solar powdered autonomous vehicle

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a project report on solar powered autonomous vehicle

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CONTENTS

DEC- 2015

CONTENTS
LIST OF FIGURES ....................................................................................................................2
LIST OF TABLES ......................................................................................................................3
ABSTRACT ...............................................................................................................................4
CHAPTER 1: INTRODUCTION ................................................................................................5
1)

Self-maintenance ......................................................................................................................... 5

2)

Sensing the environment ............................................................................................................. 5

3)

Task performance ........................................................................................................................ 6

4)

Autonomous navigation ............................................................................................................... 6

CHAPTER 2: LITERATURE SURVEY .....................................................................................7
CHAPTER 3: COMPONENTS USED ...................................................................................... 11
1)

SOLAR PANELS ........................................................................................................................... 11

2)

PLASTIC CHASSIS ........................................................................................................................ 12

3)

DC Motors :................................................................................................................................ 13

4)

WHEELS ..................................................................................................................................... 14

5)

BATTERY .................................................................................................................................... 15

6)

MICROCONTROLLER BOARD : ARDUINO MEGA ......................................................................... 16

7)

ULTRASONIC SENSOR HC-SR04................................................................................................... 18

8)

SERVO MOTOR - S3003 .............................................................................................................. 19

9)

ARDUINO MOTOR SHIELD .......................................................................................................... 21

CHAPTER 4: HARDWARE IMPLENTATION ....................................................................... 23
CHAPTER 5: SOLAR IRRADIATION .................................................................................... 30
CHAPTER 6: CALCULATIONS.............................................................................................. 31
CHAPTER 7: RESULTS .......................................................................................................... 33
CHAPTER 8: CONCLUSION AND FUTURE WORK ............................................................ 38
REFERENCES ......................................................................................................................... 39

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LIST OF FIGURES

DEC- 2015

LIST OF FIGURES
Figure 1 SOLAR PANELS ................................................................................................................... 11
Figure 2 PLASTIC CHASSIS................................................................................................................ 12
Figure 3 DC MOTORS.......................................................................................................................... 13
Figure 4 WHEELS ................................................................................................................................ 14
Figure 5 BATTERY .............................................................................................................................. 15
Figure 6 ARDUINO MEGA .................................................................................................................. 16
Figure 7 HARDWARE DESIGN ........................................................................................................... 23
Figure 8 SIDE VIEW ............................................................................................................................ 23
Figure 9 SENSOR PLACEMENT ......................................................................................................... 24
Figure 10 FRONT VIEW OF ROVER ................................................................................................... 25
Figure 11 SIDE VIEW OF ROVER ....................................................................................................... 25
Figure 12 CHARGING AND DISCHARGING SYSTEM ..................................................................... 26
Figure 13 ALGORITHM FOR BATTERY SELECTION ...................................................................... 27
Figure 14 BATTERY SWITCHING SYSTEM ..................................................................................... 28
Figure 15 RESULT 1............................................................................................................................. 33
Figure 16 RESULT 2............................................................................................................................. 34
Figure 17 RESULT 3............................................................................................................................. 35
Figure 18 RESULT 4............................................................................................................................. 36
Figure 19 RESULT 5............................................................................................................................. 37

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LIST OF TABLES

DEC- 2015

LIST OF TABLES
Table 1 TECHNICAL SPECIFICATION OF ARDUINO MEGA ......................................................... 17
Table 2 MONTHLY SOLAR IRRADIATION IN BANGALORE ........................................................ 30

