通过基于模型的框架简化无人机自动驾驶仪的调整

IF 1.7 3区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Soulimane Kamni , Antoine Bertout , Emmanuel Grolleau , Gautier Hattenberger , Yassine Ouhammou
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引用次数: 0

摘要

现成的开源自动驾驶是由从业者定制的,以满足客户的特定需求。当自定义函数需要数百赫兹或几千赫兹量级的低延迟和/或快频率时,它们可能会影响底层稳定回路的行为。本文提出了一种工具链,该工具链能够使用基于AADL(架构分析与设计语言)语义的领域特定语言(DSL)提取模型,并根据特定需求进行扩展,以捕捉自动驾驶的内部行为。这种提取是在自动驾驶仪的编译过程中直接完成的。然后,我们在自动驾驶仪的模型上应用一种工具来为无偏移系统分配偏移。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Easing the tuning of drone autopilots through a model-based framework

Off-the-shelf open-source autopilots are customized by practitioners to satisfy their customer’s specific needs. When custom functions require low delays and/or fast frequency, in the order of magnitude of hundreds or a couple of thousand hertz, they may impact the behavior of the underlying stabilization loop. This paper proposes a tool chain able to extract a model using a Domain-Specific Language (DSL) based on AADL (Architecture Analysis & Design Language) semantics, extended with specific needs to capture the internal behavior of autopilots. This extraction is done directly during the compilation process of the autopilot. Then, we apply on the model of an autopilot a tool to assign offsets for offset-free systems.

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来源期刊
Journal of Computer Languages
Journal of Computer Languages Computer Science-Computer Networks and Communications
CiteScore
5.00
自引率
13.60%
发文量
36
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