https://github.com/5had3z/chasing-targets-gym

https://github.com/5had3z/chasing-targets-gym

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/5had3z/chasing-targets-gym
• Owner: 5had3z
• License: mit
• Created: 2023-03-09T04:46:15.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-12-21T01:07:10.000Z (6 months ago)
• Last Synced: 2025-04-03T01:04:21.916Z (3 months ago)
• Language: Python
• Size: 2.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

        
===================

Chasing Targets Gym

===================

|version| |python| |license| |codestyle|

.. |version| image:: https://img.shields.io/pypi/v/chasing-targets-gym

    :target: https://pypi.org/project/chasing-targets-gym/

    :alt: PyPI - Package Version

.. |python| image:: https://img.shields.io/pypi/pyversions/chasing-targets-gym

    :target: https://pypi.org/project/chasing-targets-gym/

    :alt: PyPI - Python Version

.. |license| image:: https://img.shields.io/pypi/l/chasing-targets-gym

    :target: https://github.com/5had3z/chasing-targets-gym/blob/main/LICENSE

    :alt: PyPI - License

.. |codestyle| image:: https://img.shields.io/badge/code%20style-black-000000.svg

    :target: https://github.com/psf/black

Introduction

------------

This is a simple gym environment that sets up a set of robots and targets for them to chase.

These targets are dumb, they simply move at a constant speed and bounce off the "limits" of 

the simulation environment. The intention is that the robots will chase after these targets,

and switch to a new target after catching their current one. The targets are "transparent" and

robots are free to ignore "avoiding them", the intention is that they avoid each other. An

example of a simulation with robot controller is shown below.

.. image:: misc/example_sim.gif

Usage

-----

Since this uses the gymnasium, you can spin an environment up same as any other env, and you can use our optimized planner. A script is included that shows of this planner and environment when you install this library ```chasing-targets-example --max-step=500```.

.. code:: python

    

    from gymnasium import Env, make

    from chasing_targets_gym.planner import Planner

    env: Env = make(

        "ChasingTargets-v0",

        render_mode="human",

        n_robots=10,

        n_targets=3,

        robot_radius=0.1,

        max_velocity=0.5,

        target_velocity_std=0.5,

        max_episode_steps=1000,

    )

    planner = Planner(

        env.get_wrapper_attr("robot_radius"),

        env.get_wrapper_attr("dt"),

        env.get_wrapper_attr("max_velocity"),

    )

Installation

------------

Either you can clone and pip install the source, or you can install via pypi.

If installing from source seems to stall for no apparent reason, try --no-build-isolation.

.. code:: bash

    git clone https://github.com/5had3z/chasing-targets-gym && cd chasing-targets-gym && pip3 install -e .

Otherwise install pypi package

.. code:: bash

    pip3 install chasing-targets-gym

Some Credit

-----------

I was pointed to a basic environment `here `_ but it didn't

really match what I wanted, so I made my own based off this.