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ABSTRACT

DEC- 2015

ABSTRACT
Autonomous vehicle navigation has become an important research area in various applications of
motion path planning, localization, and mapping. For an autonomous robot, obstacle detection,
collision avoidance and depth prediction for path planning in a solar powered autonomous
vehicle are crucial tasks for the success of the robot.
One of the most important capabilities expected from an autonomous vehicle is avoiding
collision with obstacles in its path. For this purpose, autonomous vehicle must be able to perform
an emergency maneuver as soon as the obstacle is detected. Here we are designing an
autonomous vehicle with multiple sensors to detect obstacles from different directions and avoid
collision. The height and width of an obstacle is estimate using sensors. Depth prediction is also
implemented. A microcontroller is fitted on a PCB board which is used to control the entire
system. The autonomous vehicle is fitted with four wheels for movement, solar panels as a
source of power supply.
The design implemented in this paper proposes the use of two separate battery units working
alternately, thus one of the batteries receives the charge current from the Photovoltaic (PV)
system while the other provides energy to the robotic vehicle. Unlike other designs, in a
conventional system the power source is used to recharge a single battery. The robot can only be
used when the battery is fully charged and must remain idle during the recharging. The battery
charge controller is also useful, when the both the batteries are unable to provide the current to
the vehicle. It will make the direct connection between the load and PV system. The sensor data
collected by the sensors is used to maneuver the vehicle. This vehicle is expected to explore any
alien environment and take decisions autonomously.

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INTRODUCTION

DEC- 2015

CHAPTER 1: INTRODUCTION
An autonomous robot is a Skynet that performs behaviors or tasks with a high degree of
autonomy, which is particularly desirable in fields such as space exploration, household
maintenance (such as cleaning), waste water treatment and delivering goods and services.
A fully autonomous robot can:





Gain information about the environment
Work for an extended period without human intervention
Move either all or part of itself throughout its operating environment without human
assistance
Avoid situations that are harmful to people, property, or itself unless those are part of its
design specifications

An autonomous robot may also learn or gain new knowledge like adjusting for new methods of
accomplishing its tasks or adapting to changing surroundings. Like other machines, autonomous
robots still require regular maintenance.

1) Self-maintenance
The first requirement for complete physical autonomy is the ability for a robot to take care of
itself. Many of the battery-powered robots on the market today can find and connect to a
charging station, and some toys like Sony's Aibo are capable of self-docking to charge their
batteries.
Self-maintenance is based on "proprioception", or sensing one's own internal status. In the
battery charging example, the robot can tell proprioceptively that its batteries are low and it then
seeks the charger. Another common proprioceptive sensor is for heat monitoring. Increased
proprioception will be required for robots to work autonomously near people and in harsh
environments. Common proprioceptive sensors include thermal, optical, and haptic sensing, as
well as the Hall Effect (electric).

2) Sensing the environment
Exteroception is sensing things about the environment. Autonomous robots must have a range of
environmental sensors to perform their task and stay out of trouble.


Common exteroceptive sensors include the electromagnetic spectrum, sound, touch,
chemical (smell, odor), temperature, range to various objects, and altitude.
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INTRODUCTION

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Some robotic lawn mowers will adapt their programming by detecting the speed in which grass
grows as needed to maintain a perfectly cut lawn, and some vacuum cleaning robots have dirt
detectors that sense how much dirt is being picked up and use this information to tell them to
stay in one area longer.

3) Task performance
The next step in autonomous behaviour is to actually perform a physical task. A new area
showing commercial promise is domestic robots, with a flood of small vacuuming robots
beginning with iRobot and Electrolux in 2002. While the level of intelligence is not high in these
systems, they navigate over wide areas and pilot in tight situations around homes using contact
and non-contact sensors. Both of these robots use proprietary algorithms to increase coverage
over simple random bounce.
The next level of autonomous task performance requires a robot to perform conditional tasks.
For instance, security robots can be programmed to detect intruders and respond in a particular
way depending upon where the intruder is.
4) Autonomous navigation

