https://github.com/elymsyr/auv_simulation

A complete development and testing environment for Model Predictive Control (MPC) systems. It features a simulation environment, communication bridges for HIL/MIL testing, and implementations of imitation learning and PPO, complete with visualization tools.
https://github.com/elymsyr/auv_simulation

unity zeromq

Last synced: about 2 months ago
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A complete development and testing environment for Model Predictive Control (MPC) systems. It features a simulation environment, communication bridges for HIL/MIL testing, and implementations of imitation learning and PPO, complete with visualization tools.

• Host: GitHub
• URL: https://github.com/elymsyr/auv_simulation
• Owner: elymsyr
• Created: 2025-07-07T14:44:15.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2025-07-18T13:05:41.000Z (12 months ago)
• Last Synced: 2025-07-18T17:48:14.759Z (12 months ago)
• Topics: unity, zeromq
• Language: Python
• Homepage: https://github.com/elymsyr/auv_control_system
• Size: 39.1 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# AUV Simulation

This repository contains the full development and testing environment for Model Predictive Control (MPC) systems, including simulation, communication, and learning phases.

## Project Structure

- **connection/**  

  Python modules for testing communication, code definitions, and visualization.

  - `bridge.py`: Communication bridge between test/Model and simulation.

  - `codes.py`: Code definitions and utilities.

  - `comm.py`: Communication test interface.

  - `visualize.py`: Visualization tools for data EnvironmentMap.save and results.

- **simulation/**  

  Simulation environment, assets, and configuration files.

  - `config.json`: Simulation configuration parameters.

  - `Assets/`, `Models/`, `Scenes/`, `Scripts/`, `Settings/`, `TutorialInfo/`: Unity or simulation assets and scripts.

- **test/**

  Testing and validation scripts for different phases.

  - `il/`: Imitation learning tests.

  - `il-map/`: Map-based imitation learning.

  - `map-entegrated-mpc/`: MPC tests with mapping integration.

  - `Model/`: Model-specific tests.

  - `mpc/`: MPC algorithm tests.

  - `ppo/`: Proximal Policy Optimization (PPO) reinforcement learning tests.

## Features

- **MPC Algorithm Development**: Core algorithms and utilities for MPC.

- **Simulation Environment**: Configurable simulation for SIL, MIL, and HIL testing.

- **Imitation Learning**: Scripts and tests for imitation learning phases.

- **Reinforcement Learning**: PPO-based learning and testing.

- **Visualization**: Tools for visualizing simulation and control results.

- **Comprehensive Testing**: Organized test suites for all development phases.

# License

[GNU GENERAL PUBLIC LICENSE](LICENSE)