This repository is built upon on multiagent-particle-envs and provides a set of environments with a variety of realistic constraints to simulate aerial anmanned vehicles settings with realistic constraints.
The goal of all the scenarios is to have each drones reaching their targets under certain conditions:
- drones_wind_battery_a4.py: normal battery and wind conditions
- drones_wind_battery_a4_battery02.py: starting battery capacity is very low
- drones_wind_battery_a4_wind1.py: very strong wind conditions
- drones_wind_battery_moving_a4.py: targets are not static but are randomly moving around
- drones_wind_battery_po_a4.py: agents have limited vision
- drones_wind_battery_moving_a4_hard.py: all the previous constraints are mixed together
- Create conda env
conda create -y -n auv python=3.9 anaconda
- Enable conda env
conda activate auv
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Install possible dependencies
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pip install PyHamcrest==1.9.0
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pip install install gym==0.7.3
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Install drones env
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cd unmanned-aerial-vehicles-marl-env
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pip install -e .
- Interactive testing:
python bin/interactive.py
- Random generated episodes:
python example_env_interaction.py