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Robust Pipeline Localization for an Autonomous Underwater Vehicle using Stereo Vision and Echo Sounder Data

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Robust pipeline localization for an AUV using stereo vision

and echo sounder data

Gøril M. Breivik*, Sigurd A. Fjerdingen, Øystein Skotheim

SINTEF, Norway

*[email protected]

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Submarine pipeline shutdowns are costly

 Submarine pipelines

important network for oil/gas

connect offshore to onshore

 Example:

Gas field Ormen Lange meets 20 percent of UK’s gas

requirements

Pipeline Langeled of length

1,200 km connects the gas field to UK

 Pipes need to be inspected:

processing stops are costly and should be avoided

environmental harm should be prevented

www.gassco.no

(3)

Inspection can reveal pipe defects

 Possible pipeline defects:

corrosion

cracking

stress

bending

denting

movements

free spans

partial burial of the pipe

www.jee.co.uk

(4)

Submarine pipe inspection is cost and time consuming

 Inspection using remotely operated vehicles (ROV)

includes a manned support vessel

limited operating range

limited weather conditions

relatively slow speed

www.km.kongsberg.com

(5)

AUV is the solution to many cost issues

 Autonomous underwater vehicles (AUV):

unmanned

untethered

no support vessel

operate autonomously

www.ntnu.no/gemini/

(6)

Pipeline tracking is essential to AUVs

 SINTEFs AUV

developed for research

several sensors:

two underwater cameras

echo sounder

sonar

IMU

GPS (for use in surface)

 Autonomous navigation:

how to localize pipeline relative to AUV?

how to robustly track pipeline position?

(7)

Three sensors ensure more continuous pipeline tracking in 3D

 Two sensor combinations:

one camera and echo sounder

stereo camera

 Recordings show that:

accuracy is equal for both sensor combinations

accuracy is good enough for our needs

using both combinations ensures more continuous pipe localization over time

(8)

Outline

 3D localization using one camera and echo sounder

 3D localization using stereo cameras

 Experiments and results

 Conclusions

(9)

Outline

 3D localization using one camera and echo sounder

 3D localization using stereo cameras

 Experiments and results

 Conclusions

(10)

3D pipe position found using one camera

 Principle of algorithm:

pipe is a line in camera image

this line spans a plane in 3D when seen from the camera

sea floor is a second plane in 3D, given by depth

measurements from the echo sounder

pipe position is found as the intersection line of the two planes in 3D

 Assumption:

the sea floor is assumed horizontal in the area of interest

a

(11)

Outline

 3D localization using one camera and echo sounder

 3D localization using stereo cameras

 Experiments and results

 Conclusions

(12)

Epipolar lines give point pairs for stereo triangulation

 Principle of algorithm:

points correspond to epipolar lines

pick two points on pipe in right image (o and o)

epipolar lines (- and -) cross pipe in corresponding points

conventional stereo triangulation is used to find position in 3D

pipe position is defined as a straight line through the two 3D points

left camera right camera

(13)

Outline

 3D localization using one camera and echo sounder

 3D localization using stereo cameras

 Experiments and results

 Conclusions

(14)

Pool experiments enable ground truth comparison

 Experiments from a pool

AUV kept stable in four positions relative to pipe

Sensor data recorded

Ground truth measured using a tape measure

 Three sensor combinations give three pipe positions:

Left camera + echo sounder

Right camera + echo sounder

Stereo camera

(15)

Left camera + echo sounder Right camera + echo sounder Stereo camera

Ground truth

Estimated pipe positions lie close to

ground truth

(16)

Echo sounder approach gives pure horizontal pipe positions

view from above view from the side

Left camera + echo sounder Right camera + echo sounder Stereo camera

Ground truth AUV in origin (o)

(17)

Outline

 3D localization using one camera and echo sounder

 3D localization using stereo cameras

 Experiments and results

 Conclusions

(18)

Conclusions

 Equal accuracy for both algorithms:

mean: 8-17 cm (position) and 1°-3° (angle)

standard deviation: 3-16 cm (position) and 0°-9° (angle)

good enough for our needs

 More robust pipe tracking using both algorithms:

Echo sounder performs 2x better than stereo (true positives)

Stereo camera assumes pipe segmentation from two images

Echo sounder assumes horizontal sea floor

(19)

Final comments

 Measuring ground truth is challenging

 Adjusting for vehicle movement using intertial

measurement unit data can improve results

(20)

Thank you!

www.sintef.com/omd

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