DECLARATION

I do hereby declare that the work reported in this dissertation was exclusively carried out by me under the supervision of Mr.Duminda T Wijesinghe.It describes the results of my own independent research except where due reference has been made in the text. No part of this dissertation has been submitted earlier or concurrently for the same or any other degree.

. .Date Signature (H.M.C.B Mawilmada) We/I endorse the declaration by the candidate.

..........................MR.Duminda T Wijesinghe

Date: .

ABSTRACT

Outdoor localization involves handling environmental ambient noises as well as adapting the system to sudden changes in parameters such as light level variation. Trilateration algorithms are used for localizing robot in a limited area with a higher accuracy. Researchers have carried out in trilateration algorithm either using ultrasonic sensors or computer vision. Ultrasonic sensory trilateration involves a higher error ratio due to variations of environmental air velocity, moisture level and air density. CV mainly lacks adjustability to light condition variations. Higher the accuracy in CV, greater the cost of implementation. This Project is based upon combining both algorithms to get a higher accuracy output and making the algorithm viable with higher ambient noise with a low cost. Three stationary ultrasonic receivers were placed in known distance apart with a colour tag(red). The robot was assembled with colour identification using a web camera (to track the colour tag on the receivers) and an ultrasonic transmitter. RF signal was initiated simultaneously with the ultrasonic burst which directed towards the receivers. The time taken for the ultrasonic burst to be received after receiving the RF signal was recorded for three receivers separately and distance from each station was calculated. Trilateration was used to predict the position and Kalman filtering was used to filter out the noises System was implemented and tested in an open ground which has minimal obstacle disturbances but high noise levels (light and sound) with about 1000m2 area and was able to achieve accuracy of 40-50cm with 80% confidence level for stationary robot and while moving at 1ms-1 accuracy of 60cm is achieved with a confidence level of 80% which is acceptable accuracy to localize an outdoor robot. Higher accuracy of 40-50cm was obtained for stationary positions, which suggests system is suitable for localizing slow moving robots such as grass cutters, Automated guided vehicles, combined harvesters etc.

ACKNOWLEDGEMENT.

At this important milestone of entire hard work I would like to express my gratitude to all those who were with me and helped me to finish this journey successfully.First of all I would like to express my very great appreciation to MR.Duminda T Wijesinghe my project supervisor for his wisdom and enormous support and encouragement given to me throughout the three months to make this project very successful. He had been very kind and patient while suggesting me the outlines of this project and correcting my doubts. I thank him for his overall support.I'm pleased to thank Auston Ceylon and all the staff members for their kind cooperation and help.I also like to thank Mr. Aruna Rubasinghe and Bhanu Watawana for sharing their experience and knowledge with me to make this project successful.At last but not least, I would be very grateful to my parents who were behind all the time encouraging me and making all the preparations required to pass this important mile stone of my life.

TABLE OF CONTENT

DECLARATION ii ABSTRACTiiiACKNOWLEDGEMENTS iv TABLE OF CONTENTS v LIST OF FIGURES vii CHAPTER1.Introduction11.1.Problem Statement21.2.Literature Survey21.3.Solution Overview32.Methodology52.1.Ultrasonic Sensor52.1.1.Ultrasonic Sensor Coverage-Horizontal Plane62.1.2.Ultrasonic Sensor Coverage-Vertical Plane72.2.Sensor System72.2.1.Ultrasonic Transmitter System82.2.2.Ultrasonic Receiver System82.3.Node Placement92.4.Outdoor Localization System92.5.Trilateration Algorithm102.6.Improving Results with Kalman Filter112.7.Discrete Kalman Filter for Radius Measurements11

3.Implementation Of The System123.1.Ultrasonic Receiver Unit123.1.1.Ultrasonic Transducer133.1.2.Ultrasonic Amplifier133.1.3.Frequency Detector153.1.4.Microcontroller183.1.5.Power Supply193.1.6.Embedded Algorithm203.2.Ultrasonic Transmitter Unit213.2.1.Power Supply223.2.2.Microcontroller223.2.3.Boost Converter233.2.4.H-Bridge253.2.5. XBee Module 263.2.6.Embedded Algorithm273.3.Servo Controller Unit283.3.1.Power Supply283.3.2.Microcontroller283.3.3.PC USB Interface304.Results and Discussion315.Conclusions33