For a robot to associate behaviors with a place (localization) requires it to know where it is and
to be able to navigate point-to-point. Such navigation began with wire-guidance in the 1970s and
progressed in the early 2000s to beacon-based triangulation. Current commercial robots
autonomously navigate based on sensing natural features. The first commercial robots to achieve
this were Pyxus' HelpMate hospital robot and the CyberMotion guard robot, both designed by
robotics pioneers in the 1980s. These robots originally used manually created CAD floor plans,
sonar sensing and wall-following variations to navigate buildings. The next generation, such as
Mobile Robots' PatrolBot and autonomous wheelchair, both introduced in 2004, have the ability
to create their own laser-based maps of a building and to navigate open areas as well as
corridors. Their control system changes its path on the fly if something blocks the way
At first, autonomous navigation was based on planar sensors, such as laser range-finders, that
can only sense at one level. The most advanced systems now fuse information from various
sensors for both localization (position) and navigation. Systems such as Motivity can rely on
different sensors in different areas, depending upon which provides the most reliable data at the
time, and can re-map autonomously.

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LITERATURE SURVEY

DEC-2015

CHAPTER 2: LITERATURE SURVEY
1) “Embedded System Based Power Management for Battery Operating
Robotic Vehicle”,

T.Mathews and V. Gopi, 2014 International Conference on Circuit, Power
and Computing Technologies [ICCPCT].

This paper is about a robotic vehicle aims on the design of efficient charging system of batteries
by means of tracked solar panels. The main attraction of this paper is the design concept of the
charging and discharging cycles of the batteries based on the PIC micro-controller. The efficient
charging system concept is designed on a PIC micro-controller. The energy system consists of
two batteries and are, one for charging independently from the solar panel and the other battery
gives the energy for the Robotic vehicle. By implementing this method the efficient power
management becomes possible.
The switching time between the batteries can also be reduced by control algorithm programmed
in the PIC micro-controller. Since only one battery is charging at a time, the size of solar panel
also can be minimized. The sensors attached to the battery system will monitor the battery’s
external parameters and thus the life time of battery can be increased based on the sensors
readings. The readings from the vehicle will get in the remote PC.This paper focuses to improve
the operation of a fore mentioned robotic exploration rovers with intelligent purposes and also
with the power system operations. The tool used in this proposed system is Visual Basic for
indicating the external parameters like temperature, humidity for monitoring the battery external
parameters. Visual Basic also gives the light sensors readings and provides Graphical User
Interface (GUI). VB also includes the control switches for the vehicle movement control. The
system reduces the size of the PV panels by charging one battery at a time and other will be
connected to the load.

2) “Autonomous Vehicle Guidance System with Infrastructure”,

Kyung-Bok
Sung, Kyoung-Wook Min, Ju-Wan Kim, and Jung-Dan Choi, Signal Processing and Communication
Systems (ICSPCS), 2013 7th International Conference.

This paper presents system architecture for autonomous vehicle guidance system with
infrastructure. First, an example service of autonomous vehicle guidance with infrastructure is
described. In the service, vehicle drives autonomously based on vehicle mounted sensors. But in
special area, the vehicle gets sensor data from infrastructure for safety and accuracy.
Second, a design is proposed for system architecture for autonomous vehicle guidance with
infrastructure. Hardware for autonomous driving is designed with minimal vehicle sensors and
software blocks are proposed to process sensor data from infrastructure system and vehicle
sensors. Finally, the test system is implemented. However, when trying to make a vehicle
autonomously travel to a predefined destination, there are several challenges to be overcome.
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LITERATURE SURVEY

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The first one is to know where the vehicle is. The second one is to detect surrounding
environments to avoid a collision. The third is to detect signs on the road, such as lanes,
crosswalks, and speed bumps, particularly in a rural environment. This paper describes an
autonomous vehicle guidance system with infrastructure sensors. The vehicle is modified for
autonomous driving and has sensors for short range obstacle detection. The vehicle also has a
communication device for communicating with infrastructure sensors. The infrastructure sensors
detect obstacles in the special area and send the information to the vehicle.

