Project 2

Authors:

• Marwan Abbas Github Profile
• Omar Abu Gabal

Problem Statement:

Indoor positioning systems has been around for decades now, and it has been a hot topic in research eversince. But Indoor positioning systems has a huge overhead of collecting the data of the Received Signal Strength Indicator (RSSI) of WiFi inside the buildings, researchers have to walk through the whole building with a reader to read the RSSI, which is tedious. Our project is a proposed solution to help researchers with their mission, by collecting the RSSI of a floor automatically. Our system will have minimal human interaction, it would need the user to write a simple text file that describes the floor for the dagu to move accordingly. The text file would need to be saved on a Micro SD card, and inserted in the Micro SD Card Adapter. The user will then leave the dagu at the starting position, the dagu will then go through the whole floor stopping every 1 meter and buzz when it is done, the SD card will have a file called "wifidata.csv" that has all the WiFi points names and the respective RSSI.

Hardware Used:

• STM32
• ESP32
• dagu car
• Wheel Encoder
• Micro SD Card Module
• Pololu TReX DMC
• SN74HC00N chip

software components:

• STM32cubMX
• keil vision v5
• arduino IDE

Architecture:

Architecture of the system:

As shown in the figure bellow, there is a feedback loop between the STM32 and the ESP32 in order for the STM32 to notify the ESP32 when the Dagu is done with moving the 1 meter, and then the ESP32 notifies the STM32 that it is done collecting data and the Dagu can start moving again.

The wheel encoder is put on the Dagu wheels to calculate exactly how many times the wheel turned in order to calculate the distance that the Dagu moved to have accurate readings and localize the Dagu offline.

There's a MUX so that one Micro SD card is used for both reading the directions by the STM32 and writing the .csv file using the ESP32

The Pololu TRex DMC takes the commands from the STM32 UART to drive the motors of the Dagu

Software Architecture:

This is the flow of our software, we did not need to use the FREERTOS as we didn't find the need for it as we are communicating two devices together and there is no priorities in taks.

Hardware:

ESP32

The ESP32 is used because the STM32 does not have a WiFi module, so we used the ESP32 in order to collect the required data.

The WiFi library was used to get the SSID and the RSSI of the WiFi points visible to the ESP32.

The SD and SPI libraries were used to write the .csv file on the SD card.

Micro SD Card Reader Module

• This module was used to communicate with the Micro SD card through SPI.
• The module is used to read and write files through a FATFS file system, it can interface with a circuit board with 5V or 3.3V (used the 5V in this project)
• The communication interface is typical SPI interface.
• There are six pins as shown in the diagram below. GND, VCC, MISO, MOSI, SCK, CS.
• Voltage regulator for 4.5V ~ 5.5V down to 3.3V
• MicroSD card connector, self bomb deck, easy card insertion.
• Supported Card Types:
  • Micro SD Card (<=2G)
  • Micro SDHC Card (<=32G) (USED IN THIS PROJECT)
• Issues faced:
  • When interfaced with STM32 an old driver had to be installed
  • Formatting the MicroSD card to support FATFS
  • Doesn't support MicroSD cards with memory size greater than 32GB

Datasheet for reference Source of the picture

Multiplexer

Due to the lack of components we had to make our own multiplexer using NAND gates.

Used 4 SN74HC00N chip to construct the MUX

Architecure of one MUX

Architecure of the MUX in our system

Wheel Encoder

• The wheel Encoder is used to accuratly localize the dagu and know the exact distance that it should move before stopping.
• The wheel encoder is divided into 2 parts as we can see in the digram below, the firs part is the small wheel which will be placed beside the dagu wheel to move with the dagu acceleration and the other part is the chip, the chip has a reciver and transmerter which transmit light continusly.
• The wheel encoder has 3 pins, VCC which should be 3.3V, grnd and output pin.
• the output pin of the wheel encoder start with a high value and when the wheel starts to move and cut the light it changes states from high to low and then when the light is not being blocked anymore is goes back to high again
• the small wheel have 12 gaps and solid parts which make the entire wheel, so when the output pin state changes 12 times then we know that the dagu wheels have completed exactly 1 rotation
• we calculated the distance that the dagu moved by keeping track of the number of rotations that the wheels did and multipling that number by the radius of the wheel
• we calculated the angles in which the car should move for example 0 or 45 degrees by calculating the radius of the car and through it we calculated the arc that the car should move in to move exactly with the angle that we want
• the equation to move 1 meter forward is Distance = Number_of_revolutions * (12.5/100). Where 12.5 is the diameter of the wheel in cm and we devide it by 100 to make it into meters
• the equation to move Certain degree is Distance = Number_of_revolutions * (47/100) where 47 is the distance between two wheels or the Diameter of the whole car

Demo 1:

Dagu moving 1 meter

ESP32 data gathering

Final Demo:

Dagu moving according to input file

Challenges:

• Our main challenge was to insert the wheel encoder in the dagu, as the dagu wheels are connected directly to the DC motor
  1. The first solution was to change the DC motors in the dagu and use a DC motor that has a wheen encoder embedded in it
  2. The second solution was to modify the already existing wheels to put an encoder in it, which is the solution that we went with. After some research and help from Mechanical engineers we found a way to put the wheel encoder on the already existing wheels
• The SD card interface with the STM was not working as we were trying to make it work with the wrong drivers
• We needed to construct a MUX so that both ESP32 and STM32 read and write on the same MicroSD

Future work

For future engineers, we might need a more autonomous way to control the Dagu, maybe using cameras to detect doors and go through them. Also, another feature that would be extremely useful is obsticle detection, as this project would stop working if the user is not extremely precise with their commands.

We believe that this project would be beneficial because it will reduce the overhead of collecting the RSSI "WIFI signal strength at different location" to build the fingerprint of the building. by automating this process researchers can concentrate more on the different algorithms and techniques in which they can create to reduce the absolute mean error between the user location and the estimated location and try to create better techniques that can be robust to environment changes and can be generalized to different building at different locations.

Presentation MS2 Link

https://drive.google.com/file/d/1tfSCS1q_egZYdxbkJUDPdCJWKFP4syyZ/view?usp=sharing

Final Presentation Link

https://drive.google.com/file/d/1fyh6Bcv9o0Kg8UTmcHzeXHSopLF01OPG/view?usp=sharing

Resources

• wheel encoder
• ESP32 Datasheet
• STM32L432KC Datasheet
• Micro SD Card Module
• Micro SD Card Module