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Multi-Sensor Integration and Fusion using PSoC

M.S. FINAL PROJECT REPORT

Submitted by

Student Name

Master of Science in Electrical and Computer Engineering

The Ohio State University, Columbus

Under the Guidance of

Dr. Lisa Fiorentini

Assistant Professor, Clinical

Department of Electrical and Computer Engineering

The Ohio State University, Columbus

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TABLE OF CONTENTS

ABSTRACT .................................................................................................................................................. 1

INTRODUCTION ........................................................................................................................................ 2

PROGRAMMABLE SYSTEM-ON-CHIP (PSoC) ...................................................................................... 2

MULTI-SENSOR SYSTEM ARCHITECTURE ......................................................................................... 5

ENCODERS ................................................................................................................................................. 7

TEMPERATURE SENSOR ......................................................................................................................... 8

ACCELEROMETER .................................................................................................................................. 10

MAGNETOMETER ................................................................................................................................... 11

GPS ............................................................................................................................................................. 13

REAL TIME CLOCK (RTC) ..................................................................................................................... 14

DATA LOGGING IN F-RAM ................................................................................................................... 15

COMMUNICATION WITH RASPBERRY PI ......................................................................................... 17

LIDAR ........................................................................................................................................................ 21

REFERENCES ........................................................................................................................................... 23

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LIST OF TABLES

Table 1: List of Hardware Components Used .............................................................................................. 5

Table 2: Encoder Color Code Description .................................................................................................... 6

Table 3: PSoC 4200M Pin Connections ....................................................................................................... 6

Table 4: Sensor Characters, Table 5: Special Characters ........................................................................... 18

LIST OF FIGURES

Figure 1: High Level Block Diagram of PSoC 4200M................................................................................. 3

Figure 2: CY8CKIT-044 PSoC 4 M-Series Pioneer Kit ............................................................................... 3

Figure 3: TopDesign Schematics of PSoC Creator Project .......................................................................... 4

Figure 4: Design Wide Resources of PSoC Creator Project ......................................................................... 5

Figure 5: A and B Channel Encoder Output Waveforms ............................................................................. 7

Figure 6: Quadrature Decoder Component Configuration ............................................................................ 7

Figure 7: TMP102 Internal Register Structure.............................................................................................. 8

Figure 8: I2C Component Configuration ...................................................................................................... 9

Figure 9: I2C Timing Diagram to Read data from TMP102 ........................................................................ 9

Figure 10: I2C Timing Diagram for ADXL345 .......................................................................................... 10

Figure 11: Internal Schematic diagram of HMC5883L .............................................................................. 12

Figure 12: Raw NMEA Sentences transmitted by the GPS ........................................................................ 14

Figure 13: RTC Component Configuration ................................................................................................ 15

Figure 14: Timing Diagram to write data into F-RAM............................................................................... 15

Figure 15: Timing Diagram to read data from F-RAM .............................................................................. 16

Figure 16: Bridge Control Panel to read data from F-RAM ....................................................................... 16

Figure 17: UART Component Configuration ............................................................................................. 17

Figure 18: Example communication packets between Raspberry Pi and PSoC ......................................... 19

Figure 19: PSoC Firmware Flowchart for communication and unparsing ................................................. 20

Figure 20: LIDAR Lite Block Diagram ...................................................................................................... 21

Figure 21: PSoC 4 I2C Component Configuration for LIDAR .................................................................. 22

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ABSTRACT

Multi-Sensor Integration and Fusion subsystem is a part of the multidisciplinary research project

Unmanned Ground Vehicle (UGV) and Aerial (UAV) Vehicle Swarms. In order for autonomous

navigation, path planning and target identification of the autonomous vehicles, various sensors

measurements are required. A PSoC 4 (Programmable System-on-Chip) from Cypress

Semiconductors was used to interface various sensors. The PSoC 4 is based on ARM Cortex M0

architecture along with the integration of programmable analog and digital blocks. The PSoC 4

acts as a coprocessor collecting all the sensor data in real time and communicating it to Raspberry

Pi which performs high level controls based on the sensor measurements. The sensor data is also

logged in an external memory, a 256 K byte F-RAM available on the PSoC 4 Development Kit. A

specific communication scheme was also developed on top of UART protocol between the PSoC

4 and Raspberry Pi to transfer specific sensor readings requested by Raspberry Pi.