3) “Collision Avoidance Maneuver for an Autonomous Vehicle”,

By M. Durali,

G. Amini Javid and A. Kasaiezadeh, 2006. 9th IEEE International Workshop.

One of the most important capabilities expected from an autonomous vehicle is avoiding
collision with obstacles in its path. For this purpose, autonomous vehicle must be able to perform
an emergency maneuver as soon as the obstacle is detected. This paper presents a method for
designing and performing an emergency maneuver in order to avoid collision with a fixed or
moving obstacle in the path. A sinusoidal or exponential trajectory, which is a function of the
relative distance between vehicle and obstacle, is designed as the desired trajectory for lateral
motion of the vehicle. A sliding mode controller is designed in order to guarantee that the vehicle
tracks that desired trajectory. The method does not have computational difficulties and is
appropriate for real time implementations.
In this paper, we propose a method for overtaking and avoiding collision with a fixed or moving
obstacle. First, a dynamic model of the autonomous vehicle is presented. This model will be used
in designing a controller. Then, desired trajectories to be followed by the autonomous vehicle in
order to avoid collision are proposed. These trajectories are functions of the relative distance of
the autonomous vehicle to the obstacle. As a result, the obstacle can have any arbitrary
longitudinal velocity profile. Next, a sliding mode controller for controlling lateral motion of the
autonomous vehicle, in order to track the desired trajectory, is designed. Finally, the results of
simulation of vehicle maneuvers are presented.

4) “Japanese Rover Test-bed for Lunar Exploration”, By Takashi Kubota, Yasuharu
Kunii, Yoji Kuroda, Masatsygu Otsuki, in Proc. Int. Symp. Artif. Intell., Robot. Automat.Space,
no.77, 2008

Lunar exploration missions including landser and rovers are earnestly under studying in Japan.
One of main missions for lunar robotics exploration is to demonstrate the technologies for lunar
or planetary surface exploration. They will cover landing technology and surface exploration
rover technology. Lunar geologic survey will be also performed for utilization and scientific
investigation of the moon. The working group has been conducting the feasibility study of
advanced technologies for lunar robotics exploration. Unmanned mobile robots are expected for
surface exploration of the moon, because mobile robots can travel safely over a long distance.
This paper presents system overviews of developed test-bed roves, guidance and navigation
schemes, smart manipulators and some experimental results.
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5) “Emergency Maneuver Library – Ensuring Safe Navigation
In Partially Known Environments”,

By Sankalp Arora, Sanjiban Choudhury, Daniel Althoff
and Sebastian Scherer, 2015 IEEE International Conference on Robotics and Automation (ICRA)

Autonomous mobile robots are required to operate in partially known and unstructured
environments. It is imperative to guarantee safety of such systems for their successful
deployment. Current state of the art does not fully exploit the sensor and dynamic capabilities of
a robot. Also, given the non-holonomic systems with non-linear dynamic constraints, it becomes
computationally infeasible to find an optimal solution if the full dynamics are to be exploited
online. In this paper they have presented an online algorithm to guarantee the safety of the robot
through an emergency maneuver library. The maneuvers in the emergency maneuver library are
optimized such that the probability of finding an emergency maneuver that lies in the known
obstacle free space is maximized. It is proved that the related trajectory set diversity problem is
monotonic and submodular which enables one to develop an efficient trajectory set generation
algorithm with bounded sub-optimality. An off-line computed trajectory set that exploits the full
dynamics of the robot and the known obstacle-free region s generated. It is tested and validated,
the algorithm on a full-size autonomous helicopter flying up to speeds of 56m/s in partiallyknown environments. Results from 4 months of flight testing where the helicopter has been
avoiding trees, performing autonomous landing, avoiding mountains are presented while being
guaranteed safe.