References 34 Appendices 35

LIST OF FIGURES

Figure 1: Robot fabricated1Figure 2:Beam pattern as in the manufacturer datasheet6Figure 3: 2D view of the single ultrasonic sensor7Figure 4: Placing the sensors8Figure 5: 3 circle method10Figure 6: Block diagram of the Node10Figure 7: 400SR16012Figure 8: Waveforms of received ultrasonic signal and amplified output13Figure 9 : Block diagram14Figure 10: Amplifier Schematic14Figure 11: Frequency vs. sensitivity of ultrasonic transducer14Figure 12: Schematic of frequency detector16Figure 13: Output of frequency detector w.r.t input ultrasonic signal17Figure 14: Schematic of microcontroller unit17Figure 15: Schematic of power supply unit18Figure 16: Basic algorithmic flow diagram of ultrasonic receiver unit19Figure 17: Structure of ultrasonic transmitter unit20Figure 18: Schematic of microcontroller unit21Figure 19: Standard schematic of MC34063 based boost converter22Figure 20: SMPS Schematic23Figure 21: Waveform of ultrasonic transducer drive voltage for 8V supply24Figure 22: Schematic of H-bridge section25Figure 23: Basic algorithmic flow diagram of ultrasonic transmitter unit26Figure24: XBee module....26Figure 25: Basic algorithmic flow diagram of ultrasonic transmitter unit..27Figure 26: Schematic of Servo Controller......29 Figure 27: Schematic of USB interface circuit30Figure28: Occurrence graph........................................................................................31

ii

CHAPTER 1

1. INTRODUCTION

Figure 1: Robot fabricatedRobotic Localization is a vast area of research & implemented at different scales. Many researches are carried throughout the world to find optimum and most cost effective method of implementing a localization system. In these project, technologies like Computer Vision, GPS, Wi-Fi, GSM, RFID and ultrasonic are used for the localization. The main concept of robotic localization is similar where it uses a known stationary position as the base and calculates the relative position with different technologies. Outdoor localization involves handling environmental ambient noises as well as adapting the system to sudden changes in parameters such as light level variation. The motivation of this project is to address this issue and find an optimum trilateration algorithm for robotic localization. CV, Wi-Fi, GSM, RFID and Ultrasonic sensory localization uses trilateration algorithms. Trilateration algorithms are used for localizing robot in a limited area with a higher accuracy. Researchers have carried out in trilateration algorithm either using ultrasonic sensors or computer vision. Ultrasonic sensory trilateration involves a higher error ratio due to variations of environmental air velocity, moisture level and air density. CV mainly lacks adjustability to light condition variations. Higher the accuracy in CV, greater the cost of implementation. This project is based upon combining both algorithm to get a higher accuracy output and making the algorithm viable with higher ambient noise with a low cost.

1.1 Problem Statement Outdoor Robotic Localization involves high costs and use of advanced technologies. The main objective was to build and implement a low cost, high accuracy outdoor localization system. It is consisting ultrasonic transmitters and receivers. Usage of minimum number of receiver base stations and deliver an acceptable accuracy for localized robot was also considered. To minimize the power usage and the number of base stations Computer Vision was used to target the outgoing burst. Low cost ultrasonic sensors usually work in a range of less than 4m. Improvements were made to increase the range.

1.2 Literature Survey The active bat location systemThe active bat location system consists of mobile or fixed wireless transmitters, a matrix of receiver elements, and a central controlling system. Receivers are placed in a square grid, 1.2m apart, and are connected by a high-speed serial network in daisy-chain fashion. The central controller starts the activity of transmitters by periodically broadcasting messages addressed to each of them in turn. A transmitter, up on hearing a message addressed to it, sends out an ultrasonic pulse. The receiver systems which also listen to the initial RF signal will determine the time interval between the receipt of the RF signal and the receipt of the ultrasonic signal. By this method they estimate the distance to the transmitter. By considering enough distance measurements the system can then determine the location of the transmitter. The system has an accuracy of 3cm. Though the accuracy of the system is very high it need a sophisticated environment to deploy.