Multiple sensors like Motor Encoders, IMU, GPS, Temperature Sensor and LIDAR were

successfully interfaced with PSoC 4. The Motor Encoders consists of hall effect sensors which

produces a pulse every time the motor rotates, the counters in PSoC 4 are used to count these

pulses to determine the rpm of the motor and hence the wheel. The IMU consists of a combination

of Accelerometer and Magnetometer to measure the linear acceleration and orientation of the robot

with respect to the Earth’s Magnetic field essentially a compass pointing towards the north

direction. The temperature sensor is used to measure the ambient temperature. GPS gives the

position of the robot in terms of longitude and latitude. In addition to the position, the speed of the

robot can also be measured and the UTC time from the GPS is used to lock the RTC time of PSoC

4 for the time stamp of the sensor readings. LIDAR is used to detect obstacles in front of the robot.

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INTRODUCTION

Multi-Sensor integration refers to the process of using of multiple sensors to obtain more accurate

and reliable information regarding the system and its environment. Multi-Sensor fusion refers to

the process of combining the information from various sensors and representing it in a common

format understandable to the main processor which will take decisions based on the sensor data.

The acquisition of sensor data must be done in real-time in order to make the decisions at the right

time. The time at which the each sensor data is acquired must also be included in the data format

to be sent to the main processor. In addition to sending the sensor data to the main processor, it

must also be logged in an external memory.

In this project, the main processor is a Raspberry Pi 2 and a PSoC 4200M performs the multi-

sensor integration and fusion in real-time and sends the fused sensor data to Raspberry Pi. The

sensors currently integrated with the PSoC 4200M are,

1. Motor Encoders

2. Temperature Sensor

3. Accelerometer

4. Magnetometer

5. GPS

6. LIDAR

PROGRAMMABLE SYSTEM-ON-CHIP (PSoC)

The PSoC 4200M device from Cypress Semiconductors is a mixed signal system on chip based

on 32-bit Arm Cortex M0 architecture with programmable analog and digital blocks as depicted

in the high level block diagram in Figure 1. Multiple sensors, both analog as well as digital sensors

can be interfaced with PSoC 4200M to acquire sensor data in real-time. The programmable analog

and digital blocks operate independently along with the CPU of the PSoC [1]. This enables

acquisition of data from multiple sensors, formatting of sensor data and communication with the

main processor in parallel. The PSoC 4200M device also contains a Real Time Clock (RTC) which

is used to time stamp the sensor data.

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Figure 1: High Level Block Diagram of PSoC 4200M

CY8CKIT-044 PSoC 4 M-Series Pioneer Kit shown in Figure 2 features a PSoC 4200M device

which is used in this project to interface with the various sensors and the Raspberry Pi. This

development kit also contains an on-board programmer and debugger and therefore no additional

hardware is required to program and debug the PSoC 4200M device [2].

Figure 2: CY8CKIT-044 PSoC 4 M-Series Pioneer Kit

PSoC 4200M

ARM Cortex M0

Programmable Analog Blocks

RTC

Programmable Digital Blocks

Sensor Inputs

Sensor Data to Raspberry Pi

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The firmware for the PSoC 4200M device was developed using the PSoC Creator IDE (Version –

3.2 SP1). The PSoC Creator contain PSoC components which are virtual ICs which users can drag

and drop into a design and configure them to meet the application requirements. Every PSoC

component comes with its own set of API libraries [3]. PSoC Creator is free to use and can be

downloaded from the following link, www.cypress.com/PSoCCreator.

Figure 3 shows the top design schematics of the PSoC Creator developed for Multi-Sensor

Integration and Fusion project.

