Lunar Lander Project

Overview

The Lunar Lander Project simulates a lunar landing mission with two control strategies: a PID controller and a Deep Q-Network (DQN) agent. The project includes a graphical user interface (GUI) for adjusting simulation parameters such as gravity, wind power, and fuel limits. The goal is to safely land the lunar lander using the selected control strategy.

Features

• PID and DQN Controllers: Test and compare the performance of a PID controller and a trained DQN agent for lunar landing.
• Customizable Environment Parameters: Fine-tune settings like gravity, wind power, fuel limits, and malfunctions through an intuitive GUI.
• Simulation Visualization: Real-time graphical feedback on the lunar lander's behavior and performance.

GUI Functionality

The GUI provides the following features:

• Choose Environment: Select between a Custom or Original environment for the simulation.

  • Custom Environment: Users can modify specific parameters, including:
    • Gravity: Modify gravity to test controller performance under different conditions.
    • Wind Power: Change wind conditions to introduce variability into the simulation.
    • Fuel Limit: Set fuel constraints to challenge the controllers.
    • Malfunction: Toggle random malfunctions to simulate real-world issues.

• Controller Selection:
  Select between the PID or DQN controller for the simulation.

• Number of Iterations:
  Define how many simulation runs should be executed.

• Run and Exit Buttons:
  Use the Run button to start simulations or the Exit button to close the application.

Installation

To set up the project locally:

1. Clone the Repository:

   git clone https://github.com/YarinOhayon/Lunar_Lander.git
   cd Lunar_Lander

2. Install Dependencies: Ensure Python is installed, then install the required packages:

   pip install -r requirements.txt

3. Run the Application: Launch the GUI by executing:

   python LunarLanderGUI.py

Usage

1. Select an Environment:
   Choose between a Custom or Original environment.

   • If you select Custom, you'll be able to adjust specific parameters (gravity, wind power, etc.).

2. Select a Controller:
   Choose between PID or DQN from the dropdown menu in the GUI.

3. Set Parameters (Custom Environment):
   If you selected the Custom environment, adjust the following parameters as needed:

   • Gravity: Modify the gravity level.
   • Wind Power: Introduce or adjust wind conditions.
   • Fuel Limit: Set limits on available fuel.
   • Malfunctions: Toggle random malfunctions on or off.

4. Start the Simulation:
   Click the Run button to begin the simulation with the selected environment, controller, and parameters.

5. Close the Application:
   Click the Exit button to terminate the application.

Code Structure

• LunarLanderGUI.py: Implements the GUI using Tkinter for user interactions, allowing users to select controllers and adjust simulation parameters.
• LunarLanderEnvWrapper.py: Wraps the Lunar Lander environment to integrate and manage adjustable parameters like gravity and wind.
• DQNAgent.py: Contains the implementation of the Deep Q-Network (DQN) agent used to control the lunar lander and make decisions based on the environment state.
• LunarLanderPIDController.py: Implements the Proportional-Integral-Derivative (PID) controller for managing the lunar lander’s descent.
• DQN.py: Defines the architecture of the Deep Q-Network (DQN) using PyTorch, including fully connected layers and dropout for reinforcement learning tasks.
• PIDController.py: Implements a basic PID controller to calculate control outputs based on setpoint and measurement, with methods for computing control actions.
• ReplayBuffer.py: Provides a replay buffer for storing transitions and sampling mini-batches for training the DQN agent.
• TrainDQN.py: Contains the training function for the DQN model, which allows you to train the agent in the Lunar Lander environment and save the trained model.
• Plots.py: Contains functions for plotting the performance of different models (PID, DQN) and environments (Classic, Fuel, Wind, Gravity, and Malfunction).
• requirements.txt: Lists the Python packages required to run the project.
• README.md: Documentation file describing the project, installation, usage, and other relevant information.