Autonomous marine operations and systems in the · PDF file Centrefor Autonomous Marine Operations and Systems -AMOS 1 Autonomous marine operations and systems in the Arctic Professor

1Centre for Autonomous Marine Operations and Systems - AMOSwww.ntnu.edu/amos

Autonomous marine operations and systems

in the ArcticProfessor Asgeir J. Sørensen,

Department of Marine Technology, Norwegian University of Science and Technology,

Otto Nielsens Vei 10, NO-7491 Trondheim, NorwayE-mail: [email protected]


• Technology platforms for integrated environmental mapping and monitoring

• Laboratories for unmanned systems• AMOS research areas on unmanned systems

Content


Integrated Environmental Mapping and Monitoring

Ingunn Nilssen et al.


Stationary platforms

AUVs

Satellites

Ships

Spatial and temporal resolution and coverage of different platforms

Gliders

ROVs


Lander Characteristics

http://www.metas.no/

Instrument platform either standing on the seafloor (lander), or suspended in the water column moored to the seafloor or tethered to floating device at the surface

Offline or accessible via cable or satellite/radio communication

Unlimited depth range


ROV Characteristics Main components: vehicle, umbilical

and control stations Delivered in different sizes, depth and

thrust ratings, functionality, manipulator and sensors

Power supply and communication by umbilical

Navigation by means of acoustics, INS, DVL

ROV is normally launched from crane on ship with station keeping capability by anchors or dynamic positioning (DP) system


AUV Characteristics Main components: vehicle,

control station, acoustic navigation and for bigger AUVs launch and recovery system

Delivered in different sizes, depth and thrust ratings, functionality, and sensors

Carries its own power supply Operates supervised or

autonomously with limited communication ability

Limited access to AUVs with manipulator capabilities doing light intervention and sampling


Glider Characteristics• Long operational range• Slow speed operation – 0.4

m/s average.• Operation typical 15-30 days

covering 600-1500 km range• Less navigation and control

capabilities of the vehicle• May divide into small gliders

(0-100 m depth) and large gliders (0-1000m).

• Deployed from boats and quayside

• Used for oceanographic surveys

• Buoyancy driven propulsion by variable ballasting of water




Content


NTNU AUR-Lab and UAV-Lab: Integrated technology platform for ocean space research

Air:Penguin B fixed-wing UAVX8 fixed-wing UAVHexa-copters

Water column and sea floor:ROV MinervaROV 30kROV SEABOTIXAUV Remus 100HUGIN HUS

Sea surface:Ships - Gunnerus

ROV Minerva

AUV REMUS 100 at Svalbard

Photo: NTNU AUR-Lab

Photo: NTNU AUR-Lab

Photo: NTNU AUR-Lab

Photo: NTNU UAV Lab

11Centre for Autonomous Marine Operations and Systems - AMOSwww.ntnu.edu/amosPhoto: NTNU AUR-Lab

NTNUApplied Underwater Robotics Laboratory

AUR-Lab


NTNU Research Vessel Gunnerus

NTNU's research vessel, R/V Gunnerus, was put into operation in spring 2006. The ship is fitted with a dynamic positioning system and a HiPAP 500 unit, optimal for ROV operations and the positioning of any deployed equipment.

The vessel is arranged with wet lab, dry lab and a computer lab in addition to a large aft deck.

Accommodation comprise three double berth scientific personnel cabins and three single berth crew cabins. The large mess hall functions as a lecture room for 25 people.


ROV Minerva

• Observation class– ~400 kg– 3CCD camera– 3 ”regular” ROV-camera– 5-function manipulator– 1-functions manipulator– Scanning sonar– Altimeter– ~600 meter cabel on

winch (fiber)– HiPAP and DVL for

positioning– Control container


- HD 1080i camera (HD SDI or HDMI)- External LED lights- SD Camera (520 line Wide Dynamic Range color - 0.1 Lux)- Tritech Micron Scanning Sonar (75 meters range)- 150 m umbilical

Depth Rating 200 Meters (Seawater) Length 530 mm Width 245 mm Height 254 mm Diagonal 353 mm Weight in Air 11 kg

SEABOTIX LBV – 200-4

15Centre for Autonomous Marine Operations and Systems - AMOSwww.ntnu.edu/amos 15

AUV REMUS 100

• Marine Sonics 900 kHz Side Scan sonar

• Teledyne RDI 1.2 MHz up/down DVL/ADCP

• Wet Labs ECO Triplet puck

• Aanderra Dissolved Oxygen Optode

• Neil Brown CT sensor

• LBL navigation system

• Imagenex Delta T multibeamechosounder

Navigation:Inertial NavigationGPS/HiPAP (tracking, aiding)

