Abstract
This work introduces SwarmRL, a Python package designed to study intelligent active particles. SwarmRL provides an easy-to-use interface for developing models to control microscopic colloids using classical control and deep reinforcement learning approaches. These models may be deployed in simulations or real-world environments under a common framework. We explain the structure of the software and its key features and demonstrate how it can be used to accelerate research. With SwarmRL, we aim to streamline research into micro-robotic control while bridging the gap between experimental and simulation-driven sciences. SwarmRL is available open-source on GitHub at this https URL.
Abstract (translated)
本工作介绍了SwarmRL，一个旨在研究智能主动粒子的Python软件包。SwarmRL为使用经典控制和深度强化学习方法控制微观颗粒的模型提供了易于使用的界面。这些模型可以在模拟或现实环境中共存于一个共同框架中。我们解释了软件的架构及其关键特征，并展示了如何使用它来加速研究。通过SwarmRL，我们旨在简化微型机器人控制的科学研究，并缩小实验和仿真驱动的科学之间的差距。SwarmRL可以在GitHub上的这个链接开源使用。
URL
https://arxiv.org/abs/2404.16388
