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Universitat de GironaComputer Vision and Robotics Group
Presented by: Dr. Pere Ridao
An Introduction to Applied Underwater Robotics
Robtica submarina
Anlisi dimatge
Percepci 3D
Visi submarina
Hardware en temps real
VICOROB Research Team
CIRS: Research Center in Underwater Robotics
Conclusion
Introduction
Applications
ICTINEUAUV, a research testbed
Navigation & Mapping
Future Work
3
Introduction
4
OCEANS Exploration 71 % earth surface is covered by water
37 % of the populations lives at less than 100 km form the coast
Oceans are a source of food and resources
Oceans play an important role in the clima
Manned Submersibles
ROVs AUVs
Technology
5
155 m
308 m
600 m
6000 m
10,911 m
Detph vs Technology
Introduction
Introduction: Marine Robots
ASC
IAUV
Survey AUV
Hovering AUV
ROV
Glider Hybrid ROV/AUV
ASCASCASC
IAUVIAUV
Survey AUV
Hovering AUV
ROROV V Survey
GlGlididererd Hybriiybb
ROV//AUVOV//A
CIRS-UdG Robots
1995 2001 2005 2006 2010
Applications
Industrial Scientific
Introduction: UdG Robot Prototypes
Conclusion
Introduction
Applications
ICTINEUAUV, a research testbed
Navigation & Mapping
Future Work
8
Pasteral dam
Objective: Execute an inspection of a dam wall to search for cracks or other damages on the concrete.
[P. Ridao et al., JFR10]
9
Applications: Dam Inspection
Pasteral dam Pasteral dam
[P. Ridao et al., JFR10]
10
Applications: Dam Inspection
Mequinenza dam
Objective: Providing visual validation for a sonar-based system developed to detect zebra mussel colonies.
[P. Ridao et al., WPDC10]
11
Applications: Habitat Mapping
Mequinenza dam
[P. Ridao et al., WPDC10]
12
Applications: Habitat Mapping
Dive 1 Dive 2
Dive 4
Dive 3
AZORES Workshop
FREESUBNET IN COOPERATION WITH FREESUBNET RTN NETWORK
Applications: Seafloor Mapping
Dive 4
Dive 3
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AZORES Workshop
FREESUBNET IN COOPERATION WITH FREESUBNET RTN NETWORK
20 m
20 m
5 m 5 m
Dive 4
Applications: Seafloor Mapping
[Escartin et al., GGG08]
Applications: Multimodal Mapping
Multimodal Maps
Image Mosaic & Bathymetry registration
Eiffel Tower hydrothermal vent. Data from IFREMER
Very Large Maps
20.000 images mosaic (6 days of ROV survey)
Lucky Strike Hydrothermal Vent site Data from WHOI 15
[Nicosivici et al. OCEANS08]
Applications: Micro-Bathymetry & 3D Mosaicing
3D Mosaics
16
Conclusion
Introduction
Applications
ICTINEUAUV, a research testbed
Navigation & Mapping
Future Work
17
How did it start ... (2006)
ICTINEUAUV: A bit of history
18
[D. Ribas et al., ICRA07]
How did it continue... (2006)
ICTINEUAUV: A bit of history
Pass the Gate Score the Cross
Hit the target Recover
4 Phases
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There are other ICTINEUS ...
Breaking the Surface 2009
ICTINEUAUV: A bit of history
Narcs Monturiol 1819-1885
ICTINEU II, Model Barcelona harbour
ICTINEU3, Manned Submersible under
development
ICTINEUAUV, to pay homage to Narcs
Monturiol
20
The Ictineu AUV
Characteristics
Open frame design
Small form factor (74 x 46.5 x 52.4 cm)
Lightweight (52 Kg)
Complete sensor suite
ROV/AUV
ICTINEUAUV: The Robot
21
The Ictineu AUV
Teth
ered
B
uoy
Unt
hete
red
ICTINEUAUV: The Robot
22
The Ictineu AUV
Pressure vessels
Power module (2 sealed 12V 12Ah lead acid batteries)
Computer module (PC104 and Mini-ITX computers)
23
ICTINEUAUV: The Robot
The Ictineu AUV
Thrusters
2 vertical thrusters
4 horizontal thrusters
Motion controlled in 4 DoF (surge, sway, heave and yaw)
24
ICTINEUAUV: The Robot
The Ictineu AUV
Forward-looking color camera
Downward-looking b&w camera
Cameras
DVL (Doppler Velocity Log)
3D velocities (bottom/water)
Pressure
Range
ICTINEUAUV: The Robot
The Ictineu AUV
AHRS
Heading, pitch, roll and heave acceleration.
