多智能体空中3D打印的最优安全意识调度与效用最大化在依赖约束下
Optimal Safety-Aware Scheduling for Multi-Agent Aerial 3D Printing with Utility Maximization under Dependency Constraints
AI总结：
本文提出了一种基于效用最大化的优化框架，用于在依赖约束下实现多智能体空中3D打印的最优安全调度。
摘要：
本文提出了一种新颖的协调和任务规划框架，以实现多个无人 aerial 车（UAV）在空中3D打印中的同时无冲突协作。所提出的框架制定了一个优化问题，考虑将建设任务分成子任务和一组自主UAVs，以及有限的体积和电池。它生成了一个最优的任务计划，包括任务分配和调度，同时考虑到由于3D设计的几何和结构要求而产生的任务依赖性，以及UAV之间的安全约束、材料使用和每个UAV的总飞行时间。在UAV同时操作过程中可能出现的冲突在段级上得到解决，通过动态选择每个任务的起始时间和位置以确保碰撞自由的并行执行。提出了一种重要性优先级，以加速计算，通过引导解决方案向更重要的任务倾斜。此外，提出了一种效用最大化公式，以动态确定给定任务所需的最优UAV数量，平衡最小化makespan和部署多余代理之间的权衡。所提出的框架的有效性通过基于Gazebo的模拟设置进行评估，其中代理由任务控制模块协调，该模块根据生成的最优调度计划分配打印任务，同时保持每个UAV的材料和电池约束。
英文摘要：
This article presents a novel coordination and task-planning framework to enable the simultaneous conflict-free collaboration of multiple unmanned aerial vehicles (UAVs) for aerial 3D printing. The proposed framework formulates an optimization problem that takes a construction mission divided into sub-tasks and a team of autonomous UAVs, along with limited volume and battery. It generates an optimal mission plan comprising task assignments and scheduling while accounting for task dependencies arising from the geometric and structural requirements of the 3D design, inter-UAV safety constraints, material usage, and total flight time of each UAV. The potential conflicts occurring during the simultaneous operation of the UAVs are addressed at a segment level by dynamically selecting the starting time and location of each task to guarantee collision-free parallel execution. An importance prioritization is proposed to accelerate the computation by guiding the solution toward more important tasks. Additionally, a utility maximization formulation is proposed to dynamically determine the optimal number of UAVs required for a given mission, balancing the trade-off between minimizing makespan and the deployment of excess agents. The proposed framework's effectiveness is evaluated through a Gazebo-based simulation setup, where agents are coordinated by a mission control module allocating the printing tasks based on the generated optimal scheduling plan while remaining within the material and battery constraints of each UAV.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