6) “Mult-Sensor Input Path Planning For an Autonomous Ground Vehicle”
By Nathir A. Rawashdeh and Hudhaifa T. Jasim, Proceedings of the 9th International Symposium
on Mechatronics and its Applications (ISMA13), Amman, Jordan, April 9-11, 2013

Autonomous Unmanned Ground Vehicles (UGV’s) are mobile platforms that serve a wide range
of specialized applications in urban, military, domestic, and industrial settings. UGV’s can be
remotely operated or autonomous and usually include a variety of sensors and manipulators that
are used to solve specific investigation tasks. They also include sensory input for use in
autonomous navigation algorithms. For example, radio activity or explosive sensors can help the
remote assessment of a dangerous area. In the case of autonomous navigation, a UGV usually
employs Light Detection and Ranging (LIDAR) sensors a. k. a. laser range finders, ultra sonic
sensors, cameras, and Global Positioning System (GPS) receivers to avoid obstacles and follow a
set of GPS waypoints that define a path for the UGV to cover. This paper presents the
development of autonomous path planning in a UGV that uses various sensors including, a laser
range finder, a digital compass, a GPS receiver, and computer vision. The sensor data is fused in
a ―cost matrix‖ that assigns positive numerical values to obstacles detected using the various
sensors. Negative value contributions are added to the cost matrix is areas corresponding to the
desired heading dictated by GPS waypoint navigation. A cost function is implemented by adding
cost matrix values over several possible paths crossing the matrix, causing the lowest-cost path
to be selected as the UGV’s next heading. The algorithm was tested on a grassy path with white
lines defining an allowable path that includes various physical obstacles.
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LITERATURE SURVEY

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7) “Sojourner mars rover thermal performance”,

By H. J. Eisen, L. C.Wen, G.
Hickey, and D. F. Braun, presented at the 28th Int. Conf. on Environmental Systems, Danvers, MA,
1998

Sojourner rover landed on the surface of mars on july4, 1997 as a part of Mars Pathfinder
Mission. The mission lasted almost three months during which thermal design of the Rover was
tested. This paper summarizes the Rover’s design and performance as well as post mission
model correlation.

8) “Autonomy for mars rovers: Past, present, and future,” By M. Bajracharya, M.
W. Maimone, and D. Helmick, Published in: Computer (Volume:41 , Issue: 12 ),
DOI:10.1109/MC.2008.479

Since the 1960’s there have been efforts world-wide to develop robotic mobile vehicles for
traversing planetary surfaces. Developments in mobility, navigation, power, computation, and
thermal control are discussed in this paper .

9) “FIDO rover field trials as rehearsal for the NASA 2003 mars exploration
rovers mission”,

By Edward Tunstel, Terry Huntsberger, Hrand Aghazarian, Paul Backes,
Eric Baumgartner, Published in: Automation Congress, 2002 Proceedings of the 5th Biannual
World (Volume:14 )

This paper describes recent extended field trials performed using the FlDO (Field Integrated Design
& Operations) rover, an advanced NASA technology development platform and research prototype
for the next planned rover mission to Mars. Realistic physical simulation of the NASA 2003 Mars
Exploration Rovers mission was achieved through collaborative efforts of robotcists, planetary
scientists, and mission operations personnel.

10) “The K9 On-Board Rover Architecture,”

By John L. Bresina, Maria Bualat,
Michael Fair ,Richard Washington, Anne Wright, 6th Int. Symp. Artificial Intelligence, Robotics and
Automation in Space, Montreal, QC, Canada, 2001.

This paper describes the software architecture of NASA Research Center K9 rover. The goal of the
on board software architecture team was to develop a modular, flexible framework that would allow
both high- and low-level control of the K9 hardware.

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COMPONENTS USED

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CHAPTER 3: COMPONENTS USED
1) SOLAR PANELS

Figure 1 SOLAR PANELS

Specification:
No. of panels: 4
5Watts, 17Volts, 300mA, 340x215x18(mm), 0.9Kg.

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COMPONENTS USED

2)

DEC-2015

PLASTIC CHASSIS

Figure 2 PLASTIC CHASSIS

Specification:
No. of chassis: 1
406.4x406.4x100(mm), 1.1Kg

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COMPONENTS USED

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3) DC Motors :

Figure 3 DC MOTORS

Specification:
No. of dc motor: 4
100RPM, 12V, 30Kg-cm torque, No load current 60mA, Full load current 300mA, 200gram.

