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VISVESVARAYA TECHNOLOGICAL UNIVERSITY BELGAUM

First Evaluation Report

On

AGROBOT-ROBOT IN AGRICULTURE

Submitted byBATCH NO: 16

NAME: USN NO. :

1. NAVYA. H.N. 4GH08ME038

2. MUNAHID PASHA 4GH07ME406

3. ZABI ULLA KHAN 4GH07ME055

4. KOTRESH. A.B. 4GH08ME026

Under the Guidance of

Dr. MANJUNATH.K

DEPARTMENT OF MECHANICAL ENGINEERING

GOVERNMENT ENGINEERING COLLEGE HASSAN 573201

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TABLE OF CONTENTS

1. INTRODUCTION....3

2. THE CURRENT STATE OF AGRICULTURAL ROBOTICS...4

2.1. Robots in Agriculture.......................4

2.1.1 Autonomous Lawnmowers

2.1.2 Fruit Picking Robot

2.1.3 Eye Sonic Robot

2.1.4 Field robot "Eye-Maize"

2.1.5 Mushroom Picking Robot

2.1.6 The Oracle Robot

2.1.7 Precision Guidance Systems

3. PROBLEM DEFINATION..6

4. LITERATURE REVIEW................................................................7

5. OBJECTIVES OF THE PROJECT......9

6. METHODOLOGY......10

6.1. Block Diagram of Agrobot..11

7. REFERENCES... ....12

8. WORK DONE SO FAR...13

9. WORK TO BE CARRIED OUT.13

1. INTRODUCTION

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Agriculture comes from two Latin words: ager which means a field culturia which

means cultivation, the tillage of the soil. The word robot came from the Czech word

robota, which means forced labor, or work & the term robot was first coined by Karel

Capek.

Robot is "A re-programmable, multifunctional mechanical manipulator designed to

move material, parts, tools, or specialized devices through various programmedmotions for the performance of a variety of tasks [2].

The idea of robotic agriculture is not a new one. Many engineers have developed

driverless tractors in the past but they have not been successful as they did not have

the ability to embrace the complexity of the real world. Most of them assumed an

industrial style of farming where everything was known before hand and the machines

could work entirely in predefined ways much like a production line.

The approach is now to develop smarter machines that are intelligent enough to work

in an unmodified or semi natural environment. These machines do not have to beintelligent in the way we see people as intelligent but must exhibit sensible behavior in

recognized contexts. In this way they should have enough intelligence embedded

within them to behave sensibly for long periods of time, unattended, in a semi-natural

environment, whilst carrying out a useful task.

The approach of treating crop and soil selectively according to their needs by small

autonomous machines is the natural next step in the development of Precision

Farming (PF) as it reduces the field scale right down to the individual plant. One simple

definition of PF is doing the right thing in the right place at the right time with the right

amount.

Most of the current machinery is very weather dependant. Tractors cannot drive on

soil when it is wet, sprayers cannot work in high winds etc. Perhaps it will be possible

to develop smaller, less intrusive machinery that can allow more tasks to be carried

out in marginal conditions as shown in figure 1.

.. The Current State of Current State of A

Fig 1 Agrobot

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2. THE CURRENT STATE OF AGRICULTURAL ROBOTICS

Today agricultural robots can be classified into several groups: harvesting or picking,

planting, weeding, pest control, or maintenance. Scientists have the goal of creating

robot farms where all of the work will be done by machines. The main obstacle to this

kind of robot farm is that farms are a part of nature and nature is not uniform. It is not

like the robots that work in factories building cars. Factories are built around the job at

hand, whereas, farms are not. Robots on farms have to operate in harmony with nature.

Robots in factories dont have to deal with uneven terrain or changing conditions.

Scientists are working on overcoming these problems.

