AUV Design: Intelligent Vehicle using Sensor Fusion Control Scheme

Abstract

In recent past, large physical changes has been observed
on earth and sea due to the drastic change in the global
environmental conditions. These changes has increased
the sea water level and created the alarming conditions for
the humans living near the coastal areas. The underwater
robot can solve such challenges (Underwater) precisely and
accurately without intervene of human operator. Such vehicles
are performing a variety of tasks in subsea, predominantly in
the offshore oil and gas industry, civil engineering and marine
sciences etc. Apart from these developments, under water
remote-sensing, navigation, image processing has also seen
a large growth in terms of software’s and processing power.
Many ROV are suffering from large power backup, accurate
object/target identification etc due to the failure of sensory
information. A new underwater autonomous system with
suitable mechanical constraints, kinematic constraints has
been designed. The designed ROV can take decisions under
water using artificial intelligence (particularly using Sensor
Fusion). The designed schematics with various components
along with simulation results of object identification are hereby
tried to be concluded.

Full text

36 In t e r n a t I o n a l Jo u r n a l o f el e c t r o n I c s & co m m u n I c a t I o n te c h n o l o g y
IJECT Vo l . 2, Is s u E 3, sEpT. 2011 ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print)
www.iject.org
Abstract
In recent past, large physical changes has been observed
on earth and sea due to the drastic change in the global
environmental conditions. These changes has increased
the sea water level and created the alarming conditions for
the humans living near the coastal areas. The underwater
robot can solve such challenges (Underwater) precisely and
accurately without intervene of human operator. Such vehicles
are performing a variety of tasks in subsea, predominantly in
the offshore oil and gas industry, civil engineering and marine
sciences etc. Apart from these developments, under water
remote-sensing, navigation, image processing has also seen
a large growth in terms of software’s and processing power.
Many ROV are suffering from large power backup, accurate
object/target identication etc due to the failure of sensory
information. A new underwater autonomous system with
suitable mechanical constraints, kinematic constraints has
been designed. The designed ROV can take decisions under
water using articial intelligence (particularly using Sensor
Fusion). The designed schematics with various components
along with simulation results of object identication are hereby
tried to be concluded.
Keywords
Sensor fusion, underwater robot, ROV, articial intelligence
I. Introduction
Field robotic is concerned with the development of robotic tools
for non-accessible and often dangerous environments, either
on or under land, air or sea. The goal of this eld is to develop
a system that can be used to facilitate work in a real world
domain. Automatic underwater robotic vehicles are currently
receiving a considerable amount of attention around the world,
as they allow all to explore the work in the area which is, beyond
our reach. These vehicles will now have signicant importance
in environment control and monitoring in aquatic agriculture
and the utilization of offshore resources. Clearly the type of
task that can be performed by these robots will dictate their
own conguration.
Most of the ROVs serve oil and gas companies and the rest of the
ROVs maintain subsea telecom cables, aid scientic research,
and mine for diamonds. Most of the offshore operations need
just a few robots for construction and maintenance for laying
cables, operating valves, and anchoring equipment, among
other tasks. Some robots are being developed for carrying the
payloads [10-11].
As companies expand operations with deeper wells and
horizontal drilling, more equipment with complex operations
needed at the sea oor and this will require sophisticated
technology to run. This includes more sophisticated robots will
be needed to do more varied tasks and in greater proportion.
And with so many ROVs working in such close quarters,
mishaps are more likely. In early June, two ROVs collided,
dislodging a tube inserted into a riser pipe. But experts think
this record could be improved. The solution probably won’t
involve engineering new hardware but rather developing more
sophisticated software.
ROVs make mistakes most often because their human pilots’
do. As there is no tactile feedback, no depth perception, no
audio feedback of what’s going on down there. To help eliminate
human error, we are developing computer software to automate
some of the standard things that ROVs do, like testing a rig’s
blowout preventer. Our automation techniques improve not only
the time that it takes to do these tasks but also the quality of
the results [1].
Automating of ROVs is done for rening their awareness about
the surroundings, this feature of the robots might be useful
for the robots to navigate the cables and moving gear in the
gulf.
II. Mechanical Design
The objective of the vehicle is, to monitor the sea parameters
and to navigate through the ocean. The proposed robot will
consists of six modules with mechanical structure. As we did
research upon the physics of motion, hydrodynamics of marine
life like shes, cephalopods, whales, tortoises and many more
,we were able to categories the type of propulsion systems
into two.
1. Jet propulsion
2. Tail propulsion
All the cephalopods move by jet propulsion technique [2]
whereas shes move by tail propulsion technique. Both the
techniques have their own advantages and disadvantages. Jet
propulsion technique is an energy consuming way to travelling
here and there compared to tail propulsion technique. The
relative efciency of jet prolusion is less [3] than that of the
tail propulsion for relative large bodies. Tail propulsion are very
useful to maintain the steady velocity whereas jet propulsion is
basically useful for stop-n-start aggressive motions. They are
basically used for providing bursts of high speeds.
Because of individual advantages of tail propulsion and jet
propulsion system [3-4] in context to navigation leads to our idea
for submarine. We are used hybrid tail propulsion system.
A. Technical Details
In this design there are six ns, one thruster, one buoyancy
adjust mechanism.
1. Fins are basically used for forward linear motion, left turn,
right turn, up turn, down turn.
2. Thruster is basically used for sudden backward push, and
sudden forward push in emergencies.
3. Buoyancy adjusts mechanism basically used to adjust net
weight of the submarine and also used for the vertical
linear motions.
Fins are actuated with the help of Ironless rotor low inertia dc
servo motors of following specs:
AUV Design: Intelligent Vehicle using
Sensor Fusion Control Scheme
1Sachin Sharma, 2Prince Khurana, 3Raghav Nagpal, 4Varun Katha
1,2,3Dept. of Instrumentation & Control Engg., Dr. B. R. Ambedkar National Institute of Tech., Jalandhar, India
4Dept. of Mechanical Engineering, Dr. B. R. Ambedkar National Institute of Tech., Jalandhar, India

