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Getting Started with Robotics

What is Linux?

Linux is an open-source operating system, created by Linus Torvalds in 1991, and is used on everything from personal computers to servers. Unlike DOS, which is a single-tasking, text-based operating system, Linux supports multitasking and multiuser operations. It offers both a graphical interface and a powerful command-line interface.

Installation 🛠️

For this robotics project, we will use Docker to set up our Linux environment. Docker is a platform that allows you to automate the deployment of applications inside lightweight, portable containers. These containers package everything you need to run the software, including the operating system, libraries, and dependencies, ensuring consistent performance across different environments.

Why Docker? 🐳

  • Consistency: Docker ensures that the software runs the same way, regardless of where it’s deployed.
  • Isolation: Each Docker container is isolated, preventing conflicts between different software environments.
  • Portability: Docker containers can be easily shared and run on any system with Docker installed, making it ideal for collaboration and deployment.

Installing Docker

Important

Ensure that Virtualtization is enabled in BIOS for Your system.

Windows

Important

Ensure that WSL is Enabled in your Windows.

  1. Download Docker Desktop: Go to the Docker Desktop for Windows download page.
  2. Install Docker Desktop: Run the installer and follow the on-screen instructions.
  3. Start Docker Desktop: After installation, Docker will start automatically. You can access it from the Start menu.
  4. Verify Installation: Open PowerShell and run the command: 
    docker run hello-world

Linux

  1. Update Your System: Open your terminal and run the following commands:

    sudo apt update
sudo apt upgrade

  2. Install Docker: Go to the Docker Desktop for Linux and follow the isntructions

  3. Verify Installation: Open PowerShell and run the command:

    docker run hello-world

MacOS

  1. Download Docker Desktop: Visit the Docker Desktop for Mac download page.
  2. Install Docker Desktop: Open the downloaded .dmg file and drag the Docker icon to your Applications folder.
  3. Start Docker: Launch Docker from your Applications folder. Docker will start running in the background.
  4. Verify Installation: Open PowerShell and run the command: 
    docker run hello-world

Cloning the Repository

Clone the repository on your local machine using the command:

git clone https://github.com/Robotics-Society-PEC/Getting-Started-With-Robotics.git

Building the Docker Image

Important

Ensure that you run this command from within the repository.

This repo provides a Docker image with ubuntu installed, To build the image run the command:

docker build -t <name_of_image> .

After the image is done building, you can enter the Linux enviornment using the command:

docker run -it <name_of_image>

Basic Linux Commands

Navigating the Filesystem 🗂️

Understanding how to navigate the filesystem is fundamental when working with Linux.

1. pwd (Print Working Directory)

The pwd command shows the full path of the current directory you are in.

pwd

Example: If you are in the /home/user/documents directory, running pwd will output:

/home/user/documents

2. ls (List Directory Contents)

The ls command lists all files and directories in the current directory.

ls

Example: To list files with details (like file size and permissions):

ls -l

3. cd (Change Directory)

The cd command changes the current directory to a different one.

cd /path/to/directory

Example: To move to the home directory:

cd ~

File Operations 📁

These commands help you create, move, and manage files and directories.

1. touch (Create a File)

The touch command creates an empty file.

touch filename

Example: To create a file named example.txt:

touch example.txt

2. mkdir (Create a Directory)

The mkdir command creates a new directory

mkdir directory_name

Example: To create a directory named projects:

mkdir project

3. cp (Copy Files)

The cp command copies files or directories from one location to another.

cp source_file destination

Example: To copy file.txt to another directory:

cp file.txt /home/user/documents

4. mv (Move/Rename Files)

The mv command moves or renames files or directories.

mv old_name new_name

Example: To move file.txt to another directory:

mv file.txt /home/user/documents

Or to rename file.txt to newfile.txt:

5. rm (Remove Files/Directories)

The rm command removes files or directories.

rm filename

Example: To remove a file named file.txt:

rm file.txt

To remove a directory and its contents:

rm -r directory_name

Linking Local Volume to DOcker using Docker Compose

Why Do We Need to Link Volumes?

When working inside a Docker container, you might create or modify files within the container's filesystem. However, these changes are isolated from your local machine, which means:

  • Files created or modified inside the container will not automatically appear in your local filesystem.
  • Git won't be able to track changes made inside the container since they aren't visible in your local directory.

To solve this, we can link a directory inside the Docker container to a directory on your local machine. This way, any changes made in the container will be reflected on your local machine, and vice versa.