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4) WHEELS

Figure 4 WHEELS

Specification:
No. of wheels: 4
120mm (diameter), 60mm(width), Hole diameter 4 mm.

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5) BATTERY

Figure 5 BATTERY

Specification:
No. of battery: 2
Lithium Ion, 2000mAh, 12V, 300Am, 72x56x15(mm), 0.2Kg

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6) MICROCONTROLLER BOARD : ARDUINO MEGA

Figure 6 ARDUINO MEGA

The Arduino Mega 2560 is a microcontroller board based on the ATmega2560 . It has 54 digital
input/output pins (of which 15 can be used as PWM outputs), 16 analog inputs, 4 UARTs
(hardware serial ports), a 16 MHz crystal oscillator, a USB connection, a power jack, an ICSP
header, and a reset button. It contains everything needed to support the microcontroller. The
Arduino Mega can be powered via the USB connection or with an external power supply. The
operating voltage of arduino mega 2560 is 5v. The dc current per input and output pin is 40mA.
The ATmega2560 has 256 KB of flash memory for storing code (of which 8 KB is used for the
bootloader), 8 KB of SRAM and 4 KB of EEPROM. The Arduino Mega can be programmed
with the Arduino software , The ATmega2560 on the Arduino Mega comes preburned with a
bootloader that allows to upload new code without the use of an external hardware programmer.
It communicates using the original STK500 protocol.

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Table 1 TECHNICAL SPECIFICATION OF ARDUINO MEGA

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7) ULTRASONIC SENSOR HC-SR04

 The HC-SR04 ultrasonic sensor uses sonar to determine distance to an object like bats or
dolphins do. It offers excellent non-contact range detection with high accuracy and stable
readings in an easy-to-use package. From 2cm to 400 cm or 1‖ to 13 feet. It operation is
not affected by sunlight or black material like Sharp rangefinders are (although
acoustically soft materials like cloth can be difficult to detect). It comes complete with
ultrasonic transmitter and receiver module.
Features:
 Power Supply :+5V DC
 Working Currnt: 15mA
 Ranging Distance : 2cm – 400 cm/1" - 13ft
 Dimension: 45mm x 20mm x 15mm

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8) SERVO MOTOR - S3003

A servomotor is a rotary actuator or linear actuator that allows for precise control of angular or
linear position, velocity and acceleration. It consists of a suitable motor coupled to a sensor for
position feedback. It also requires a relatively sophisticated controller, often a dedicated module
designed specifically for use with servomotors.

Basic Information
Modulation:

Analog
4.8V:
44.0 oz-in (3.17 kg-cm)

Torque:
6.0V:
57.0 oz-in (4.10 kg-cm)
Speed:

4.8V:

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0.23 sec/60°
6.0V:
0.19 sec/60°
Weight:

1.31 oz (37.0 g)
Length:
1.57 in (39.9 mm)
Width:

Dimensions:
0.79 in (20.1 mm)
Height:
1.42 in (36.1 mm)
Gear Type:

Plastic

Rotation/Support:Bushing

Additional Specifications

Rotational Range: 180°
Pulse Cycle:

30 ms

Pulse Width:

500-3000 µs

Connector Type: J

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9) ARDUINO MOTOR SHIELD

Arduino is a great starting point for electronics, and with a motor shield it can also be a nice tidy
platform for robotics and mechatronics. Here is a design for a full-featured motor shield that will
be able to power many simple to medium-complexity projects.










2 connections for 5V 'hobby' servos connected to the Arduino.
Up to 4 bi-directional DC motors with individual 8-bit speed
Up to 2 stepper motors (unipolar or bipolar) with single coil, double coil, interleaved or
micro-stepping.
4 H-Bridges: L293D chipset provides 0.6A per bridge (1.2A peak) with thermal
shutdown protection, 4.5V to 25V
Pull down resistors keep motors disabled during power-up
Big terminal block connectors to easily hook up wires (10-22AWG) and power Arduino
reset button brought up top
2-pin terminal block to connect external power, for separate logic/motor supplies
Tested
compatible
with
Mega,
Diecimila,
&
Duemilanove

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COMPONENTS USED

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The shield contains two L293D motor drivers and one 74HC595 shift register. The shift
register expands 3 pins of the Arduino to 8 pins to control the direction for the motor
drivers. The output enable of the L293D is directly connected to PWM outputs of the
Arduino.