2.1. ROBOTS IN AGRICULTURE

2.1.1 Autonomous Lawnmowers

The scientists and engineers at the National Robotics Engineering Center (NREC) at

Carnegie Mellon University Robotics Institute have developed a mobile robotic mower

that can autonomously move a golf course as shown in figure 2 & 3 [Blackmore et

al.2002]. It can do this safely and precisely and can reliably avoid obstacles as small as a

golf ball. Golf courses require constant maintenance and human labor for this purpose

is expensive. The idea was to replace this human labor. It can be operated at night and

during other off-peak hours and with minimum of human supervision. This robot can

move the entire fairway efficiently and with centimeter level precision to create the

cross-hatch patterns seen on premier golf courses.

Fig 2 Autonomous mower in action Fig 3 System under trees

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2.1.2 Fruit Picking Robot

Another robot is the fruit picking robot, which must be able to reach all levels of a tree

and be able to pick fruit without damaging it. The robot must have good sensory

awareness touch, sight, and image processing, and able to distinguish between

certain fruits (plums: softer; oranges: harder rind). The robot uses a camera to tell the

difference between fruit and leaves and has an air blower to blow leaves out of the

way as shown in figure 4.

.

Fig 4 Fruit Picking Robot

2.1.3 Eye Sonic Robot

The winner for the year 2009 was a robot named Eye Sonic developed at the

Wagenengen University, in cooperation with a host of industries. This robot navigates

through maize rows with help of a Sick Laser scanner as shown in figure 5. A compass

is mounted on the robot to maintain course within the maize rows and on the

headland it is used to turn. It also has the capability of detecting green golf balls.

Fig 5 Eye Sonic robot

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2.1.4 Field robot "Eye-Maize"

The goal was to make a concept and to realize a low-cost robotic vehicle usingoptoelectronic sensors and a microcontroller-based platform. The vehicle is calledEye-Maize as shown in figure 6. At the Field Robot Event Eye-Maize successfully

drove between the straight and curved rows with reasonable speed. Moreover, the U-

turn worked well for dry soil. Problems occurred at the U-turn for wetted soil due to

slip. The integration of additional devices like acceleration sensors or an electronic

compass might solve this problem in the future.

Fig 6Eye-Maize field robot

2.1.5 Mushroom Picking Robot

Mushrooms are a very difficult crop to

grow. There is a lot of labor involved.

Many mushroom farms are becoming

extremely high tech. They use

computerized systems and monitor all

production phases & it is as shown infigure 7.

Fig 7 Mushroom Picking Robot (19)

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2.1.6 The Oracle Robot

In the case of the sheep shearing robot, productivity of sheep stations can be

increased also, with fully automated sheep shearing plants taking over from teams of

shearers as shown in figure 8. After all, robots do not get tired, and don t require

lodging, feeding or back pay! However, care must be taken to keep such systems

maintained regularly, as conditions on outback stations are inhospitable for such

precision machinery.

Fig 8 Oracle Robot

2.1.7 Precision Guidance Systems

Precision Guidance system refers to the activity of operating farm equipment (tractors,combines, etc) with the aid of a positioning system such as Global Positioning System

(GPS) as shown in figure 9. There are primarily two types of guidance systems: (I) a

farmer is actually the driving the tractor and he is aided with a sensor or suite of

sensors to maintain his driving pattern referred to as Manual Control/Light bar and

(ii) a farmer is primarily supervising the tractor in its auto-steer or hands-free

mode referred to as fully auto-mated Auto Control/Auto Steer system.

Fig 9 Visualization of seeding robots. (Blackmore et al. 2008)

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3. PROBLEM DEFINATION

Seed bed preparation by manually is very risk full. Most of the current machinery is very weather dependant. Tractors cannot

drive on soil when it is wet.

Manual agriculture depends on man power it may take longer process.

4. LITERATURE REVIEW

Tim Niemueller et al. [1] have developed a short introduction to the basics of robotics

in the context of artificial intelligence. It describes the very basics of robotics likesensors and effectors, gives an overview on robotic history, and introduces some basic

problems encountered in modern robotics. It describes possible solutions to those

problems without going deeply into theory.