Active badge systemActive badge system uses infrared transmitters and receivers to pinpoint a location of an object. This is one of the first localization systems. But infrared suffers from having dead spots the localization accuracy of the system is low. The system can be used to track objects successfully at the room level.

The cricket localization system The cricket localization system consists of two types of nodes, they are cricket beacons that act as fixed reference points of the location system and are typically attached to the ceiling and walls of a building, and listeners that are attached to fixed and mobile objects that need to determine their location. In contrast to active bat system cricket does not need a grid like system to deploy. Therefore it is easy to deploy the system in an indoor environment. It also uses a passive mobile system which has ultrasonic receivers in the listeners. Therefore the system has an added advantage of privacy and power saving. The system has accuracy around 10cm. This system also uses more beacons than our system. BATSY system BATSY system is also a system that uses a combination of ultrasonic and RF for localization. The system has an accuracy of 3cm.

IEEE 802.11 based localization systemsMany research groups have developed localization systems using IEEE 802.11. But those systems have a median estimation error around 1- 3m. The advantage of these systems is it can use the existing IEEE 802.11 nodes therefore special anchor nodes are not needed. Stereo vision involves two images taken at the same time, some space apart. This involves high-tech gear for higher accuracy. Low cost Stereo vision algorithms are available even though the accuracy and the outdoor compatibility is less. Ultrasonic Trilateration involves three or more ultrasonic receivers placed in a known distance apart and an ultrasonic burst is send towards it. When the pulse received, a calculation is done trilaterating the robots location to pinpoint its exact location. The error may vary around 10 20 cm.

1.3 Solution Overview

The approach is to pinpoint the location using measured distances from at least 3 stationary point ultrasonic receivers using Ultrasonic trilateration. Using the readings from CV the transmitter was oriented towards the receiver. Robot was equipped with ultrasonic transmitter and a web camera which capture the colour tag as well as orienting transmitter to receivers locations. Ultrasonic receivers were placed at stationary positions on the outdoor environment. Ultrasonic sound wave propagation time from robot to stationary positions was measured and distance was calculated using the velocity of sound and heading angle was calculated using the direction of the transmitter.

CHAPTER 2

2. METHODOLOGYThis chapter is about the sensor type that was used in the project and describes the types of sensor systems used in the project and the different methods available in order to achieve the objective. Then describes the node attributes and node placement criteria used in the project. Afterwards describes about the trilateration algorithm and filtering methods used in the system to reduce the effect of noise. 2 2.1 Ultrasonic Sensor Ultrasonic sensors are without a doubt, one of the most frequently used sensors in robotic applications and many other industrial applications. They are often used to detect the presence of objects in robotic applications. It also can be used to measure the wind speed and direction, fullness of a tank etc. Certain limitations of the ultrasonic sensors have a major effect on the success of the related applications and they often become the reason for the failures of those as well.

Ultrasonic sensors work the same principle as the radar or sonar. It generates high frequency signals and the receiver waits for the echo or the direct transmitted signal and calculates the time interval for the arrival of the echo or the direct signal to determine the distance. Most often ultrasonic sensors are used to determine the presence of obstacles.

But in this project ultrasonic sensors were used in a different perspective. In here transmitters and the receivers are in distant locations and the time taken by the ultrasonic signal to travel from the transmitter to the receiver was measured. In this project 400ST160 ultrasonic transmitters and the 400SR160 ultrasonic receivers were used. This type was chosen due to high sensitivity and sound pressure level, low cost, excellent temperature and humidity durability.

2.1.1 Ultrasonic Sensor Coverage-Horizontal Plane

Ultrasonic sensor coverage is shown below according to the manufacturer datasheet.

Figure 2:Beam pattern as in the manufacturer datasheet

The center frequency of this sensor is 40 KHz. According to the data sheet it has a beam angle of 55 degrees. Apart from the datasheet information tests were carried out a testing to determine the achievable accuracy of a single ultrasonic sensor to different distances. The following figure shows the accuracy levels we have obtained to different distance levels.