Figure 3: TopDesign Schematics of PSoC Creator Project

Figure 4 shows the design wide resources of the PSoC Creator developed for Multi-Sensor

Integration and Fusion project.

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Figure 4: Design Wide Resources of PSoC Creator Project

MULTI-SENSOR SYSTEM ARCHITECTURE

The Multi-Sensor system architecture with the interconnections between the multiple sensors and

PSoC 4200M development kit is shown in figure 5. The Temperature sensor and the Accelerometer

both use I2C interface and are connected in the same I2C bus with the PSoC 4200M. The PSoC

4200M identifies the respective sensor with its unique I2C address.

Table 1 lists all the hardware components used in the Multi-Sensor system architecture along with

their web links. The TMP102, ADXL345 and HMC5883L sensor breakout boards from SparkFun

are used in this project.

Table 1: List of Hardware Components Used

Component Description Web link

CY8CKIT-044 PSoC 4200M Development Kit www.cypress.com/CY8CKIT-044

Raspberry Pi 2 Main Processor www.raspberrypi.org

Encoders 48 CPR Quadrature Encoder www.pololu.com/product/2275

TMP102 Digital Temperature Sensor www.sparkfun.com/products/11931

ADXL345 3-Axis Accelerometer www.sparkfun.com/products/9836

HMC5883L 3-Axis Magnetometer www.sparkfun.com/products/10530

GPS Ultimate GPS module www.adafruit.com/products/746

LIDAR LIDAR Lite www.sparkfun.com/products/retired/13167

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Table 2 describes the color code functionality of connecting wires in the encoder which is obtained

from Pololu Robots and Electronics. Table 3 gives the pin connection details between the different

components and PSoC 4200M in the Multi-Sensor system architecture.

Table 2: Encoder Color Code Description

Color Function

Red Motor power (connects to one motor terminal)

Black Motor power (connects to the other motor terminal)

Green Encoder GND

Blue Encoder VCC (3.5 – 20 V)

Yellow Encoder A Output

White Encoder B Output

Table 3: PSoC 4200M Pin Connections

Component Pin PSoC 4200M Pin

Encoder 1 Encoder A Output P2.0

Encoder B Output P2.1

Encoder 2 Encoder A Output P2.2

Encoder B Output P2.3

Temperature

Sensor

SDA P4.1

SCL P4.0

Accelerometer SDA P4.1

SCL P4.0

Magnetometer SDA P4.1

SCL P4.0

GPS UART TX P1.1 (UART RX)

UART RX P1.0 (UART TX)

LIDAR SDA P6.1

SCL P6.0

Raspberry Pi 2 GPIO 14 (UART TX) P3.0 (UART RX)

GPIO 15 (UART RX) P3.1 (UART TX)

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ENCODERS

An encoder is an electromechanical device used to measure the position and speed of a motor shaft.

The motors used in the robot contain a two-channel Hall-effect sensor encoder which outputs

square waves corresponding to the rpm (rotations per minute) of the motor shaft [5]. The outputs

of the two channels are 90 degrees out of phase which refers to a quadrature encoder as shown in

Figure 5.

Figure 5: A and B Channel Encoder Output Waveforms

PSoC Creator offers a quadrature decoder component as shown in Figure 6 which is used to acquire

data from the two channel encoders. The encoding mode in the component is set to 4x which offers

highest resolution by counting both the rising and falling edges of both the square waves to provide

the count value output [4a].

Figure 6: Quadrature Decoder Component Configuration

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The Counter_X_ReadCounter() API is used to read the current counter value from the quadrature

encoder. The difference between the encoder values is computed by reading the encoder values at

two different times with a given time interval which is then formatted and sent to the Raspberry

Pi.

TEMPERATURE SENSOR

The temperature sensor used in this project is TMP102, which is a digital temperature sensor with

I2C interface. The TMP102 has a resolution of 0.0625°C, and accuracy of 0.5°C over the

temperature range of -25°C to +85°C [6].

