uROV: A Digitally Enabled Platform for the Future of IMR

Deniz Sevinc, uROV Project Lead

Authors: J. Vincent, D. Petrone, and J.B. Blamengin

Agenda

• Digital enablement

• uROV program

• What’s next

• Questions

2

3

ACCESSIBILITY

CONNECTIVITY

ANALYTICS

DATA

IOT

ADVANCED SENSING

AUTOMATION

Digital Enablement: OneSubsea Perspective

Enabled residency

ADVANCED SENSING

AUTOMATION

ACCESSIBILITY

CONNECTIVITY

Enabled visualization and control

Enabled efficiency in workflows

ANALYTICS

4

uROV Program

5

uROV platform

Schlumberger technologies

deployed on

SAAB Sabertooth vehicles

Deployment

efficiency

Next-generation

sensing

Digital

enablement

Strategic drivers Key technologies

Subsea

communications

Supervised

autonomy

Automatic

“eventing”

uROV Program

6

Autonomous Vehicles in Support of Naval

Operations 2005, National Academy of Sciences AUV

“Joystick control”

• Legacy approach

• Expensive deployment

• Data through tether

ROV

OneSubsea uROV“Supervised autonomy”

• Pragmatic approach

• Prescribed real-time data

• Agility

“Fire and forget”

• Future of IMR

• Trust issue around

sensitive infrastructure

• Development cost

Supervised Autonomy

7

Up to

200 m

Person in

the loop

1. Vessel

2. Host

3. Shore

Subsea

gateway

Surface gateway

up to

3 km

Subsea Communications

8

Without connectivity, digital is limited

10 Mbps

1 Mbps

100 kbps

10 kbps

1 kbps

10 m 100 m 1 km 10 km

Acoustic

100 Mbps Optical

EM/MI

1 m

Target bandwidth

at range (brownfield)

Wireless Communications: Acoustics

• 2017 Achievements

• Live video

• 10× commercial

modems

• 2018

• Integration into

uROV platform

• 2019+

• Development to

3 km

9

100 kbps at 1 km, video transfer, Boston, Oct. 2017, San Diego Dec. 2017 (vertical).

2017 achievements

2018

2019+

WORLD RECORD

Next-Generation Visualization and Measurement

Streaming LIDAR

10

Computer Vision & Machine Learning

11

Collect Subsea Data: Offline and Online

Visual Laser Sonar

CP, Nav,

Depth,

SVP, etc.

Others

Feed into Neural Network for Machine Learning

Supervised Learning2018 Project

Mantis with

major

Use Cases

Data Processing

Automation

Vehicle Command

and Control

• Autonomy aid• Feature detection • Online eventing

12

Cognitive Telemetry

• High-speed acoustic video

streaming

• Adaptive data delivery

• Telemetry manager

Supervised Autonomy

• Interactive mission planning

• Situational awareness

Next-Generation Sensing

• LIDAR

• Efficient acquisition

• Automated processing

uROV 1.0

Residency

13

Acknowledgements

OneSubsea Services Team

Schlumberger–Doll Robotics Research

SAAB

Thank you.

Questions?

14