A multi-robot–multi-task scheduling system for autonomous chemistry laboratories

Abstract

We present a multi-robot–multi-task scheduling system designed for autonomous chemistry laboratories to enhance the efficiency of executing complex chemical experiments. Building on the herein formulated and developed scheduling algorithms and employing a constraint programming approach, the scheduling system optimizes task allocation across three robots and 18 experimental stations, facilitating the coordinated and concurrent execution of experiments. The system allows for dynamic task insertion during ongoing operations without significant disruption, enhancing laboratory efficiency and flexibility while providing a scalable solution for high-throughput experimentation. In real-world applications involving four diverse chemical experiments with varied step counts, step durations, and sample throughputs, the system demonstrated its ability to reduce total execution time by nearly 40% compared to sequential execution of individual experiments, where in-experiment tasks were already optimized for concurrency. Our multi-robot–multi-task system represents a timely and significant advancement in autonomous chemistry, enabling automated laboratories to conduct experiments with greater efficiency and versatility. By reducing the time and resources required for experimentation, it accelerates the pace of scientific discovery and offers a robust framework for developing more sophisticated autonomous laboratories capable of handling increasingly complex and diverse scientific tasks.