solar powdered autonomous vehicle

CONTENTS DEC- 2015

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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

LIST OF FIGURES DEC- 2015

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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

LIST OF TABLES DEC- 2015

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LIST OF TABLES

Table 1 TECHNICAL SPECIFICATION OF ARDUINO MEGA ......................................................... 17

Table 2 MONTHLY SOLAR IRRADIATION IN BANGALORE ........................................................ 30

ABSTRACT DEC- 2015

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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.

INTRODUCTION DEC- 2015

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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.

INTRODUCTION DEC- 2015

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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.

LITERATURE SURVEY DEC-2015

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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.

LITERATURE SURVEY DEC- 2015

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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 partially-

known 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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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.

COMPONENTS USED DEC-2015

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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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2) PLASTIC CHASSIS

Figure 2 PLASTIC CHASSIS

Specification:

No. of chassis: 1

406.4x406.4x100(mm), 1.1Kg


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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.

COMPONENTS USED DEC- 2015

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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

http://cytron.com.my/p-sn-hc-sr04


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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

Torque:

4.8V:

44.0 oz-in (3.17 kg-cm)

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)

Dimensions:

Length:

1.57 in (39.9 mm)

Width:

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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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

HARDWARE IMPLEMENTATION DEC-2015

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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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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.

SOLAR IRRADIATION DEC-2015

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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

CALCULATIONS DEC-2015

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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

CALCULATIONS DEC-2015

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For Calculating Height And Width Of An Object:

A X Y B

D1 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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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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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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Figure 17 RESULT 3

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

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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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Figure 19 RESULT 5

Final result when the whole system is implemented.

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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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solar powdered autonomous vehicle

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