Figure 3: 2D view of the single ultrasonic sensor

As shown in the above figure it was possible to use for 60 degree beam angle from a single ultrasonic sensor. Three ultrasonic transmitters were used to increase the angle. The angle between two consecutive sensors is 30 degrees.

2.1.2 Ultrasonic Sensor Coverage-Vertical Plane The ultrasonic beam pattern in the vertical plane is not much wider than in the horizontal plane. In the project all the nodes in the same height were placed same height and height difference between a node and the user equipment considered a negligible value.

2.2 Sensor SystemThe sensor system consists of three parts. Ultrasonic transmitter system Ultrasonic receiver system Object tracking system

Figure 4: Ultrasonic Transmitter

2.2.1 Ultrasonic Transmitter System

The transmitter sensor system consists of 3 ultrasonic transmitters mounted on a casing. As described in section 2.1 the maximum angle that a single ultrasonic sensor can cover the area is 55 degrees according to the given datasheet. So using 3 ultrasonic sensors can transmit signals wider range. All the 3 ultrasonic sensors are placed equal space in order to achieve maximum signal coverage. The depth of the ultrasonic sensor signal coverage is not much considered as the receiver and the transmi1tter are placed approximately the same level and directs the transmitters and the receivers to the same direction.

2.2.2 Ultrasonic Receiver System

The receiver sensor system consists of 3 ultrasonic sensors mounted with equal angles between them. As the receiver sensor system is a stationary system the transmitter should be directed. The depth of the ultrasonic sensor signal coverage is not much considered in here as well.To have accurate location coordinates it is necessary to measure the distance with high accuracy. In order to achieve that it is necessary to have a good ultrasonic coverage over the outdoor environment. To obtain good coverage the transmitter/receiver units need to place properly in the testing environment.

2.2.3 Object tracking system

The common web camera was used for object tracking along with a High power servo motor. The web camera identifies the colour tag on the receiver is then checked for the center point of the tag. It is then checked with a tolerance of 10 pixels. If out of tolerance, PC sends the command to the servo to turn the camera left or right according to the position.

2.3 Node Placement

The localizing part of the project depends on the concept called trilateration. In contrast to the popular triangulation algorithm this uses distances instead of angles. The concept behind this algorithm is the intersection of three circles (or four non coplanar spheres for a three dimensional coordinate system). Since using a 2 dimensional planer coordinate system for the localization this suit the three circle method.

2.4 Outdoor Localization System

The outdoor localization system consists of 4 subsystems. Transmitter subsystem Receiver subsystem Servo Central controller Software Installed PC

Servo controller is connected to the laptop on the robot. It is connected to the receiver subsystem and the PC from a wired link. Transmitter subsystem is connected to the network from a wireless link. The details of each of the subsystems are described in chapter 3. The following figure shows the configuration of the Outdoor localization system.

Figure 5: Placing the sensors

2.5 Trilateration Algorithm Suppose the system have three circles with coordinates C1 (x1,y1) C2- (x2,y2) C3-(x3,y3)Respectively, and further know their distances l1, l2 and l3 from some unknown point(x,y). This unknown point is located at the intersection of three circles with C1,C2, and C3 as their centers and l1, l2, l3 as their radii, respectively. Then the intersection point of these three circles which is the unknown point can be expressed as follows;

Figure 6: 3 circle method

(x1-x)2 + (y1-y)2 = l12 (x2-x)2 + (y2-y)2 = l22(x3-x)2 + (y3-y)2 = l322.6 Improving Results with Kalman Filter

To further increase the results system was programmed with a one dimensional Kalman filter for the calculated radiuses from each of the receivers.

2.7 Discrete Kalman Filter for Radius Measurements

The Kalman filter is used to address a problem which is trying to estimate a discrete time controlled process that is governed by the following equation.

Xk=Axk-1 + Buk + wk-1

CHAPTER 3

3. IMPLIMENTATION OF THE SYSTEM

This chapter describes how each and every sub system of the project works. Task, circuitry, explanations are well described in the chapter.

