ControlSystem

Check the latest verison with ROS2 Humble and Gazebo implementation, uses FossenNet DL model: auv_ws

A modular, GPU-accelerated control system for Autonomous Underwater Vehicles (AUVs). The system is fully customizable and designed to operate in mission- and environment-agnostic scenarios.

This repository contains only the latest version of the main control system. For other AUV components, see:

• Simulation Systems
• Vision Systems
• Control Models
• LLM Agent
• User Interface

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Docs

• Modular System
• Vehicle Dynamics

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Features

• Non-Linear Model Predictive Control (NL-MPC) using CasADi for advanced trajectory tracking and control.
• Imitation learning: Distill CasADi-based nonlinear MPC into neural network controllers for faster iteration.
• CUDA-accelerated environment mapping for real-time collision checking and safe navigation.
• GPU-accelerated A* path planning for efficient route computation.
• Fossen equations for accurate marine vehicle dynamics modeling.
• Flexible vehicle model configuration via JSON.
• Modular architecture with custom templated components for rapid development.
• Pub/Sub communication: ROS2-like communication using ZeroMQ.
• LLM Agent: Integrate a Large Language Model agent for high-level mission planning and autonomous command interpretation.

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Requirements

• CUDA Toolkit (11.x or 12.x recommended, developed on 12.4.1)
• NVIDIA GPU with compatible driver
• Conda
• C++17 or newer
• CMake

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Building

Docker

Recommended when the original GUI is used on local web.

1. Pull and run container:

   docker pull elymsyr/control_system:latest
   docker run --gpus all -it elymsyr/control_system -h

2. Clone this repository:

   git clone https://github.com/elymsyr/auv_control_system.git
   cd auv_control_system

3. Use test UI to control the system:

   pip install zmq
   python connection/comm.py

CMake

Recommended when the test UI is used on local.

1. Install dependencies (CUDA, CasADi, nlohmann/json).

2. Clone this repository:

   git clone https://github.com/elymsyr/auv_control_system.git
   cd auv_control_system

3. Build with CMake:

   conda env create -f environment.yml
   conda run -n mp_test bash -c " \
     cd /app && \
     rm -rf build && \
     mkdir build && \
     cd build && \
     cmake -DBOOST_ROOT=\$CONDA_PREFIX \
       -DCMAKE_CXX_COMPILER=\$CONDA_PREFIX/bin/x86_64-conda-linux-gnu-g++ \
       -DCMAKE_CUDA_HOST_COMPILER=\$CONDA_PREFIX/bin/x86_64-conda-linux-gnu-gcc \
       -DCMAKE_PREFIX_PATH=\$CONDA_PREFIX \
       -DCMAKE_BUILD_TYPE=Debug .. && \
     make -j\$(nproc) \
     "

4. See help and run:

   ./control_system -h

5. Use test UI to control the system:

   pip install zmq
   conda run -n mp_test bash -c "python ../connection/comm.py"

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License

GNU GENERAL PUBLIC LICENSE

Development Process

[TR] Ocak 2025 - Mayıs 2025 geliştirme sürecine bakmak için Notion sayfasını ziyaret edebilirsiniz.

Security Notice

This project is under active development and is not production-ready.
There may be untested features, incomplete security measures, or vulnerabilities.
It is not recommended to use this system in safety-critical or production environments.