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Fall 2024 Application for the Software Team of the Machine Intelligence Laboratory

(due Sunday, August 25th, 2024 at 11:59PM EST)

Hello! Thanks for checking our lab, we appreciate your interest in applying to work with us. To gauge the skills of our software members, we ask all incoming applicants to complete a short coding challenge to assess their skills at programming. This helps us ensure that all our members have a baseline requisite of experience.

In this challenge, you will be asked to create a simple simulation of a robot moving through a course, using a system similar to the Robot Operating System (ROS), which we use in our lab.

Background

One important part of a robot is communication between its different software components. One component might be responsible for moving the robot, another for processing sensor data, and another for making decisions based on that data. In ROS, these components communicate with each other by publishing and subscribing to topics. A topic is a channel of communication that allows different components to send and receive messages.

In this challenge, you will be asked to create a simple simulation of a robot moving through a course. The robot will have a camera that can detect the color of the course, and it will use this information to navigate through the course. The robot will publish its position to a topic, and other components will subscribe to this topic to get the robot's position.

Setup Requirements

Before you start working on this project, make sure you have the following:

  • Python 3.7 or higher
  • git

Getting Started

  1. Clone this repository:
git clone https://github.com/uf-mil/fall-24-app.git
cd fall-24-app
  1. Create a new repository (name can be whatever you'd like), but please make sure that the repository is private!
  2. (optional) Create and activate a Python virtual environment
  3. Install the required packages into your project (listed below). You are free to install any other packages to aid you with your project.
pip install pygame numpy
  1. Run the tests:
python3 -m unittest

Implementation

You will be developing your implementation in two files: pubsub.py and path_following.py.

Publishing and subscribing (pubsub.py)

The skeletons for three classes are given for you; you need to fill them out. A brief description of the goals of each class is given below.

  • Topic: A topic should be initialized with a string (the name of the topic). In addition, it should hold an array of subscriber objects whose callback function is called every time data is published to the topic.
  • Subscriber: A subscriber should be initialized by passing in a topic and a callback function. A subscriber listens for new data published to a topic that triggers its callback function.
  • Publisher: A publisher should be initialized with a topic. The purpose of a publisher is to push new data into a topic to trigger all the callback functions from the subscribers stored in the topic.

These terms are derived from ROS, so feel free to explore documentation or diagrams about publishing/subscribing in ROS for more context.

Path Following (path_following.py)

For your simulation, we will provide you with the pygame loop to test out your code. Your assignment will require you to fill in the PathFollowing.main function with the expected mechanisms:

  • Your class is given the topic to send position updates to, along with the topic where camera data is being published. The camera data given to you is a 20x20 square around the robot. Furthermore, you should apply the given delay between each movement. If delay is 1, then you should wait one second in between each movement.
  • You can move as many spaces as you'd like at once, but you must move in a straight line. You can only move in the four cardinal directions (up, down, left, right).
  • You should stop moving when you reach the end of the course, and your main function should return.
  • You should publish your position to the topic given to you in the constructor.

You may create any necessary helper files, classes, and methods if necessary.

Evaluation

We will provide you with one sample course to test your code, but upon submission your code will be tested against a number of hidden test cases to evaluate the robustness of your path following algorithm (in addition to the aforementioned conditions for each file). Furthermore, we have provided an additional test to test the functionality of topics.

Also, please don't worry if you are unable to complete the entire project/pass the test cases. We are primarily focused on your thought process and your approach to the problem!

Submission

When you are ready to submit your project, follow these steps:

  1. Push your changes to your new repository:
git remote set-url origin https://github.com/<username>/<repo_name>.git
git push -u origin main
  1. Invite the following users to your GitHub repository:
  • cbrxyz (Cameron)
  • DaniParr (Daniel)
  1. Fill out the application form with the link to your repository. Congrats, you're done!

Additional Notes

  • You are free to use any resources you'd like to complete this project, but please do not copy code from other sources. We want to see your own work!
  • You are welcome to use AI tools, but they are not necessary to complete this project. This should go without saying, but please do not use AI tools to write the entire solution for you.
  • If you have any questions, please reach out to us via Discord or email (cbrown14 at ufl dot edu or dparra1 at ufl dot edu).

Good luck from all of us!

~ Andrew, Cameron, Daniel, Keith, and the rest of the Machine Intelligence Laboratory