3 3.1 Ultrasonic Receiver Unit

Ultrasonic receiver is a Node device which is responsible for measuring the ultrasonic sound wave propagation time and calculating the distance between the ultrasonic transmitter and the receiver. Sensor network consist of 3 such Node devices and the central controller is connected as a ring network using Coaxial cables. Each receiver unit consumes about 40mA.

Figure 7: Block diagram of the Node

3.1.1 Ultrasonic Transducer Ultrasonic transducer used in this project is a 400SR160 type ultrasonic receiving module. It has 40 kHz center frequency with 55O beam width. One or more such transducers are connected in parallel and mounted with some angle between transducers, in order to increase the total beam angle, hence increase the range of operation.

Figure 8: 400SR160 ultrasonic receiver

3.1.2 Ultrasonic Amplifier The output of the ultrasonic transducer is a signal with amplitude of few mili-volts. This amplitude varies with the strength of the receiving ultrasonic sound wave. Therefore this small signal needs to be amplified to a sufficient value before processing further. This is important to detect ultrasonic signals emitting from a location few meters away. Below, oscilloscope screen shows voltage signal (in yellow) generated by ultrasonic transducer and signal after amplification (in blue). Signal before amplification has about 16mV peak to peak value.

Figure 9: Waveforms of received ultrasonic signal and amplified output

Amplifier section can be expanded as below.

Figure 10 : Block diagram of amplifier expansion

Figure 11: Amplifier Schematic

The amplifier is based on TL082CP operational amplifier manufactured by Texas Instruments. There are several important factors that need to be considered when selecting an op amp for an application like amplifying a signal from an ultrasonic transducer. Three main factors were considered when choosing the op amp for the design; Op amp input bias current Op amp gain bandwidth product Number of op amps in a single package

As the signal received from the ultrasonic transducer is very small, loading effect can easily attenuate and distort the input. Therefore amplifier's input current required to bias the internal circuitry needs to be extremely low. Unlike bipolar input op-amps, TL082 have JFET inputs which require only about 50 pA of input bias current. Therefore loading effect caused by amplifier stage can be negligible. Op-amps gain bandwidth product (GBP) is also an important factor when designing the amplifier stage. Voltage signal of the transducer is 40 kHz signal. Op amp should be able to amplify this 40 kHz signal without distortion. TL082 has a gain bandwidth product of 4 MHz . Therefore maximum amplification that can be achieved by one op amp on 40 kHz signal is 100 times.

3.1.3 Frequency Detector Normally, amplified signal from the amplifier is sent through a band pass filter and a peak detector followed by a comparator to get a constant dc voltage as a trigger signal to the microcontrollers. This is done assuming ultrasonic transducer is only sensitive to its resonance frequency which is 40 kHz. These methods are erroneous and amplified signal cannot be directly fed into the microcontroller because the amplified signal can be a signal other than an ultrasonic signal with 40 kHz frequency. This is possible because transducer used to receive ultrasonic signals is also sensitive to other frequency ranges. Ultrasonic transducers resonance frequency is around 40 kHz, but it generates voltage signals for any other sound frequencies. However these signals generated by frequencies other than 40 kHz are attenuated due to less sensitivity of transducer to non 40 kHz signals. However after amplified by the amplifier, these signals can become significant, hence will act as false triggers to the microcontroller especially if the amplifier gain is sufficiently large. Following graph shows transducers sensitivity to the receiving sound frequencies. In this design amplified output of the received signal is given to a frequency detector circuit. This is done in order to verify whether the signal amplified by the amplifier, is actually a 40 kHz signal or any other noise signal.

Figure 12: Frequency vs. sensitivity of ultrasonic transducer

Frequency detection is done using the LM567 tone decoder IC by National semiconductors. LM567 tone and frequency decoder is a highly stable phase-locked loop with synchronous AM lock detection and power output circuitry.

Figure 13: Schematic of frequency detector

LM567 has an active low open collector output. Circuit set its output to logic low from logic high, whenever a frequency within its detection band is present at the self-biased input. Below oscilloscope screen shows output of LM567 (in blue) for input of 40 kHz bursts (in yellow).