To increase the maximum current, the L293D allows extra chips with "piggyback".
Piggyback is soldering one or two or three extra L293D drivers on top of the L293D
drivers on the board to increase the maximum current. The L293D allows parallel
operation.



The Motor Shield is able to drive 2 servo motors, and has 8 half-bridge outputs for 2
stepper motors or 4 full H-bridge motor outputs or 8 half-bridge drivers, or a
combination.



The servo motors use the +5V of the Arduino board. The voltage regulator on the
Arduino board could get hot. To avoid this, the newer Motor Shields have connection
points for a seperate +5V for the servo motors

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CHAPTER 4: HARDWARE IMPLENTATION

Figure 7 HARDWARE DESIGN

Figure 8 SIDE VIEW
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Figure 9 SENSOR PLACEMENT

As seen in the figure, there are three sensors present in the rover. One in the front which is
connected to servo motors and can move horizontally and vertically. One at the back to detect
obstacles from behind and the last one in the front to predict depth.

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Figure 10 FRONT VIEW OF ROVER

Figure 11 SIDE VIEW OF ROVER
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Figure 12 CHARGING AND DISCHARGING SYSTEM

This diagram depicts the overall architecture of the system. As we can see the solar panels are
connected to the charge controller, which consists of the input coming from the panels, and the
batteries which are supposed to be charged. The batteries are connected to a single channel
DPDT relay board, where the battery with more charge is connected to the load and the other is
charged. The load consists of the H Bridge which controls the motors of the rover and the
Microcontroller (Arduino mega 2560). The decision as to which battery is to be selected is done
by the microcontroller. During sunny days (Good solar radiation) charge controller will charge
the batteries also provide the power to the load simultaneously. While in cloudy days (Bad solar
radiation) charge controller will provide power to the load through the battery. So, because of
these characteristics of the charge controller, we can improve and increase the life cycle of the
batteries. Charge controller is also used to prevent the batteries from over charging and reverse
current.

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Figure 13 ALGORITHM FOR BATTERY SELECTION

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Rechargeable Battery System
The design implemented in this paper proposes the use of two separate battery units working
alternately, thus one of the batteries receives the charge current from the PV system while the other
provides energy to the robotic vehicle. Unlike other designs, in a conventional system the power
source is used to recharge a single battery. The robot can only be used when the battery is fully
charged and must remain idle during the recharging. The battery charge controller is also useful,
when the both the batteries are unable to provide the current to the vehicle. It will make the direct
connection between the load and PV system.

Figure 14 BATTERY SWITCHING SYSTEM

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HARDWARE IMPLEMENTATION

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The battery switching system consists of single channel 12V DC DPDT (Double pole double
throw) relay board with break-before-make operation logic. Their function is connecting
electrically the charge and discharge paths between the batteries. The batteries are connected to
the NO (normally open) and NC (normally closed) terminal of the relay. The relay board is
controlled by microcontroller.

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SOLAR IRRADIATION

DEC-2015

CHAPTER 5: SOLAR IRRADIATION
Solar radiation is radiant energy emitted by the sun, particularly electromagnetic energy. It is
also known as short-wave radiation. Solar radiation comes in many forms, such as visible light,
radio waves, heat (infrared), x-rays, and ultraviolet rays. The sun is the earth's major energy
source and radiates its energy from a distance of 150 million kilometers, or 8.3 light minutes.
This solar radiation reaches the outside of our atmosphere with an irradiance of about 1360
Watts per square meter (W/m2). It covers the spectrum from ultraviolet, through visible, to near
infrared wavelengths. Solar radiation is very important factor for space missions. It is measured
in Sieverts (sV). Radiation Assessment Detector (RAD) is the first instrument to measure the
radiation in environment, used during Mars mission and it is developed by NASA for Curiosity
Rover. The radiations on the Mars are several hundred times more intense than it is on Earth.
Martian atmosphere is very thin at around 1% the density of Earth’s air and no magnetosphere.
The total solar irradiation on Mars is 475 watt per meter square.

