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SHaSTA (Simulator for Human and Swarm Team Applications)

Simulator Banner (Screenshot for illustration purposes only.)

Welcome to the SHaSTA! An open-source simulation platform to study human-swarm applications. The platform provides a unified interface for humans and learning algorithms to command/learn swarm robot behaviors. SHaSTA also provides a unique ability to collect physiological information from humans and time synchronize it with swarm simulation.

Table of Contents

Features

  • Realistic swarm simulation powered by the pybullet.
  • Human-Swarm Interaction interface.
  • Physiological signal (EEG, EMG, Eye movement, etc.) collection facility built on lab streaming layer.
  • OpenAI Gym interface for reinforcement learning experiments.
  • Highly customizable simulation environment.
  • Easy-to-use and well-documented codebase.

Installation

  1. Clone this repository to your local machine using:

    git clone https://github.com/ub-nsf-hsi/shasta-ub.git
    
    
  2. Install the required dependencies:

    pip install -r requirements.txt
    
  3. Configure your XPlane installation and simulator settings as needed.

Usage

  1. Launch the simulator by running:

    python main.py
    

    If you want to run a particular block of code, replace the skip by run.

  2. Explore the simulation environment, adjust settings, and start flying!

MRTA Formulation

The file MRTA_Experiment.py in experiments folder present the MRTA formulation

Contributing

We welcome contributions from the community to improve and expand this simulator project. If you're interested in contributing, please follow our Contribution Guidelines.

Code of Conduct

Please review and adhere to our Code of Conduct when participating in our community. We strive to maintain a respectful and inclusive environment for everyone.

License

This project is licensed under the MIT License, which means you are free to use, modify, and distribute the code in your projects.


We hope you enjoy using the SHaSTA. Happy flying!

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MRTA Formulation with Shasta Simulator

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