Figure 14: Output of frequency detector w.r.t input ultrasonic signal

Center frequency of this detection bandwidth can be calculated using following equation.

RV1 is calculated from above equation for f0 = 40 kHz and C18 = 4.7 nF as 5.32 k. RV1 is replaced with a 10 k multi-turn trim-pot in order to set the center frequency precisely to 40 kHz. Temperature instability in capacitors can cause frequency drift in the system which leads to malfunctions over the time. Therefore a Mylar capacitor is chosen over a ceramic capacitor for the C18 as Mylar capacitors have higher temperature stability than ceramic capacitors.

3.1.4 Microcontroller PIC12F683 microcontroller by Microchip Technologies Inc. was chosen as the heart of the receiver subsystem. It is an 8 pin microcontroller with 2k flash memory and operates with 20 MHz clock speed. Main function of the microcontroller is to calculate the distance between the ultrasonic transmitter and the receiver by measuring the time difference between sync pulse from central controller and the ultrasonic signal from the transmitter. Calculated distance is stored in the memory until the central controller request the distance.

Figure 15: Schematic of microcontroller unit3.1.5 Power Supply Power supply to the system contains + 9V, - 9V, +5 V and ground. 9V dual supply is used to operate the op-amp and 5 V is for the frequency detector circuit and the microcontroller unit.

Figure 16: Schematic of power supply unit

3.1.6 Embedded Algorithm

Figure 17: Basic algorithmic flow diagram of ultrasonic receiver unit

If the issued command is equals to the broadcasting address, receiver sub system start the process to calculate distance. It time synchronized with transmitter unit using a synchronizing bit via central controller. Time synchronized receiver sub system measure the time duration to propagate ultrasonic wave. Using the speed of sound in air, distance calculation will be completed. We used 330ms-1 as the speed of sound by neglecting the effect from atmospheric temperature variation. This is because at the trilateration, error due to temperature variation cancelled out.Calculated distances are stored to send later when a request is made by the central controller. If the received command is equals to the device ID of a receiver subsystem, it sends the stored distance to central controller immediately. All the decoded commands are error checked for accurate communication. If a single error occurs, receiver will neglect the data.

3.2 Ultrasonic Transmitter Unit Ultrasonic transmitter unit is the mobile device of the system.

Figure 18: Structure of ultrasonic transmitter unit3.2.1 Power Supply Power supply to the system is provided using the robot's battery with 7000mAh capacity. This is reduced to 5v and 3.3v to power up the controller board and the XBee module. And battery power is directly connected to input of the boost converter, which used to drive the ultrasonic transducers. Power consumption of the transmitter is about 150mA. 3.2.2 Microcontroller PIC16F876A microcontroller was chosen as the brain of the system. It is responsible for following tasks; 1. Communicate with central controller through RF using the XBee module. 2. Generating ultrasonic burst at central controllers request 3. Controlling the boost converter to adjust the power of the ultrasonic burst 4. Receive calculated coordinates from central controller and pass it to through the output port.

Figure 19: Schematic of microcontroller unit3.2.3 Boost Converter Displacement of the ultrasonic transmitter transducer diaphragm is proportional to the voltage applied to the diaphragm. As applied voltage increases diaphragm displacement increases, hence it increases the energy of the ultrasonic burst, allowing it to travel higher distances before decaying. Boost converter is used to generate 4 predefined voltages up to 20v from battery input. These voltages are used to drive ultrasonic transducers. When transmission over higher distance is required output voltage of the boost converter is adjusted by the microcontroller as necessary. Boost converter is based on MC34063A IC by on semiconductors.

Figure 20: Standard schematic of MC34063 based boost converter

Original boost converter design is modified to make a voltage controlled, voltage output so that microcontroller can adjust the output voltage of the boost converter in real time. Modified boost converter is shown below in Figure

Figure 21: SMPS Schematic

Modification allows microcontroller to set boost converter's output voltage to 4 different pre defined voltages (8V, 12V, 15V and 20V). This is done by applying 5V or 0V to the terminals Vset_8, Vset_12, Vset_15 or Vset_20. When 5V is applied to a terminal it will reverse bias the diode connected to it and will effectively remove the effect of the resistor attached to that terminal. When 0V is applied to a terminal by the microcontroller it will forward bias the diode connected to it, and it will act as a ground path to the diode and the resistor connected to it. Hence it will form a voltage divider between output voltage and ground.

