- Project presentation is ready in docs.
- "AUV Static Environment Simulation" can be run directly in releases.
- To create Unity Environment to train and simulation the Agent, please follow the instructions below.
- Install Python 3.9.x
- Install Unity Editor
- Create a virtual environment
Run the following commands.
$ python -m venv sample-env
$ .\sample-env\Scripts\activate
$ python -m pip install --upgrade pip
$ pip install -r requirements_py39.txt
Note that on Windows, you may also need Microsoft's Visual C++ Redistributable if you don't have it already. See the PyTorch installation guide for more installation options and versions.
- Open Unity Hub.
- Select
Open
and chooseAUV
folder. - Ignore warnings and choose
Continue
- Start with
Safety Mode
- Open the
Package Manager
underWindow
Menu
- Click the
+
button and selectAdd package from disk..
option - Locate to
com.unity.ml-agents
under root. Selectpackage.json
- Apply same steps for
com.unity.ml-agents-extensions