Figure 7 shows the internal register configuration of the temperature sensor. To read the current

temperature from the sensor, the pointer register must first be initialized to point to the address of

the temperature register. After pointing to the temperature register, data can be read from the

temperature register. Two bytes of data must be read from the temperature register which

corresponds to the MSB and LSB of the temperature reading.

Figure 7: TMP102 Internal Register Structure

The PSoC 4200M communicates with the TMP102 sensor via I2C interface. The PSoC 4200M is

configured as an I2C master with 100 Kbps data rate as shown in Figure 8. To communicate with

the slave I2C sensor, the master should know the I2C address of the slave. For TMP102 sensor,

the 7-bit I2C address is 0x48 which is provided in the datasheet of the sensor. The I2C timing

diagram to read data from TMP102 is shown in Figure 9.

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Figure 8: I2C Component Configuration

Figure 9: I2C Timing Diagram to Read data from TMP102

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Following is the sequence of steps followed in the firmware to get the temperature reading:

1. Initialize the 8-bit pointer register to “00” to point to the temperature register using the API,

I2C_I2CMasterWriteBuf

2. Read two bytes of data from temperature register using the API, I2C_I2CMasterReadBuf [4b]

3. Combine the MSB and LSB of the temperature reading

4. Shift left the combined data by 4 bits and multiply by 0.0625 to get the current temperature

5. Compute the difference between two temperature readings in a given time interval which is

then formatted and sent to the Raspberry Pi

ACCELEROMETER

The accelerometer used in this project is ADXL345, which is a 3-axis MEMS accelerometer with

13-bit resolution and measurement at up to +/-16 g. Digital output data is formatted as 16-bit twos

complement and is accessible through either a SPI (3- or 4-wire) or I2C digital interface. The

ADXL345 automatically modulates its power consumption in proportion to its output data rate

which can be configured.

Registers 0x32 to 0x37 inside the ADXL345 holds the output data for each axis. Two 8-bit registers

hold the data for one axis. Register 0x32 and Register 0x33 hold the output data for the x-axis,

Register 0x34 and Register 0x35 hold the output data for the y-axis, and Register 0x36 and Register

0x37 hold the output data for the z-axis [7].

The PSoC 4200M communicates with the ADXL345 sensor via I2C interface. The accelerometer

is connected to the same I2C bus as the temperature sensor. For ADXL345 sensor, the 7-bit I2C

address is 0x53 which is provided in the datasheet of the sensor. The I2C timing diagram for

ADXL345 is shown in Figure 10.

Following is the sequence of steps followed in the firmware to get the accelerometer reading:

1. Initialize the accelerometer by first going into standby mode

Figure 10: I2C Timing Diagram for ADXL345

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2. Configure the accelerometer in full resolution, 100 Hz data rate, stream mode and measurement

mode

3. Read data from two registers corresponding to each axis

4. Combine the data from the two registers for each axis to get the current reading for the

respective axis

5. Compute the difference between two accelerometer readings in a given time interval which is

then formatted and sent to the Raspberry Pi

MAGNETOMETER

The magnetometer used in this project is HMC5883L, which is a 3-axis magnetometer from

Honeywell. The HMC5883L contains a high-resolution HMC118X series magneto-resistive

sensors plus an integrated application specific processor for amplification, automatic degaussing

strap drivers, offset cancellation, and a 12-bit ADC that enables 1° to 2° compass heading

accuracy.

Digital output data is formatted as 16-bit twos complement and is accessible through e I2C digital

interface.

Registers 0x03 to 0x08 inside the HMC5883L holds the output data for each axis. Two 8-bit

registers hold the data for one axis. Register 0x03 and Register 0x04 hold the output data for the

x-axis, Register 0x07 and Register 0x08 hold the output data for the y-axis, and Register 0x05 and

Register 0x06 hold the output data for the z-axis.

The PSoC 4200M communicates with the HMC5883L sensor via I2C interface. The magnetometer

is connected to the same I2C bus as the temperature sensor and the accelerometer. For HMC5883L

sensor, the 7-bit I2C address is 0x1E which is provided in the datasheet of the sensor [8].