Microcontroller can turn off the boost converter by applying 5V on all four terminals, which will turn off all 4 diodes. This will connect feedback pin (pin 5) of MC34063 to Vout through R10 which act as a pull up resistor to feedback pin. This will set voltage of feedback pin to a higher voltage than 1.25V thus MC34063A will set its duty cycle to 0 trying to decrease voltage of feedback pin to 1.25V by decreasing the Vout.

Boost converter is turned off when RF communication is active in order to avoid any electromagnetic interference generated by inductor of the boost converter, to the RF communication. Boost converter is only turned on before transmitting an ultrasonic burst. This also acts as an energy saving process because power wastage by boost converter is minimal during its turned off mode.

3.2.4 H-Bridge Direction of ultrasonic transmitter diaphragm's movement depends on the polarity of applied voltage. The diaphragm can be moved in both forward and backward directions by applying an alternative voltage. Such movement increases the energy stored in the ultrasonic burst. Therefore the H bridge circuit is used to provide alternative voltage signal at 40 kHz to the transducers.

The output signal of H-Bridge for 8V supply is as below. It has near 16V peak to peak value.

Figure 22: Waveform of ultrasonic transducer drive voltage for 8V supply

H-bridge circuit is based on L293 IC by Texas instruments. Direction change pins of L293 are supplied with 40 kHz signal and 1800 phase shifted 40 kHz signal. Ultrasonic burst is generated by applying logic 1 to L293's enable pin. Output of H-Bridge is connected to 8 ultrasonic transducers connected in parallel. When logic 1 is applied to enable pin, transducers are applied with twice voltage as boost converters output voltage, by the H-bridge.

Figure 23: Schematic of H-bridge section

3.2.5 XBee MODULE

RF communication between central controller and the Transmitter unit is done using a XBee module. RF module used in this project is a 2.4GHz, 1mW, series 1 XBee module by Digi internationals. Operating range of module is 100m. It is based on IEEE 802.15.4 specification and Zigbee network standard.

Figure :24 XBee module3.2.6 Embedded Algorithm

Figure 25: Basic algorithmic flow diagram of ultrasonic transmitter unit

Figure 25 shows the basic algorithmic flow chart of transmitter sub system. Communication channel between the transmitter sub system and central controller is a radio frequency interface using XBee modules. Transmitter sub system responds to two different kinds of commands. Mainly if the central controller request the generation of tracking signal, transmitter sub system emits 100ms ultrasonic sound burst in to the air. Controlling the power of ultrasonic burst also controlled according to the central controllers request.

3.3 Servo Controller Unit This circuit was designed to communicate with the laptop that is placed on the robot and orient the ultrasonic burst towards the receivers.

3.3.1 Power Supply Central controller is powered by mains supply. As ultrasonic receiver units are powered from central controller, 24V center tapped transformer is used to drop 230V. Single power supply of 5V is used to drive circuits in central controller while +12V and -12V DC voltage is send to ultrasonic receiver units.

3.3.2 Microcontroller PIC 16F876A is used as the microcontroller of the Central controller. Main task of it is to communicate with ultrasonic receivers and ultrasonic transmitter to synchronize them and then collect distance measurements from each receiver.

Figure 26: Schematic of Servo controller

3.3.3 PC USB Interface Central controller is connected to PC through USB connection. For this purpose separate PIC18F2550 microcontroller with USB capability is used and USB interface software is based on PicKit2 Software. Data is transferred through serial communication at 9600bps, and circuit will act as a serial to USB converter.

Figure 27: Schematic of USB interface circuit

CHAPTER 4

4.RESULTS AND DISSCUTIONMeasurements were taken in several stationary positions (50 positions) to estimate the Root Mean Square Error with extended Kalman filters. Average data and weighted average data was analyzed and following figure shows the occurrence pattern and the mean error of the data.

