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BSK-RL: Environments and Algorithms for Spacecraft Planning and Scheduling

BSK-RL (Basilisk + Reinforcement Learning) is a Python package for constructing Gymnasium environments for spacecraft tasking problems. It is built on top of 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 is developed by the Autonomous Vehicle Systems (AVS) Lab at the University of Colorado Boulder.

Usage

Installation instructions, examples, and documentation can be found on the BSK-RL website (under construction).

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RL environments and tools for spacecraft autonomy research, built on Basilisk. Developed by the AVS Lab.

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