Figure 11 shows the internal schematics of the HMC5883L magnetometer sensor along with the

example connection with the I2C Master which in this case is a PSoC 4200M.

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Following is the sequence of steps followed in the firmware to get the magnetometer reading:

1. Initialize the magnetometer by first going into standby mode

2. Configure the magnetometer in full resolution, 100 Hz data rate and continuous measurement

mode

3. Read data from two registers corresponding to each axis

4. Combine the data from the two registers for each axis to get the current reading for the

respective axis

5. Compute the difference between two magnetometer readings in a given time interval which is

then formatted and sent to the Raspberry Pi

The magnetometer readings are not tilt compensated, however since the accelerometer reading is

also available to the main processor which is a Raspberry Pi, it can perform tilt compensation using

both the magnetometer and accelerometer reading to perform tilt compensation and calculate the

true reading when the magnetometer is not lying flat which is usually the case in off terrain

environment.

Figure 11: Internal Schematic diagram of HMC5883L

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GPS

The GPS module used in the project is the Ultimate GPS module from Adafruit which is a breakout

board with the MTK3339 chipset, which is a high-quality GPS module that can track up to 22

satellites on 66 channels, has an excellent high-sensitivity receiver (-165 dB), and a built in

antenna. The GPS module also has built in data logging ability and can be powered using a CR1220

coin cell to keep the RTC running. The GPS module also contains an LED which blinks at about

1Hz while it's searching for satellites and blinks once every 15 seconds when a fix is found to

conserve power [9].

The GPS module transmits the received messaged through UART interface. The default baud rate

of the GPS module is 9600 bps. GPS modules start transmitting data as soon as they are powered

on and try to get a 'fix' (location verification). The data transmitted by them is the raw GPS "NMEA

sentence" output which contains multiple different kinds of NMEA sentences [10]. The two

NMEA sentences used in this project are the $GPRMC (Global Positioning Recommended

Minimum Coordinates) and the $GPGGA sentences. These two provide the time, date, latitude,

longitude, altitude, estimated land speed, and fix type. Fix type indicates whether the GPS has

locked onto the satellite data and received enough data to determine the location (2D fix) or

location + altitude (3D fix).

The PSoC 4200M communicates with the GPS module via UART interface which is configured

at 9600 baud rate [4c]. The PSoC firmware contains a function called GetGPSMessage() which

extracts the required information such as longitude, latitude, altitude, speed an UTC time. The

UTC time can also be used to initialize the RTC of PSoC 4200M since RTC resets the time every

time power is turned off to the PSoC.

Figure 12 shows an example of the raw GPS NMEA sentences transmitted by the GPS module.

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Following is the sequence of steps followed in the firmware to get the GPS readings:

1. Start the UART component which is configured at 9600 baud rate

2. Store the raw NMEA sentences in a buffer using UART_G_GetChar() API until one complete

set of NMEA sentences are received

3. Check whether a fix is obtained from the received NMEA sentences

4. If a fix is obtained, call the GetGPSMessage() function

5. The GetGPSMessage() function first extracts the $GPRMC and the $GPGGA sentences from

the raw NMEA sentences

6. The GetGPSMessage() function then extracts the longitude, latitude, altitude, speed and UTC

time from $GPRMC and $GPGGA sentences

REAL TIME CLOCK (RTC)

The data acquired from all the sensors is formatted into a common format along with a time stamp

at which the sensor data was acquired.

The RTC component in PSoC Creator as shown in Figure 13 is used obtain the current time. The

RTC_GetHours, RTC_GetMinutes, RTC_GetSecond APIs are used to get the hours, minutes and

seconds respectively from the time value passed from the RTC_GetTime() API [4d]. The time in

hours: minutes: seconds is then added to the sensor data which is then sent to the Raspberry Pi.