In t e r n a t I o n a l Jo u r n a l o f el e c t r o n I c s & co m m u n I c a t I o n te c h n o l o g y 37
IJECT Vo l . 2, Is s u E 3, sEpT. 2011
ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print)
www.iject.org
Fig. 1: Block Diagram of the Robot modules
Model no. M35
1. Load 18Ncm
2. Angle of precision 1.8 degree
3. Power up to 20watt
4. Weight 150g
5. Size 35mm (diameter)
50mm Integrated Thruster
1. power upto 100watt
2. Size 72mm(dia) *51mm
3. Weight 0.4kg
This mechanism basically adjusts the buoyant force for adjusting
the weight of the bot and for vertical motion.
This mechanism comprises of following parts:
1. One Compressed air cylinder
2. One Ballast body
3. Three Pneumatic valves
4. Tubing
Specs:
1. Capacity 0.3ltr
2. Diameter 51 mm
3. Material Aluminum6061
4. Rating 1800psi to 3000psi
5. Weight 1.5kg
Dimensions of the AUV
1. Breadth(z axis) 28cm
2. Length(x axis): 40cm
3. Height(y axis) 4cm - 4cm (adjustable)
B. Motion
As ns changes the direction of ow of water, this change in
momentum gives a push in back according to the Newton law
of motion. Single n gives upward force. But set of ns can be
operated in such a way that they can give number of motions
[5].
Linear motion that is the motion along the axis of the bot.
the set of ns can be triggered in such a way that it can do
linear momentum transfer along the axis of the bot. A very
similar motion can be obtained by triggering the ns after a
regular interval of time. Each predecessor ns with a time
interval ‘t’. This time is same between adjacent ns and x
for a particular velocity, but it varies with change in angular
velocity of ns maintain a wave motion in ns. Left and right
motion can be achieved by keeping one side ns stop & move
the other. Thruster designed to give
Fig. 2: Example of Various motions
sudden forward and backward pushes when needed in
emergencies. It consists of motor propeller assembly oriented
along the axis of the bot.
C. Final Design
Estimated weights
1. Processor unit: 2kg
2. Battery: 3kg( 4 batteries)
3. Servo motors: 1.2 kg( 6 motors)
4. Thruster: 0.5 kg
5. Air cylinder: 2kg
6. Supported mechanical parts: 3kg
7. Supported electronics: 0.8 kg
8. Weight of shell: 1.5kg
Total Estimated weight: 12kg
Fig. 3. Final ROV Design
Center of gravity and center of bouncy
Along x axis: 20.5 cm
Along y axis: 6cm
Along z axis: 14cm
Net weight of AUV in water with ballast body lled with water:
0.5 kg
Volume of ballast body = 40cm*12cm*6.25cm
Net weight of AUV in water with ballast body lled with air:
-2.5kg