Solar Irradiation in Bangalore
Annual average is 5.26 kilo watt hour per meter square.

Table 2 MONTHLY SOLAR IRRADIATION IN BANGALORE

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CALCULATIONS

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CHAPTER 6: CALCULATIONS
Power requirement for dc motor:
DC motor Specification - 100RPM, 12V, 30Kg-cm torque, No load current 60mA, Full load
current 300mA

For linear motion
Prot = M x W
Where,
Prot is the rotational mechanical power.
M is Torque in Newton meter.
W is Angular velocity.
So,
Prot = ((30/100) 9.81) x ( 100x2π/60)
= 2.943 x 10.4719
= 30.81 Watts
Solar Energy output of PV system:
Panel Specification - 5Watts, 17Volts, 300mA (On Earth)
For any other Planet (Except Earth)
Total power output = Total area x solar irradiance x conversion efficiency
= 0.0731 x 475 x .18
= 6.25005 Watt

Charging time for Battery:
Battery Specification - 12v,2000mAh,300mA
So,
Energy = 12x2 = 24Watt hour (from 1 battery)
Total Energy = 24x2 = 48 Watt hour (from 2 batteries)
Peak capacity of four solar panel is 20 Watt, and hence
Charging time = 48/20 = 2.4hour
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CALCULATIONS

DEC-2015

For Calculating Height And Width Of An Object:

A

X

Y

D1

B

D2

C
For finding out the height or width of an object, when the sensor senses an obstacle, it gives the
distance of the obstacle from the vehicle, i.e. D1 and similarly the distance of other edge of the
obstacle D2.The angle α is obtained by the servomotor movement.

Now the height/width is = X + Y
sin( 𝛼 /2) = X / D1
Therefore, X = D1 * sin( 𝛼 /2)
Similarly,
sin( 𝛼 /2) = Y / D2
Therefore, Y = D2 * sin( 𝛼 /2)
And now, the width / height = X+Y.
This way we can determine the height and width of the obstacle. The distance of the obstacle can
be determined by using trigonometric functions again,
cos( 𝛼/2) = distance of the obstacle / D1 or D2
Distance of the obstacle = cos( 𝛼/2) ∗ 𝐷1 𝑜𝑟 𝐷2

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RESULTS

DEC-2015

CHAPTER 7: RESULTS

Figure 15 RESULT 1

The obstacle is present at 10.39 cm , which is less than 15 cm so the vehicle stops .

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RESULTS

DEC- 2015

Figure 16 RESULT 2

The obstacle is present at a distance of 16.97 cm, this is more than 15 cm so the vehicle moves.

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RESULTS

DEC- 2015

Figure 17 RESULT 3

There is no object detected, hence the vehicle continues to move.

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RESULTS

DEC- 2015

Figure 18 RESULT 4

Both the battery values are read, one of them is selected and given to the load and the other is
charged.

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RESULTS

DEC-2015

Figure 19 RESULT 5

Final result when the whole system is implemented.
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CONCLUSION AND FUTURE WORK

DEC-2015

CHAPTER 8: CONCLUSION AND FUTURE WORK
In this project we implemented battery switching and have determined the dimensions of the
obstacle and the distance at which it is present. Depending on the obstacle dimension and
distance at which it is present the vehicle is controlled. This data alone is not sufficient for path
planning. Depth detection is one major aspect which needs to be addressed. So with the help of a
camera images can be captured and processed and the data from the sensors can be combined
and used for path planning. The rover must be able to take independent decisions and move
efficiently in any environment

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REFERENCES

DEC-2015

REFERENCES
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