Figure 12: Raw NMEA Sentences transmitted by the GPS

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Figure 13: RTC Component Configuration

DATA LOGGING IN F-RAM

The CY8CKIT-044 also provides onboard memory storage via Cypress’s non-volatile F-RAM

device of 1 Mb capacity [11]. The F-RAM is connected to the I2C interface of the PSoC 4200M

device with a 7-bit I2C address of 0x50. It is used for data logging in this project. The combined

sensor data from all the sensors along with the timestamp is stored in the F-RAM.

Figures 14 and 15 show the timing diagram for write and read operations using F-RAM.

Figure 14: Timing Diagram to write data into F-RAM

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Figure 15: Timing Diagram to read data from F-RAM

The data stored in the F-RAM can later be read using the Bridge Control Panel software available

along with the installation of PSoC Creator [2]. Connect the Kit to PC using USB cable and in the

Bridge Control Panel, select KitProg and once it connects read data from the F-RAM using the

command, w 50 00 00 r 50 x x x x x x x x x x x x x x x p as shown in Figure 16.

The above command reads 15 bytes of data starting from the memory location with address 00. To

read data from a different memory location, specify the two byte address after w 50 followed by

the rest of the command.

Figure 16: Bridge Control Panel to read data from F-RAM

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COMMUNICATION WITH RASPBERRY PI

The PSoC 4200M communicates with the Raspberry Pi via UART interface. The UART

component in PSoC 4200M is configured at 115200 baud rate as shown in Figure 17. Customized

handshake control is implemented while communicating with the Raspberry Pi.

Figure 17: UART Component Configuration

All the sensor data and timestamp information are in hexadecimal representation which are

converted to ASCII characters using sprintf function to send the data over UART.

Note that the acquisition of sensor data, formatting and data logging continues irrespective of the

handshake control status i.e., the PSoC 4200M will not be idle until it receives a start from the

Raspberry Pi. It will continue to perform other functions in parallel.

Once the Raspberry Pi receives the sensor data, it decodes the data format and makes decisions

based on the individual sensor data.

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The following tables give the characters chosen for different sensors and also for additional details like timestamp and sensor data

logged for a given time duration,

Table 4: Sensor Characters Table 5: Special Characters

# Sensor Sensor

Reading

Character Example data

1 Encoders Left Encoder EL 2489

Right Encoder ER -1672

2 Accelerometer X-Axis AX 212

Y-Axis AY -163

Z-Axis AZ 12

3 Magnetometer X-Axis MX 253

Y-Axis MY 26

Z-Axis MZ -45

4 GPS Latitude GX 4000.175N

Longitude GY 08234.134W

Altitude GZ 545.4

Speed GS 022.4

Time GT 12:35:19

5 Temperature Sensor Temperature TE 23.24

6 Time Stamp - TS 00:01:30

# Additional Readings Character

1 Timestamp TS

2 All Sensors AL

3 Previous Sensor Data PR XX 05*

4 End Character !!

* XX – Respective Sensor Character

followed by the time duration in seconds

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Example: Raspberry Pi sends the command ELERGXGY!! to request the Encoder and GPS data from the PSoC and the PSoC

responds with the respective sensor data along with timestamp as shown in Figure 18.

Figure 18: Example communication packets between Raspberry Pi and PSoC

UART Settings for communication between Raspberry Pi and PSoC:

Baud rate: 115200 bps (bits per second)

Data bits: 8 bits

Parity: None

Stop bits: 1

Following is the representation of each of the sensor reading:

Encoder Data: ± Number of ticks in 100ms (example: 2489, -1672)

Accelerometer (units in G-forces (g)) and Magnetometer (units in micro Tesla): ±Reading for each axis (example: 212, -163)

GPS Example Readings

Latitude: 4000.175N (Latitude 40 degrees 00.175 minutes North)

Longitude: 08234.134W (Longitude 082 degrees 34.134 minutes East)

Altitude: 545.4 (Meters, above mean sea level)

Speed: 022.4 (Speed over the ground in knots)

Time: 12:35:19 (UTC time)

Temperature: ± reading in degree Celsius (example: 23.24, -2.58)

Time Stamp: Hours:Minutes:Seconds (example: 00:01:30)

EL ER GX GY !!