Communications:Acoustic modem, Wi-Fi, Iridium

REMUS support from Horten

REMUS training in Horten


Hugin HUS collaboration

• National collaboration lead by FFI– FFI– UiB/HI– NTNU– Kongsberg Maritime


« Wet Dream »NTNU Subsea Centre

for Education, Research, and Innovation

Photo: NTNU AUR-Lab


Harbour

Located at TBS• Truck• Crane• LBL network• Containers


Proposal: NTNU Subsea Center at Trondhjem Biological Station

• Workshop• Quay• Water depth

120m


NTNU Subsea Centre

21www.ntnu.edu/amos Centre for Autonomous Marine Operations and Systems

Unmanned Aerial Vehicle (UAV)Laboratory and Research

Professors Tor A. Johansen and Thor I. FossenDepartment of Engineering Cybernetics

22www.ntnu.edu/amos Centre for Autonomous Marine Operations and Systems

Main Goals

We intend to enable autonomous marine operations with Unmanned Aerial Systems (UAS)

• Fault‐tolerant control, navigation and communication for BLOS operations• Harsh environment; anti‐icing systems• Autonomous ship‐based launch and recovery• Onboard intelligence – cannot assume high‐quality communication:

Real‐time image and sensor data analysis, remote sensing, search and tracking• Delay‐tolerant communication relaying and networking;

Heterogeneous multi‐vehicle BLOS operations• UAS‐assisted deployment and recovery of sensor nodes and other assets

Maritime and Coastal UAS Scenarios• Large distances (100’s km) and long endurance (>8 hours) BLOS operations• Very limited communication infrastructure in many areas (including arctic regions); satellite

systems with small footprint are generally sparse, unreliable, expensive, and low capacity.• Low risk for incidens involving third parties; little air/surface traffic, sparsely or not populated

IEEE 802.11b/g (WiFi) node; 2.4 GHz

UbiquityUniFi AP‐OUTDOOR+Access Point(2.4 GHz)

UbiquityAirMax Rocket M5 Station/Bridge(5.8 GHz)

UbiquityAirMax Rocket M5 Access Point / Bridge (5.8 GHz)

Router with DHCP server

PC with AUV command and control software

Networked operation with aerial, surface and underwater vehicles

Example: UAV for communication relaying

Remus 100 AUV (Autonomous Underwater Vehicle)

X8 UAVOnshore command and control center




Content


2013-2022

Centre for Autonomous Marine

Operations and Systems

2014-11-21


Shipping

Offshore renewable energy

Ocean Science

Oil & gas in deeper water…

…. and in Arctic areas

SUPER CLUSTER

Ocean Industry

Aquaculture and biological production

Marine mining

Fisheries


Vision• To establish a world-leading research centre on autonomous marine

operations and systems• Fundamental knowledge is created through multidisciplinary

theoretical, numerical and experimental research within the knowledge fields of hydrodynamics, structural mechanics, guidance, navigation and control.

• Cutting-edge interdisciplinary research will provide the needed bridge to make autonomy a reality for ships and ocean structures, unmanned vehicles and marine operations, to meet the challenges related to greener and safer maritime transport, monitoring and surveillance of the seas and oceans, offshore renewable energy, and oil and gas exploration and production in deeper and Arctic waters.

The Centre of Excellence (CoE) will contribute to improved international competitiveness of Norwegian industries as well as to safety and protection of the marine environment.


Greener operations

Offshore renewable

energy

Autonomous surveillance

Oil & gas in deeper water…

…. and in Arctic areas

Centre for Autonomous Marine

Operations and Systems

Hydrodynamics andStructural Mechanics

Guidance, Navigation and Control

Experiments

Knowledge fields &research methods

Interdisciplinary researchareas &

challenges

AMOS

Next step in research, education and innovation

Open water biological

production


AMOS Facts and Figures 2014Personnel in 2014:6 Key scientists/professors6 Adjunct professor9 Affiliated scientists2 Scientific advisors/professors4 Post Docs/researchers53 PhD candidates (target: 100)2 administrative staff

Graduated PhDs:5 PhDs graduated from associated AMOS projects (3 IMT and 2 ITK)

Partners:NTNU, Research Council of Norway, Statoil, DNV GL, MARINTEK, SINTEF Fisheries and Aquaculture, SINTEF ICT

Budget (10 years):700+ MNOK


Department of Marine Technology

NTNU

Engineering Scienceand Technology

Centre for Autonomous Marine Operations and Systems (AMOS)

Information Technology, Mathematics and Electrical Engineering

Department of Engineering Cybernetics

SINTEF Fisheries and Aquaculture

SINTEF ICT

Statoil DNV GL

AMOS

MARINTEK

SINTEF

RCN


1. Autonomous offshore renewable energy2. Offshore aquaculture 3. Autonomous unmanned vehicles and

operations4. Smarter, safer and greener marine vessels

and operations

Research Areas


Why autonomy?

