Optimal Resource Utilization for Autonomous Laboratory Orchestrators
Summary
This paper presents a two-step method for optimizing resource utilization in autonomous laboratories using constraint programming for scheduling and status dependencies for robust execution, demonstrated on a platform for metal-organic framework synthesis.
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# Optimal Resource Utilization for Autonomous Laboratory Orchestrators Source: [https://arxiv.org/abs/2607.01188](https://arxiv.org/abs/2607.01188) [View PDF](https://arxiv.org/pdf/2607.01188) > Abstract:In autonomous laboratories, AI agents suggest the next batch of experiments to do\. However, planning and executing those tasks taking full advantage of the available resources is a completely different question\. This can be challenging when dealing with real\-world hardware constraints, especially so when there are multiple instruments with different capacities and throughputs\. Here we demonstrate a 2\-step method to address resource utilization for our autonomous platform for metal\-organic framework synthesis\. First, we use constraint programming to find optimal schedules\. This finds schedules that minimizes the total time while still satisfying the limitations and capacities of the hardware\. Secondly, we use a system of status dependencies for each task, which allows for the robust execution of the optimal schedules\. ## Submission history From: Austin McDannald Ph\.D\. \[[view email](https://arxiv.org/show-email/3f6bb6eb/2607.01188)\] **\[v1\]**Wed, 1 Jul 2026 17:20:45 UTC \(520 KB\)
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