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Easing the tuning of drone autopilots through a model-based framework
Journal of Computer Languages ( IF 2.2 ) Pub Date : 2023-09-15 , DOI: 10.1016/j.cola.2023.101240
Soulimane Kamni , Antoine Bertout , Emmanuel Grolleau , Gautier Hattenberger , Yassine Ouhammou

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.



中文翻译:

通过基于模型的框架简化无人机自动驾驶仪的调整

现成的开源自动驾驶仪由从业者定制,以满足客户的特定需求。当自定义函数需要低延迟和/或快频率(数百或几千赫兹的数量级)时,它们可能会影响底层稳定环路的行为。本文提出了一种工具链,能够使用基于 AADL(架构分析和设计语言)语义的领域特定语言(DSL)来提取模型,并根据特定需求进行扩展以捕获自动驾驶仪的内部行为。这个提取是在自动驾驶仪的编译过程中直接完成的。然后,我们在自动驾驶仪模型上应用一个工具来为无偏移系统分配偏移。

更新日期:2023-09-15
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