What is Docker Compose? 🐳

Docker Compose is a tool that allows you to define and manage multi-container Docker applications. With Docker Compose, you can define all your services, networks, and volumes in a single YAML file. This simplifies the process of managing complex applications by allowing you to spin up an entire environment with a single command.

Setting Up Docker Compose

Let's set up Docker Compose to link your local volume with the Docker container.

1. Create a docker-compose.yml File

Create a new file named docker-compose.yml in your project directory. This file will define the Docker services and link the volumes.

services:
  robotics-env:
    build: .
    volumes:
      - ./workspace:/home/myuser/workspace
    stdin_open: true # Equivalent to `-i` in `docker run`
    tty: true # Equivalent to `-t` in `docker run`
    command: /bin/bash

Explanation:

  • stdin_open: true: This is equivalent to using the -i flag with docker run. It keeps the standard input (stdin) open even if not attached.
  • tty: true: This is equivalent to using the -t flag with docker run. It allocates a pseudo-TTY, which makes the terminal session interactive.
  • command: /bin/bash: Ensures that when the container starts, it opens a bash shell, allowing you to interact with the container.

2. Run Docker Compose

To start the container in interactive mode, simply use:

docker-compose up

This command will start your container as specified in the docker-compose.yml file, attaching the terminal to it, so you can interact with the shell inside the container.

3. Accessing the Container

Once the container is running, you should automatically be placed inside the container's bash shell, where you can run commands interactively.

Running in Detached Mode

If you later want to run the container in detached mode (not interactively), you can add the -d flag to the docker-compose up command:

docker-compose up -d

This runs the container in the background, freeing up your terminal for other tasks.

4. Creating a File inside the Container

Let's test this by creating a file inside the container and ensuring it's visible on your local machine.

  1. Inside the Docker Contianer: 
    touch /home/myuser/workspace/newfile.txt
  2. On your local machine: Check your ./workspace directory, and you should see newfile.txt there.

This synchronization ensures that all your work inside the Docker environment is consistent with your local development setup, making it easier to manage code and collaborate.

Compiling and Executing C Code

To work with C programs in a Linux environment, you'll need to know how to compile and run your code using the command line. Here's how you can do it:

1. Compiling the C Program

To compile the C program, you can use the gcc compiler, which is widely used in Linux environments. The general syntax for compiling a C program is:

gcc -o output_name source_file.c

For our example, compile the main.c file like this:

gcc -o hello hello.c
  • gcc: The GNU C Compiler.
  • -o hello: This specifies the output file name. In this case, the compiled program will be named hello.
  • hello.c: The source file you want to compile.

2. Executing the Compiled Program

Once your program is compiled successfully, you can run it using the following command:

./hello

This will execute the hello program and output:

Hello, World!

Examples

  1. Hello, World!
  2. Variables and Data Type
  3. If Else Statements
  4. While Loop
  5. For Loop
  6. Functions
  7. Arrays
  8. Structures
  9. Robot Simulation

Practice Question

2D Robot Simulation

Objective:

Create a simulation for a robot that can move in a 2-dimensional space. The robot should have the ability to move both horizontally (x-axis) and vertically (y-axis). After simulating the movement, calculate and print the total displacement of the robot from its starting position.

Instructions:

  1. Define a struct for the Robot:
  • The Robot struct should include:
    • name: The name of the robot.
    • x_position: The position of the robot on the x-axis.
    • y_position: The position of the robot on the y-axis.
    • x_speed: The speed of the robot along the x-axis.
    • y_speed: The speed of the robot along the y-axis.

  1. Create a function to update the robot's position based on its speed and the time interval.

  2. Create a function to print the robot's current position.

  3. Simulate the robot's movement over a series of time intervals (e.g., 10 intervals).

  4. Calculate the total displacement of the robot from its starting position. The displacement is the magnitude of the vector from the starting position (0, 0) to the final position (x_position, y_position) and can be calculated using the formula:

$$\text{Displacement} = \sqrt{(\text{x\_position})^2 + (\text{y\_position})^2}$$
  1. Print the robot's position at each time interval and the total displacement at the end.

Example Output:

  • Time Interval 1: Position (x, y) = (1, 2)
  • Time Interval 2: Position (x, y) = (2, 4)
  • ...
  • Total Displacement: 10.77 units

Additional Challenge:

Allow the robot to change its speed randomly at each time interval and observe how this affects its final displacement.

📝 License

This project is GPL-3 licensed.