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A Method for Evaluating and Selecting Suitable Hardware for Deployment of Embedded System on UAVs

机译:一种评估和选择合适硬件用于在UAV上部署嵌入式系统

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摘要

The use of UAVs for remote sensing is increasing. In this paper, we demonstrate a method for evaluating and selecting suitable hardware to be used for deployment of algorithms for UAV-based remote sensing under considerations of , , , and constraints. These constraints hinder the deployment of rapidly evolving computer vision and robotics algorithms on UAVs, because they require intricate knowledge about the system and architecture to allow for effective implementation. We propose integrating computational monitoring techniques—profiling—with an industry standard specifying software quality—ISO 25000—and fusing both in a decision-making model—the analytic hierarchy process—to provide an informed decision basis for deploying embedded systems in the context of UAV-based remote sensing. One software package is combined in three software–hardware alternatives, which are profiled in hardware-in-the-loop simulations. Three objectives are used as inputs for the decision-making process. A Monte Carlo simulation provides insights into which decision-making parameters lead to which preferred alternative. Results indicate that local weights significantly influence the preference of an alternative. The approach enables relating complex parameters, leading to informed decisions about which hardware is deemed suitable for deployment in which case.
机译:使用无人机用于遥感。在本文中,我们演示了一种用于评估和选择合适的硬件来用于部署基于UAV的遥感的算法的方法,以及在考虑的情况下,和约束。这些约束阻碍了在UAVS上部署快速发展的计算机视觉和机器人算法,因为它们需要有关系统和架构的错综复杂的知识,以允许有效实现。我们建议将计算监控技术 - 剖析 - 与行业标准指定的软件质量-ISO 25000在决策模型中 - 分析层次结构 - 分析层次处理 - 为在UAV的上下文中部署嵌入式系统提供明智的决策依据基于遥感。一个软件包在三种软件 - 硬件替代方案中组合,这些替代方法是在循环硬件仿真中的配置。三个目标被用作决策过程的输入。蒙特卡罗仿真提供了洞察力,决策参数导致哪个替代方案。结果表明,局部权重显着影响替代方案的偏好。该方法使得能够与复杂的参数相关联,这导致了关于哪个硬件被认为适合部署的知识决定在这种情况下。

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