Fibre optic gyro
Heading with low drift rate
ICTINEUAUV: The Robot
Generation of acoustic images of the surroundings
360 scans around the vehicle
Maximum range of 100 m
The Ictineu AUV
MSIS (Mechanically Scanned Imaging Sonar)
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ICTINEUAUV: The Robot
Vehicle positioning
Acoustic modem
The Ictineu AUV
USBL transponder
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ICTINEUAUV: The Robot
[Palomeras et al. MCMC09]
ICTINEUAUV: The Software Architecture
Software objects that dialog with the hardware
Two types:
Sensor objects
Actuator objects
Robot interface
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Navigator object: Estimate the position and velocity of the robot (EKF) Obstacle Detector: Determine the position of obstacles (wall, bottom, )
Perception module
[Palomeras et al. MCMC09]
30
ICTINEUAUV: The Software Architecture
Receives sensor inputs and sends command outputs to the actuators. Behaviours:
GoTo WallInspection Distance Heading Start/Stop Camera Check Water Check Temperature and Pressure
Control module
[Palomeras et al. MCMC09]
31
ICTINEUAUV: The Software Architecture
Defining the task execution flow to fulfill a mission
Mission control
[Palomeras et al. MCMC09]
32
ICTINEUAUV: The Software Architecture
Conclusion
Introduction
Applications
ICTINEUAUV, a research testbed
Navigation & Mapping
Future Work
33
Fundamental Problems in Underwater Robotics...
What path should I follow?
Where am I? Where am I?Where am I?Navigation
I f ll ?I follow?Path Planning
Where are the amphoras? amphoras?amphoras? Mapping
How should I steer To follow the desired
path
Control
What force should I Apply to achieve the
desired speed?
Guidance
Breaking the Surface 2009
Navigation & Mapping
Map Robot Pose Environment
Localization Algorithms
Mapping Algorithms
SLAM: Simultaneous Localization And Mapping
Navigation & Mapping:
The Navigation Problem
NNavigation: Estimate the position, orientation and velocity of a vehicle
From Gade 2008
North Pole {E} {N} {L} {B}
Origin at the centre of the earth. Earth fixed. Origin at P=[l, ] on the earth surface. Plane XY tg to earth surface. Axis pointing North-East-Down Same origine than N. Rotated wrt to zN a certain angle to avoid the singularity in the pole. Vehicle attached frame
xb
yb zb
B
Navigation & Mapping:
Inertial Navigation Systems
Navigation: Estimate the position, orientation and velocity of a vehicle
Inertial Navigation Systems
Inertial sensors are used for the navigation.
3 Accelerometers are used for the linear motion estimation.
3 Gyroscopes are used for the angular motion estimation.
The sensors are expensive and require an accurate calibration.
The position estimate drifts over time.
NNavigation: Estimate the position, orientation and velocity of a vehicle
Inertial Navigation Systems
Early INS were based on gyro-stabilized gimbaled platforms
Strapdown systems avoid moving parts using virtual gyro-stabilization techniques
Measure acceleration & angular velocity. Computer linear velocity, position and attitude.
Navigation & Mapping:
Inertial Navigation Systems
Navigation: Estimate the position, orientation and velocity of a vehicle
Inertial Navigation Systems (Strapdown)
+!122#
gravitationIB IB B IB
Ff a g a
m
BIB Can be measured using a triad acc.
DLc
Sagnac effect (1925)
Due to the rotation the light path is longer cw than acw.
The phase delay is proportional to the
Navigation & Mapping:
Inertial Navigation Systems
NNavigation: Estimate the position, orientation and velocity of a vehicle
Inertial Navigation Systems (Strapd