ECE434 Project - Vehicle Telemetry

Embedded Linux Class by Mark A. Yoder

Team members: Jason Su Harris Wu

Grading Template

I'm using the following template to grade. Each slot is 10 points. 0 = Missing, 5=OK, 10=Wow!

Add Extras

09 Executive Summary
09 Packaging
09 Installation Instructions 
09 User Instructions
09 Highlights
09 Theory of Operation
09 Work Breakdown
09 Future Work/Conclusions
09 Hackster.io
09 Demo/Poster
00 Not Late

Score:  90/100

Executive Summary

Use extended Kalman filter to integrate GPS and IMU data to achieve a decimeter level accuracy for the position and velocity of a vehicle. Combine with data logged from the CAN bus to build a server as a platform for implementing some apps, such as lap time, accel/brake time for analysis purpose. .

Progress:

We have made a Kalman filter on MATLAB, and have it running on BeagleBone using simulated data.

We have made the GPS sensor working on the BeagleBone, and read from it at a desire interval.

We have made a server using Flask to hold webpage for dynamic visualizing data on wsl.

We have designed and ordered a PCB for BeagleBone with GPS, IMU and CAN transceivers.

We have OBDII working, and is able to log engine RPM of my car.

End with a two sentence conclusion.

The sentence count is approximate and only to give an idea of the expected length.

Packaging

A beaglebone cape with IMU, GPS and CAN transceiver.

GPS breakout board: https://www.adafruit.com/product/746

IMU breakout board: https://www.amazon.com/HiLetgo-MPU-6050-Accelerometer-Gyroscope-Converter/dp/B078SS8NQV

CAN transceiver: https://www.ti.com/product/SN65HVD230

Installation Instructions

Hardware

1. Connect GPS to UART

2. Connect IMU to I2C2

3. Connect CAN to CAN1

Software

1. Put BB-I2C2-MPU6050 into uEnv.txt and reboot.

2. Get the project:

$ git clone git@github.com:Sqzlnsy/ece434Project.git

3. Run ece434Project/install.sh and you can go to step 7

4. Set up MPU6050 on I2C2 at 0x68:

  $ cd /sys/class/i2c-adapter/i2c-2
  $ echo mpu6050 0x68 > new_device

5. Install gpsd:

  $ sudo apt-get install gpsd

6. Install python-can:

  $ pip install python-can

7. Config gpsd:

  $ nano /etc/default/gpsd

You will see the config file and change DEVICES="/dev/ttyS0" to the port you use. (ttyS0 is uart1)

8. Run setup.sh

git site: https://github.com/Sqzlnsy/ece434Project

User Instructions

1. Go to the project directory

   $ cd ece434Project

1. Run make to compile if needed

   $ make   

3. Check the status gpsd:

  cgps  //It may take a couple of minutes for the GPS to capture enough satellites depending on the weather and area. 

4. Connect to the OBDII port on your car.

5. Check the connection of CAN bus:

  candump can1

6. If you can see gps information using cpgs, and can messages using candump, you are ready to start the program.

7. Run run_background.sh (Terminate the program by run process_terminate.sh)

8. Go to http://192.168.7.2:8081/ to see the real-time visualized data

Highlights

Here is where you brag about what your project can do.

Include a YouTube demo the audio description.

Theory of Operation

Give a high level overview of the structure of your software. Are you using GStreamer? Show a diagram of the pipeline. Are you running multiple tasks? Show what they do and how they interact.

Work Breakdown

List the major tasks in your project and who did what.

Also list here what doesn't work yet and when you think it will be finished and who is finishing it.

Future Work

The extended Kalman filter still needs more work to provide higher accuracy.

Conclusions

Give some concluding thoughts about the project. Suggest some future additions that could make it even more interesting.

---

Embedded Linux Class by Mark A. Yoder