EL 1234 ER 1234 GX 4000.175N GY 08234.134W TS 00:01:30 !!

Raspberry Pi

PSoC

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Figure 19 shows the flowchart for the communication and unparsing firmware functions.

Figure 19: PSoC Firmware Flowchart for communication and unparsing

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LIDAR

LIDAR is an optical distance measurement technology that uses laser to determine the distance

from targets. LIDAR is useful because of its high accuracy over long ranges. The module used in

this project is the LIDAR Lite sensor from PulsedLight [12]. It is a compact, low cost, and low

power proximity sensor with a range of up to 40 meters with an accuracy of ±2.5cm. It can be

interfaced with a microcontroller through either the I2C or PWM interfaces. I2C is used in this

project as the internally processed distance measurements can be read directly from registers in

the LIDAR lite module, and this reduces the work of the microcontroller.

In principle, the LIDAR lite measures distance based on the precise measurement of the time delay

between the transmission of a laser signal and its reception. The high accuracy is achieved by the

digitization and averaging of two signals – a reference signal emitted by the transmitter before

distance measurement, and a received signal reflected from the target. The time delay between

these signals is estimated through an accurate correlation algorithm. This time delay is then

translated to a distance measurement based in the known speed of light. All signal processing is

dine internally on the Signal Processing Core, and the measured distance values on internal

registers which can be accessed through the I2C interface as shown in Figure 20. The default slave

address for the LIDAR lite is 0x62.

Figure 20: LIDAR Lite Block Diagram

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Figure 21 shows the I2C PSoC Creator component configuration for interfacing with LIDAR.

Figure 21: PSoC 4 I2C Component Configuration for LIDAR

Following is the sequence of steps followed in the firmware to get the distance reading:

1. Write the value ‘0x04’ to register ‘0x00’ to initiate a DC stabilization cycle, signal acquisition

and data processing.

2. Wait until an ACK is received. The unit responds with a NACK to read or write commands

with a NACK when it is busy processing.

3. Initiate a 2 byte read starting at register ‘0x8f’ and store the received bytes separately. These

are the upper and lower bytes of the distance in centimeters.

4. Combine the upper and lower bytes to get the measured distance.

Future work:

The LIDAR lite module does not include a motor that can allow the sensor to scan a wide area.

Hence, it will be useful to mount the LIDAR lite on a rotating platform attached to a servo motor

to enable the sensor to scan either a 180º forward view or an entire 360º view to create a 2D map

of all the obstacles around the vehicle based on its current position. This data can be further utilized

to perform Simultaneous Localization and Mapping.

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REFERENCES

1. PSoC 4200M Datasheet

www.cypress.com/file/139956/download

2. User Guide of CY8CKIT-044

www.cypress.com/file/157906/download

3. PSoC Creator Quick Start Guide

www.cypress.com/file/195271/download

4. PSoC Creator Component Datasheets

a. Quadrature Decoder

b. I2C

c. UART

d. RTC

5. Encoder Specifications

www.pololu.com/product/2275

6. TMP102 Datasheet

www.sparkfun.com/datasheets/Sensors/Temperature/tmp102.pdf

7. ADXL345 Datasheet

www.sparkfun.com/datasheets/Sensors/Accelerometer/ADXL345.pdf

8. HMC5883L Datasheet

cdn.sparkfun.com/datasheets/Sensors/Magneto/HMC5883L-FDS.pdf

9. Adafruit Ultimate GPS

learn.adafruit.com/adafruit-ultimate-gps/overview

10. GPS - NMEA sentence information

aprs.gids.nl/nmea/

11. F-RAM Datasheet

www.cypress.com/file/41666/download

12. LIDAR lite v1 Operating Manual

github.com/PulsedLight3D/LIDAR-Lite-Documentation/blob/master/Docs/LIDAR-Lite-v1-

docs.pdf