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halvorot / Deep-RL-Collision-Avoidance-TTK4550-Fordypningsoppgave

Collision Avoidance simulator for USV using Deep RL. A result of TTK4550 Fordypningsoppgave at NTNU
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Collision Avoidance simulator for USV using Deep RL

Python simulation framework for Collision Avoidance for Unmanned Surface Vehicle using Deep Reinforcement Learning.

An explanation of the software structure can be found in Eivind Meyers repository gym-auv

Getting Started

Note: Requires Python 3.7

Note: Pybullet needs Microsoft Visual C++ 14.0. Install it with "Build Tools for Visual Studio".

Note: Stable-Baselines only supports Tensorflow 1.14, Tensorflow 2 support is planned.

! Install Microsoft MPI (https://docs.microsoft.com/en-us/message-passing-interface/microsoft-mpi) (msmpisetup.exe , not SDK)

Note: Run the following first.

conda install -c conda-forge shapely
conda install swig
conda install ffmpeg

Then run 

pip install -e ./gym-auv/

You can now execute the script by running 

python run.py <mode> <env>

The run script can be executed with the -h flag for a comprehensive overview of the available usage modes.

Examples:

python run.py play TestScenario1-v0
python run.py train MovingObstaclesNoRules-v0
python run.py enjoy MovingObstaclesNoRules-v0 --algo algorithm --agent path\to\agent.pkl

Known bugs