Figure 28: Occurrence graph

RMSE =

System was implemented and tested in an open ground which has minimal obstacle disturbances but high noise levels (light and sound) with about 1000m2 area and was able to achieve accuracy of 40-50cm with 80% confident level for stationary robot and while moving at 1ms-1 accuracy of 60cm is achieved with confident level of 80% which is acceptable accuracy to localize an outdoor robot.

CAPTER 5

5. CONCLUTION

In this research and development project I have worked on the ultrasonic sensor system to localize a robot in a predefined outdoor area using the minimum possible number of sensors.

The system proves to do position estimation of a robot with an acceptable accuracy by using this minimum number of sensor nodes.

Higher accuracy of 40-50cm was obtained for stationary positions, which suggests system is suitable for localizing slow moving robots such as grass cutters, Automated guided vehicles, combined harvesters etc.

Wind strength in the place is also a key factor which affects the accuracy. As the sound waves are propagated by moving air particles, strong winds can change the path of ultrasonic sound wave causing delayed response of the system. Therefore system's accuracy drops when implemented on outdoors where strong wind may occur.

REFERENCES

[i] L. Nissanka B. Priyantha, Anit Chakraborty, and Hari Balakrishnan, The Cricket Location-Support System, MIT Laboratory for Computer Science.

[ii] Bahl, P., and Padmanabhan, V. Radar: The Building RF-based User Location and Tracking System. InProc. IEEE INFOCOM (Tel-Aviv, Israel, Mar. 2000).

[iii] Want, R.; Hopper, A.; Falcao, V. & Gibbons, J. (1992). The Active Badge Location System. ACM Transactions on Information Systems, Vol. 10, Issue 1.

[iv] R.W.M.C.M.S. Kapukotuwe, M.A.U.S. Malasinghe, D.M.S. Palipana, P. Wijenayaka, S.R. Munasinghe, Self Localized Field Robot

[v] N. S. Kodippili, Dileeka Dias, Integration of Fingerprinting and Trilateration Algorithms for Improved Indoor Localization Performance

[vi] Krishna Chintalapudi, Anand Padmanabha, Iyer Venkata, N. Padmanabhan, Indoor Localization Without the Pain

[vii] 400SR160-400ST160 ultrasonic transducers datasheet

[viii] TL082 datasheet

[ix] http://ww1.microchip.com/downloads/en/DeviceDoc/PICkit2PCAppSourceV261.zip : Pickit2 source code

[x] Zsolt Parisek, Zoltn Ruzsa, Gza Gordos, Mathematical algorithms of an indoor ultrasonic localization system Bay Zoltn Foundation for Applied Research, Institute for Applied Telecommunication Technologies.

[xi] Motilal Agrawal; Kurt Konolige, Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS, SRI International

[xii] Gary Bishop, Greg Welch University of North Carolina at Chapel Hill, An Introduction to the Kalman Filter

[xiii] Welch, G.; Allen, B.; Ilie, A. & Bishop, G. (2007). Measurement Sample Time Optimization for Human Motion Tracking/Capture Systems, Proceedings of Trends and Issues in Tracking for Virtual Environments, Workshop at the IEEE Virtual Reality 2007

[xiv]PedroDavalos - Se,Lowe, Visionbased Mobile Robot Localization and Mapping using ScaleInvariant Features,LittleIEEEICRA,2001

APPENDICES

Receiver Code

#use rs232(baud=9600,parity=N,xmit=PIN_A0,rcv=PIN_A1,bits=8)

#define led pin_a2#define pulse pin_a3int16 time=0;char answer;void main(){ while(true){ do{ answer=getch(); }while(answer!='T'); set_timer1(0); while(input(pulse)&&get_timer1() 4mhz)#use delay(clock=20000000)#use rs232(baud=9600,bits=8,parity=N,xmit=PIN_A0,rcv=PIN_A1,ERRORS) #define PinServo0 PIN_A2 // servo pin definedint PosServo0;int i = 0;char direction='a';#int_TIMER1 // servo control timer interrupt void TIMER1_isr(void) {output_high(PinServo0);for (i=0;i