Welcome to our Senior Design Pi Car Home Page!
See what we have been up to this semester.
Are you new to the Raspberry Pi?
We’re here to fill you in.
A Raspberry Pi is a small computer that is often used to for programming and hardware projects. They are equipped with various input and output ports, such as USB, Ethernet, HDMI, audio, and GPIO (General Purpose Input/Output) pins, which allow users to connect various peripherals and sensors to create a wide range of projects.
Have you built a Rustler car before?
We will walk you through the basics.
- The Rustler car was gutted of its default remote control so that we could install the Raspberry Pi and various sensors into it.
- There is a “pi-hat” attached to the GPIO pins of the Raspberry Pi that offers the pins specifically for the Rustler car(servo, motor, encoder, etc.)
Overview
This project aims to create a fully autonomous Rustler car that can complete a designated path and avoid an obstacle by making a turn. It is accomplished through the implementation of a camera and LiDAR sensor. An image processing system was created that isolates a particular color and uses it to maintain a straightforward direction along the designated path. The LiDAR sensor provides real time distances between the car and surrounding objects. This is used to detect when there is an obstacle in the way of the car, and it indicates to the steering mechanism that a turn will be needed. All of the sensors were able to run concurrently through the use of Python multithreading. It was found that the camera imposed limitations on this design–as it did not take high quality images during cloudy conditions. Additionally, the image processing time impacted the speed of the Rustler car causing delayed response times for the steering. However, the car was able to complete the entire path with minimal error, deeming it a successful project. In the future, if this project were to be further elaborated upon, some places for improvement would be to use a higher quality camera and to explore different methods for optimizing the image processing time.