Enables operations in complex, harsh and remoteenvironment (Dull/Dirty/Dangerous Operations)

Enables complex functionality; provides fault tolerance and robustness

Qualified operators may be a shortage

Unmanned systems may be smaller, lighter, cheaper and safer to deploy and operate

Unique (or cheaper) solution when no (or limited) communication is available (bandwidth, remoteness)

Mandatory for new functions

Smarter systems that depend less on human operators


Autonomy: definition(s)

To avoid a prolonged debate over how much “intelligence” isrequired for a vehicle to be considered “autonomous,” the committeeelected to include within the scope of this report all relevant vehiclesthat do not have a human onboard.(Autonomous Vehicles in Support of Naval Operations Committee onAutonomous Vehicles in Support of Naval Operations, National ResearchCouncil, 2005)

Intelligent systems due to their ability to manage unexpected eventsand unstructured and uncertain environments. […] this meansintegrating mathematical models with real-time data from sensorsand instruments and allowing algorithms with optimized response tobe designed and embedded in computer systems(AMOS Centre of Excellence research Proposal, 2012).


AUTONOMOUS ROVER Curiosity• Highly unknown environment (Mars);

• Has to be highly reliable;

• Has to learn and adapt from the environment to perform its tasks

• The planning cannot be done beforehand due to the unknown.

Automatic VS Autonomous

AUTOMATIC systems• Can perform well-defined tasks without

human / operator intervention

Sense Plan Act


Networking & Collaboration

Monitoring &

Diagnosis

Sensing & Perception

Learning & Adaptation

Planning & Decision

Monitoring & Diagnosis of the internal state, reconfiguration if necessary. Ability of working with degraded performance.

Sensing & Perceptionability of interpreting sensor data to plan/replan and interpret the environment.

Networking & Collaborationability of finding its own role in a group mission

Architecture Planning & Decisionability to define an high level plan and make deliberate choices.

Learning & Interpretationability of learning from the past events, interpreting cause-effect relationships


Levels of autonomy as defined by the UninhabitedCombat Air Vehicle Program

Autonomous Vehicles in Support of Naval Operations, http://www.nap.edu/catalog/11379.html

Level 1 (Manual Operation)• The human operator directs and controls all mission functions.• The vehicle still flies autonomously.

Level 2 (Management by Consent)• The system automatically recommends actions for selected functions.• The system prompts the operator at key points for information or decisions.• Many of today’s autonomous vehicles operate at this level.

Level 3 (Management by Exception)• The system automatically executes mission-related functions when response

times are too short for operator intervention.• The operator is alerted to function progress.• The operator may override or alter parameters and cancel or redirect actions

within defined time lines.• Exceptions are brought to the operator’s attention for decisions.

Level 4 (Fully Autonomous)• The system automatically executes mission-related functions when response

times are too short for operator intervention.• The operator is alerted to function progress.


Will the operator be excluded by the control loop?


Enabling Technologies• Information and communication

technology• Nano technology• Bio technology• Material technology• Integration of disciplines

and technologies• Multi-scale and distributed

systems for sensing and actuation: Micro to macro (M2M)

• …..

Research for disruptive game changing technology beyond imagination…..


Project 3: Autonomous Unmanned Vehicle Systems

Project manager

Prof. Tor Arne JohansenDepartment of Eng. CyberneticsAMOS

How to develop and use collective intelligence among robots in air, sea surface and underwater for ocean mapping and monitoring?


Project 4: Autonomous Underwater Robotics for Mapping, Monitoring and Intervention

Project manager

Prof. Kristin Y. PettersenDepartment of Eng. CyberneticsAMOS

How to make underwater robots with endurance and propulsion capabilities as marine species?


Project 5: Autonomous Aerial Systems for Marine Monitoring and Data Collection

Project manager

Prof. Thor I. FossenDepartment of Eng. CyberneticsAMOS

How to ramp up monitoring coverage 10 times with a cost of 1/10?


Project 7: Autonomous Marine Operations in Extreme Seas, Violent Water-Structure Interactions, Deep Waters and Arctic

Project manager

Prof. Asgeir J. SørensenDepartment of Marine TechnologyAMOS

How to reduce use of surface vessels with 80% in offshore oil and gas operations?

How to operate at any weather condition and offshore site without increasing cost?


Values created by AMOS• Setting agenda for research, education and

innovations on important national areas• Enabling research cooperation between

NTNU, SINTEF Group, Statoil, DNV GL, national and international partners

• Provide top qualified MSc and PhD candidates for industry and academia

• Publications in internationally leading journals and conferences

• Dissemination and knowledge transfer to industry through candidates, research institutes, and direct collaboration

• Accelerate innovations and spin-offs from NTNU and partners

The Norwegian “Silicon Valley” is the blue economy…


AMOS School of Innovation …

• Introduction, culture building, speed dating,..

• Seminars• Pitching• Business

recognition • Clustering• Company

presentations• Tailored made

courses• Screening of spin-

off candidates

Step 1

• Involve TTO• Business

development• Meet investors, IN,

NRC,..• International

cooperation• Establish AMOS

Fund?• Company spin-offs• Innovation Centre

Gløshaugen

Step 2

Step 3

Step 4

NB: This is not a linear process!


Thanks for the attention

Documents

Autonomous marine operations and systems in the · PDF file Centrefor Autonomous Marine Operations and Systems -AMOS 1 Autonomous marine operations and systems in the Arctic Professor