From 053e4ae275e65f51b261d13844d9b13d9e9ae50a Mon Sep 17 00:00:00 2001 From: Mark Stephenson <mark2000stephenson@gmail.com> Date: Wed, 29 May 2024 22:50:24 -0700 Subject: [PATCH] f --- README.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index fcd68954..bc806b92 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,14 @@ # BSK-RL: Environments for Spacecraft Planning and Scheduling -<img align="left" src="./docs/source/_images/static/bsk_rl-logo.png" width=200px style="margin:16px;"> +<img align="left" src="./docs/source/_images/static/bsk_rl-logo.png" width=180px style="margin:10px;"> -[BSK-RL](https://avslab.github.io/bsk_rl/) ([Basilisk](https://hanspeterschaub.info/basilisk) + [Reinforcement Learning](https://en.wikipedia.org/wiki/Reinforcement_learning)) is a Python package for constructing [Gymnasium](https://gymnasium.farama.org/index.html) environments for spacecraft tasking problems. It is built on top of [Basilisk](https://hanspeterschaub.info/basilisk), a modular and fast spacecraft simulation framework, making the simulation environments high-fidelity and computationally efficient. BSK-RL also includes a collection of agents, training scripts, and examples for working with these environments. +[BSK-RL](https://avslab.github.io/bsk_rl/) ([Basilisk](https://hanspeterschaub.info/basilisk) + [Reinforcement Learning](https://en.wikipedia.org/wiki/Reinforcement_learning)) is a Python package for constructing [Gymnasium](https://gymnasium.farama.org/index.html) environments for spacecraft tasking problems. It is built on top of [Basilisk](https://hanspeterschaub.info/basilisk), a modular and fast spacecraft simulation framework, making the simulation environments high-fidelity and computationally efficient. +### Usage +Installation instructions, examples, and documentation can be found on the [BSK-RL website](https://avslab.github.io/bsk_rl/). + +### Acknowledgment BSK-RL is developed by the [Autonomous Vehicle Systems (AVS) Lab](https://hanspeterschaub.info/AVSlab.html) at the University of Colorado Boulder. -## Usage -Installation instructions, examples, and documentation can be found on the [BSK-RL website](https://avslab.github.io/bsk_rl/).