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• Cross-line data should be the most accurate available
• QC tool: collect first so routine processing of main-line data is evaluated
as the mission progresses
• Cross-line placement near the transponder(s) is the obvious location
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Overall Process Flow
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Increased survey manning to 3 Lead Positions from
Hydrographic Department
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Conclusions
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1. NAVOCEANO is flagship for implementing US Navy
unmanned capabilities
2. UTP tightly coupled with the DVL-Aided inertial allows
required position accuracy for hydrographic standards
3. Ellipsoid-referenced survey techniques show promise in
extracting the needed water level corrections
4. Large strides have been made and operational use now
needed to further define process and realize capability
5. LBS-AUV operations is an exciting new area for
hydrographic and mine warfare applications
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Questions?
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Cited References
[1] Nicholson, J. W., PhD., Capt., USN, et. al., “The Present State of
Autonomous Underwater Vehicle (AUV) Applications and
Technologies,” Marine Technology Society Journal, Vol. 42, Number
1, Spring 2008
[2] Purcell, Mike, “New capabilities of the REMUS Autonomous
Underwater Vehicle,” Woods Hole Oceanographic Institution, IEEE,
2000
[3] Cronin, Doug, Dave Small, Shannon Byrne, “REMUS 600
Autonomous Undersea Vehicle Planning, Acquisition, and
Processing Workflow,” Proceedings Shallow Survey 2012, 20-24
February 2012, New Zealand
[4] Long and ultra-short baseline acoustic positioning systems:
https://en.wikipedia.org/wiki/Long_baseline_acoustic_positioning_sy
stem and https://en.wikipedia.org/wiki/Ultra-short_baseline
[5] Hegrenaes, Oyvind, Kenneth Gade, Ove Kent Hagen, Per Espen
Hagen, “Underwater Transponder Positioning and Navigation of
Autonomous Underwater Vehicles,” Proceedings of The Mts/Ieee
Oceans Conference and Exhibition, Biloxi, 2009
[6] Jalving, B., E. Bovio, Gade, K., “Integrated Navigation for AUVs
For REA Applications,” NATO Underwater Research Center
Conference Proceedings from MREP2003, NATO Underwater
Research Center May 12-15, 2003, La Spezia, Italy, available
www.navlab.net
[7] Jalving Bjorn, Kenneth Gade, Kristian Svartveit, Are
Willumsen, Robert Sorhagen, “DVL Velocity Aiding in the
HUGIN 1000 Integrated Inertial Navigation System,”
Modelling, Identification and Control Journal, Norway, 2004,
Vol 25, No 4, pp. 223-236.
[8] Zhao, Lin and Wei Gao, "The Experimental Study on
GPS/INS/DVL Integration for AUV,” IEEE Xplore, October
2008, by, Automation College, Harbin Engineering
University.
[9] Fulton, Thomas F., “Navigation Sensor Data Fusion for
the AUV Remus,” Marine Technology Special Edition,
Volume 38, Number 1 (ISSN 0025-3316), January 2001
[10] Gade, Kenneth “NAVLAB, a Generic Simulation and
Post-processing Tool for Navigation,” European Journal of
Navigation, Volume 2, Number 4, November 2004, The
Netherlands
[11] Haselmaier, Lawrence, “Computation of a Virtual Tide
Corrector to Support Vertical Adjustment of AUV Multibeam
Data,” MS Thesis, University of New Orleans, New Orleans,
LA, September 2015
[12] RD Instruments, “Workhorse Navigator Doppler Velocity
Log (DVL),” http://www.dvlnav.com/pdfs/navbro.pdf, June
2003.
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