  The recent advent of autonomous laboratories, coupled with algorithms for
high-throughput screening and active learning, promises to accelerate materials
discovery and innovation. As these autonomous systems grow in complexity, the
demand for robust and efficient workflow management software becomes
increasingly critical. In this paper, we introduce AlabOS, a general-purpose
software framework for orchestrating experiments and managing resources, with
an emphasis on automated laboratories for materials synthesis and
characterization. We demonstrate the implementation of AlabOS in a prototype
autonomous materials laboratory. AlabOS features a reconfigurable experiment
workflow model, enabling the simultaneous execution of varied workflows
composed of modular tasks. Therefore, AlabOS is well-suited to handle the
rapidly changing experimental protocols defining the progress of self-driving
laboratory development for materials research.