Blackmore et al. [2] have presented a new method, described that can be used to

decompose human controlled agricultural operations into an autonomous tractor.

Four main levels of subsumption have been identified: Operation, Task, Optimization

and Primitive Actions where each level is subsumed by the level above. Tasks were

classified into two distinctive roles, deterministic tasks. The tasks and optimizations

can be further decomposed into primitive actions which in turn are converted into the

tractor directories.

Pedersen et al. [3] have developed an autonomous systems are more flexible than

conventional systems and may reduce labor costs and restrictions on the number of

daily working hours significantly. In addition, at this stage of development, the initial

investments and annual costs for expensive GPS systems are still relatively high but it

seems possible to design economically viable robotic systems for grass cutting, crop

scouting and autonomous weeding.

Simmon [4] has developed agricultural automation is a continual development. The

current research technologies give rise to the possibility of developing a completely

new mechanization system to support the cropping system based on small smart

machines. This system replaces blanket energy over application with intelligently

targeted inputs thus reducing the cost of the inputs while increasing the level of care.

This can improve the economics of crop production as well as having less

environmental impact.

Oksanen et al.[5] had found requirements for methods and automated machinesneeded in automated crop production. During the last few decades technology used in

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crop production has developed noticeably. The work of farmers has decreased and

continues decreasing by means of technology and automation.

Jinlin et al. [6] have presented the variable Field Of View (FOV) of camera to realize

headland turning of an agricultural robot in corn fields.

Ryosuke et al. [7] have developed the modified conversion of a commercial crawler-type tractor into a robot tractor that can be navigated autonomously by using RTK-GPS

and IMU as navigation sensors. In this the robot could successfully finish the single

straight line path & a multiline path.

Shrinivas and Zanwar [8] have developed the assembly is developed for cultivating

ploughed land automatically i.e. no man power required. The project has consists of

two different mechanism. The first mechanism contains making an assembly of vehicle

and its motion, where as second mechanism is preparing a seed bed on ploughed land.

5. Objectives of the Project

Ploughing of the land. Seeding of crops. Soil lapping.

Seed bed preparation:

Ploughing is one of the most important primary cultivation processes and has beencarried out since the start of civilization. It is effectively the inversion or mixing of

topsoil to prepare a suitable seed bed. The seed require contact with soil moisture to

allow uptake of water and nutrients. It requires stability to hold the growing plant and

structured that allow the root to develop and shoots to grow.

Seed placement:

Rather than just record the position of each seed it would be better to be able to

control the seed position. This would allow not only allow the spatial variance of seed

density to be changed but also have the ability to alter the seeding pattern. The

technique of seed boring in ploughed land is in the form of row per column with fixed

standard distance depending upon type of crop or type of cultivation.

Soil lapping:

After seed placement the soil is to be overlapped with the help of v- shaped

arrangement.

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6. METHODOLOGY

The following are the steps involved in development of robot

Selection of motor- Dc motor-800RPM. Selection of drives- chain drive. Selection of materials- persorated mild steel plate. Selection of controller- Remote controle-HT-12D, HT-12E. Configuration- Cartesian coordinate. Microcontroller-PIC 16F 877. Power Source- Battery 12v, 10AH.

6.1. Block Diagram of Agrobot

The system uses so many automatic methods which really require very less man

power. The robot is made of tyre wheels with one freewheel to take immediate actions.

The ploughing and seeding mechanism is so arranged that the farmer can be

controlled from the RF remote control. To navigate the robot the camera is used which

rotates at angle of around 90 degrees. The system has been connected with wireless

technique to control the action. The data has to be sent through wireless so that to

choose the ASK (amplitude shift keying) method to send the binary data with RF

environment. The data has to be sent in the form of binary is then encoded with encoder

with the help of a key pad as shown in figure 12. The keys may be assigned separately

for every function like movement of the vehicle, rotation of the motor for ploughing,

trigger action for seeding etc. The data for every action will be encoded as 0001, 0010

0011, etc each data has got its own meaning. Finally the encoded data has been sent

through a RF technique using transmitter which is tuned at 433MHZ. The RF waves

radiated in the atmosphere through the RF antenna.

