SwarmRL: Building the Future of Smart Active Systems

TL;DR

SwarmRL is an open-source Python package that facilitates the development and deployment of control models for microscopic colloids using classical and deep reinforcement learning, bridging experimental and simulation research.

Contribution

Introduces SwarmRL, a versatile software framework that simplifies micro-robotic control research through unified simulation and real-world deployment capabilities.

Findings

Enables control of microscopic colloids via reinforcement learning.

Accelerates research by integrating simulation and experimental workflows.

Provides an accessible platform for micro-robotic control development.

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 https://github.com/SwarmRL/SwarmRL.