38 In t e r n a t I o n a l Jo u r n a l o f el e c t r o n I c s & co m m u n I c a t I o n te c h n o l o g y
IJECT Vo l . 2, Is s u E 3, sEpT. 2011 ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print)
www.iject.org
Centre of buoyancy:
Along x axis: 20cm
Along y axis: 7.84cm
Along z axis: 14cm
Difference between CG and CB: 1.84cm (along y axis)
Drag force:
Velocity of robot= 0.1 m/s2
Estimated drag coefcient= 0.45
Density of water= 1000kg/m3
Surface area =0.14*0.28 m2 =0.0392m2
Total drag= 0.0882N
Body Material:
We are using three types of materials in order to make the
body of the robot.
1. Carbon Fiber
2. Steel Sheet
3. Underwater Glass Sheet
Carbon ber will be used to make the main body and steel
sheet will be used to make the base plate and glass sheet will
be used in sections for the cameras.
III. Embedded system
Embedded system of the AUV is responsible for the stable
operation of AUV under the water and for its smooth motion for
the observation of ocean surface. In this unit there are mainly
two boards one is Attitude monitoring board and the other is
motor control board.
Fig. 4: Block Diagram of Attitude monitoring
Attitude monitoring board gives the information about the
orientation of the board in 3 DOF i.e. roll, pitch and yaw. This
data is calibrated by the circuit designed for the operation
and then the calibrated data is given to the central processor
where it takes the appropriate decision based on the data
available to it. Then controlling commands gave to the motor
controller board to change the speed of motors in order to
compensate the deviation from its stable position. Attitude
monitoring board consists of Accelerometer, Gyrocompass and
AVR micro controller.
We developed the algorithms so that while up and down
movement of the robot monitoring board should not interfere
with the motor controller board. Apart from this we will use
gyrocompass in conjunction with the accelerometer, for more
static results, by sensor fusion technique.
A. Sea Parameter monitoring and communication
We monitored temperature and depth, we used temperature
and depth sensor. These sensors give the calibrated data to
the central processor. The program running on processor will
store the values time by time in its database. The whole data of
the monitoring will be sent to the base station through wireless
communication [2] system after reaching to the surface.
This system receives and sent back the commands to the
base station. In this module we use 181KT - Miniature Depth
Sensor. It gives the calibrated output for both temperature
and pressure.
Fig. 5: Various modules of ROV
B. Navigation System
For the navigation system we are using camera arrays in
conjunction with the sonar, as camera alone doesn’t give the
information about the distance of the object from the vehicle.
[6] Hence with the introduction of the sonar we will get the
information of distance as well. Hence using both camera and
sonar we will have the exact information of object, regarding
its shape and distance from the vehicle.
We are making our vehicle to maintain a safe distance from
the objects. In ocean any moving object can come in the path
of the vehicle. Our vehicle can detect such object and can
take appropriate actions. It can also search for the objects of
our interest [7].
These cameras have user congurable vision settings and low
power requirements. The cameras are internally mounted,
thereby not interfering with the streamline motion of the body.
The vehicle will be capable of switching between cameras to
perform different tasks.
C. Motion control System
Motion control system includes the servo motors and their
controller board. This system is responsible for the movement of
the robot. While going upward, downward, side motions the speed
of motors should be varied accordingly and all these action will be
taken by the controller board. Servo motor controller board takes
the commands from the central processor and works accordingly.
Fig. 6. Motion control system
Servo motor controller Board
• 32 bit position, velocity and acceleration control
• Trapezoidal and velocity proling permit on-the-y
• 16 bit PID servo gains can be changed on-the-y
• Multi axis coordinated motion control support
• 2 or 3 channel encoder input, limit switch inputs
• Optional Step and Direction inputs
• May be used with DC brushless or brush-type motors
• Amplier includes over current, overvoltage, under voltage
and thermal overload protection
• 4-wire RS485 communications interface can be connect
to additional controllers (up to 32 total)
• Complete documentation and example software
available
IV. Image processing

