Herbie the Self-Driving RC Car

This Python library is designed to help you build and control a self-driving RC car using a Raspberry Pi. Whether you're a beginner or an experienced, this library provides a modular framework that allows you to mix and match various components, such as sensors, cameras, controller types, and drive trains, to create your own customized self-driving RC car.

Table of Contents

• Features
• Installation
• Usage
• Examples
• License

Features

• Modular architecture: Easily swap out or add new components to your RC car setup.
• Self-driving capability: Implement autonomous driving algorithms using the library's sensor and camera modules.
• Manual control: Use a controller to take the wheel when you want to drive the car manually.
• Extensible: Create custom components or algorithms to expand the functionality of your RC car.
• User-friendly: Designed with simplicity in mind to make it accessible to hobbyists and learners.

Installation

1. Clone this repository to your Raspberry Pi:

   git clone https://github.com/Caleb646/Herbie.git
   cd Herbie

2. Basic Install:

   pip install .

3. Install with PiCamera:

   pip install[PiCamera] .

4. Install with TFLite:

   pip install[TFLite] .

5. Install with Both:

   pip install[PiCamera,TFLite] .

6. Additional Dependendies

• Picar-4wd is needed if any of non-base Hardware classes are used such as DriveTrain or UltraSonic.

Usage

Getting Started

1. Import the library into your Python project:

   from Herbie.CarNav.Api import Car, AutonomousController, TFDetector
   from Herbie.Hardware.Api import DriveTrain, UltraSonic, Camera
   from Herbie.Network.Api import Client

2. Initialize the car and chosen controller:

   car = Car(
       AutonomousController(
            map_size = 11, # how big the grid the car exists in will be.
            cell_size = 25, # how big each cell in the grid is in centimeters.
            target = Position(9, 9), # the x, y position in the car's map that it needs to drive to.
            drive_train = DriveTrain(), # the drivetrain controls how the car rotates and moves forwards and backwards.
            obstacle_sensor = UltraSonic(), # the ultrasonic is how the car detects obstacles it needs to avoid.
            detector = TFDetector(Camera(), model_path="path to detection model")) # the class responsible for detecting various objects using the car's camera.
       ),
       # Client is an optional argument. It is a standard socket client that connects to a server and sends
       # data about the car's position, current obstacles, and the current path the car has chosen to take.
       Client() 
   )

3. Tell the car to drive and shutdown gracefully if an error is encountered:

     try:
         car.drive()
     except Exception as e:
         car.shutdown()
         raise e

Creating Custom Components

Herbie is made up of four modules CarNav, CMath, Hardware, and Network. In each module there is a Base.py file. Each Base.py is only dependent on the CPython3 standard library. So they can be imported and used to create a user specified class that can be used with the higher level classes. For example:

1. Creating a custom sensor class.

   from Herbie.Hardware.Base import BaseSensor
   
   class MySensor(BaseSensor):
       # Below are the only methods required for the Sensor to be able to interact with the higher level
       # classes such as AutonomousController.
       def get_distance(self) -> float:
           """Implementation"""
       def move_sensor_to(self, angle: float) -> bool:
           """Implementation"""
   
   # Now all that is needed to use this class is to pass it to the Controller class when setting up the car.
   car = Car(
   ...
   AutonomousController(
           ....
           MySensor()
       )
   )
   # This will create a car that uses your sensor for obstacle detection.

Examples

Check out the Examples/ directory for sample code using this library. These examples can help you understand how to build and program your RC car.

License

This project is licensed under the MIT License.

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Happy driving with your Raspberry Pi Self-Driving RC Car!