When the RF waves are interact with receiving antenna the demodulation will takes

place and the logical data are available but the data is in the form of serial and need

for converting it in to a parallel for this the decoder is used. The decoder converts the

serial data in to parallel, the o/p of the decoder is the same data which is sent from

the transmitter end. The data is now passed to the microcontroller for further actions.

The microcontroller used here is PIC16F 877 which is flash based memory. It is so programmed

that on receiving the particular data the particular action will execute. The controller is

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sensing the data and always in the polling mode which poles the i/p. if the data sent

from the transmitter is for the action of front movement for the robot the particular

binary data is sent in the form of RF waves as when it is interact with receiver further the

sane data is available to the controller and it send the signal to the motor driving unit

so that motors has to rotate in the forward direction and moves the robot in forward.

The motor driving circuit uses relay driving unit which decides the direction ofthe motor with proper polarities as shown in figure 13.

The motors used here is DC type 12V bidirectional. The same action is takes place

for remaining function like backward movement, left, right, forward, seeding and

ploughing motor rotation stop and start etc. To navigate the direction of the robot the

camera is used which capture the image signal. To send the picture info, the AM is used.

The transmitting of these signals is at bandwidth of 5.5MHZthrough the antenna at final

RF frequency of 400-500MHz. When these RF signal interact with receiver unit which is a

remote controlled unit, demodulation will takes place and video data processed in the

AV process block. The o/p now can be connected to TV or pc for monitoring purpose. The

pc can be used with TV tuner card so that robot can be controlled for its movement and also

possible to capture the signals directly on the hard disc.

Fig 12 Block diagram of Remote controller

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Fig 13 Block diagram of Agrobot

7. REFERENCES

[1] Tim Niemueller and Sumedha Widyadharma, Artificial Intelligence An

Introduction to Robotics, July 8, 2003, pp.1 14.

[2] Blackmore, B. S., Fountas, S., Vougioukas, S., Tang, L., Srensen, C. G., and

Jrgensen,R, A method to define agricultural robot behaviors, Mechatronics &

Robotics Conference (MECHROB) ,2004, pp.1197-1200.

[3] S. M. Pedersen S. Fountas H. Have B. S. Blackmore, Agricultural robotssystem analysis and economic feasibility, 27 July 2006, pp. 7:295308

[4] Simon Blackmore, New concepts in agricultural automation, HGCA conference

28 and 29 October 2009.

[5] M. Hakojrvi, M. Hautala, J. Ahokas, T. Oksanen, T. Maksimow, Aspiala, A. Visala,

Platform for simulation of automated crop production, Agronomy Research 8 (1),

pp.797806, 2010

[6] Jinlin Xue , College of Engineering, Nanjing Agricultural University, Nanjing ,China and Tony E.Grift, Agricultural Robot Turning in the Headland of Corn Fields,

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International journal of Applied Mechanics and Materials Vols. 63-64, 2011, pp. 780-

784.

[7] Ryosuke TAKAI, Oscar BARAWID Jr., Noboru NOGUCHI, Autonomous Navigation

System of Crawler-Type Robot Tractor, 18th IFAC World Congress, August 28 -

September 2, 2011, pp. 14165 - 14169

[8] Mr. Shrinivas R. Zanwar, Agricultural Robot for Cultivation Process,Vol. I No.1

December-January 2012 ISSN 2249-9032, pp.1-6.

Work done so far:

Literature has revived related to past development in agriculture robot. Methodology of agrobot has prepared.

Work to be carried out:

To design of the robot parts & assembling those are remaining. Programming of agrobot is in process. Remaining to fabricate.