In t e r n a t I o n a l Jo u r n a l o f el e c t r o n I c s & co m m u n I c a t I o n te c h n o l o g y 39
IJECT Vo l . 2, Is s u E 3, sEpT. 2011
ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print)
www.iject.org
Image processing technologies to trace line-like objects are
developed. In the test, lane markers were traced in real-time.
In aquatic circumstances, there exist few works concerning with
the subject. Conditions for tracking of line-like objects in the
underwater are fairly different from those in the atmosphere.
They differ from each other especially in the range of vision and
uniformity of the illumination. The range of view is much longer
than the underwater [8]. Illumination uniformity far exceeds in
case of the underwater. These all help to predict trajectory of
target objects easily after they are once caught. Stable guidance
of a vehicle based on the prediction in turn stabilizes camera’s
view and enables camera to catch the target in good position.
In the underwater, information about working circumstances
was rarely given. The extent of illumination decides the range of
view in the deep waters. Absorption and diffraction in the water
limit it [9] within 10 meters in coastal waters. Illumination by
spotlights is very inhomogeneous. The strong absorption of light
in the underwater enhances the inhomogeneity. Brightness
of illuminated region changes by the same reason if vehicles
change their altitude. Clear images cannot be obtained since
the diffraction blurs shape of objects.. ROVs and AUVs have
various factors to cause uctuation to their motion. Tidal currents
cause unpredictable uctuation of motion of tethered ROVs.
Changes of altitude, pitch and roll of vehicles change direction
and position of cables in images. Insufcient ac magnetic elds
also result in unpredictable changes of cable direction through
motion uctuation. This makes it difcult to predict direction
and position of object in the next picture exactly. So, we work
mainly in these three areas.
1. Image capturing
2. Pre-processing
3. Edge detection
V. Power and Cooling System
We are using four Customize Polymer Li-Ion Battery in order to
provide the power backup for whole system under the water.
According to our power requirement for satisfactory functioning
of the robots these batteries will be sufcient for the 3 hrs of
power backup. Due to the generation of enormous heat from
electronic circuitry, we have to make provisions of cooling in
order to avoid the failure of the system due to heat.
We are using a temperature sensor inside the main chamber
which will indicate the temperature inside the chamber. Heat
will be mainly conducted through the metallic base plate using
blow air mechanism. The speed of blower will be controlled
according to the temperature of the chamber.
VI. Conclusion
The ROV has been developed and checked in underwater.
The design is hybrid of ns and thruster for motion of vehicle,
whereas the Controlling is done threw sensor fusion of sonar
and Camera data. The vehicle has capability of self control,
object tracing and gather useful data intelligently.
References
[1] J. Hallset, “Simple visual tracking of pipelines for an
autonomous underwater vehicle”, Proc. 1991 IEEE Conf.
on Robotics and Autom., pp.2767-2772( 1991).
[2] A. J. Srensen "Structural issues in the design and operation
of marine control systems", IFAC J. Annu. Rev. Control, vol.
29, pp. 125 , 2005.
[3] D. R. Yoerger , J. G. Cooke, J. J. E. Slotine "The inuence
of thruster dynamics on underwater vehicle behavior and
their incorporation into control system design", IEEE J.
Ocean. Eng., vol. 15, p.167 , 1991.
[4] A. J. Healey , S. M. Rock , S. Cody , D. Miles, J. P. Brown
"Toward an improved understanding of thruster dynamics
for underwater vehicles", IEEE J. Ocean. Eng., vol. 29,
p.354 , 1995. .
[5] P. Ananthakrishnan, “Three-dimensional wavebody
interactions in a viscous uid,” Proc. 7th Int. Offshore l3
Polar Eng. Conf., III:672-679, 1997.
[6] F. Dellaert, D. Fox,W. Burgard, S. Thrun, "Monte carlo
localization for mobile robots," in Proc. 1999 IEEE Intl.
Conf. on Robotics and Automation (ICRA), 1999.
[7] “Interface control document”. Navstar GPS Space Segment
(Navigation User Interfaces), 2000.
[8] F. Dellaert, W. Burgard, D. Fox, S. Thrun, "Using the
condensation algorithm for robust, vision-based mobile
robot localization," in IEEE Computer Society Conf. on
Computer Vision and Pattern Recognition (CVPR'99),
1999, pp. 2588-2596.
[9] KashifIqbal, Rosalina Abdul Salam, Azam Osman an,
Abdullah ZawawiTalib, “Underwater Image Enhancement
Using an Integrated Colour Model”, IAENG International
Journal of Computer Science, 34:2, IJCS_34_2_12,
2007.
[10] Bob Anderson, Jon Crowell,” Workhorse AUV – A cost-
sensible new autonomous underwater vehicle for surveys/
Soundings, search & Rescue, and Research”, oceanserver
technology, Inc., 2009.
[11] I.Vasilescu, C.Detweiler, Doniec,D.Gurdan,” Amour V :
A Hovering Energy Efcient Underwater Robot Capable
of Dynamic Payloads”, Computer Science and Articial
Intelligence Lab, Massachusetts Institute of Technology,pp.
1-29, 2010.
Sachin Sharma was born at Dadri,
Uttar Pradesh, India on 5 July, 1987.
He is pursuing his M.tech degree
in Instrumentation and Control
Engineering from NIT Jalandhar. He
did his B.tech in Electronics and
Communication Engineering from
GLA Institute of Technology, Mathura.
He has published several papers in
International conferences. His area
of interest includes signal processing,
neural networks and system designing.