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<p>One barrier to persistent operations in systems of unmanned aerial vehicles (UAVs) served by logistics support stations is the need for methods to manage and efficiently schedule system resources. This paper presents a scheduling framework for UAV systems served by battery charging and battery replacement stations. We extend existing Petri net models for these systems to prevent unwanted resource overlap and impose a resource pairing rule to facilitate cyclic operation. Based on this rule, an extended Petri net that explicitly models the interactions of specific resources is derived. The detailed nature of the extended Petri net allows for the creation of linear programs that capture the structure of the net and generate optimal cyclic resource schedules. These cyclic schedules enable the persistent orchestration of tasks for UAV and logistics support stations. Computational complexity of the linear programs is explored.</p>

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Cyclic Resource Scheduling in Systems of UAVs and Logistics Support Stations via Petri Nets and Linear Programming

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月27日

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  • Mirza E. Neebraz,
  • Ammar Altaweel,
  • James R. Morrison

摘要

One barrier to persistent operations in systems of unmanned aerial vehicles (UAVs) served by logistics support stations is the need for methods to manage and efficiently schedule system resources. This paper presents a scheduling framework for UAV systems served by battery charging and battery replacement stations. We extend existing Petri net models for these systems to prevent unwanted resource overlap and impose a resource pairing rule to facilitate cyclic operation. Based on this rule, an extended Petri net that explicitly models the interactions of specific resources is derived. The detailed nature of the extended Petri net allows for the creation of linear programs that capture the structure of the net and generate optimal cyclic resource schedules. These cyclic schedules enable the persistent orchestration of tasks for UAV and logistics support stations. Computational complexity of the linear programs is explored.