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End-to-End Analysis and Design of a Drone Flight Controller

机译:无人机飞行控制器的端到端分析和设计

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Timing guarantees are crucial to embedded and cyber-physical applications that must bound the end-to-end delay between sensing, processing and actuation. For example, in a flight controller for a multirotor drone, the data from a gyro or inertial sensor must be gathered and processed to determine the attitude of the aircraft. Sensor data fusion is followed by control outputs that alter rotor speeds to adjust the drone's flight. If the processing pipeline between sensor input and actuation is not bounded, the drone will lose control and possibly fail to maintain flight. This paper describes a composable pipe model for sensor data processing and actuation tasks. The pipe model is used to analyze two end-to-end semantics: 1) freshness and 2) reaction time. We provide a mathematical framework to derive feasible task periods and budgets that satisfy both schedulability and end-to-end timing requirements. We demonstrate the applicability of our design approach by using it to port the Cleanflight flight controller firmware to our in-house real-time operating system called Quest. Experiments show that Cleanflight ported to Quest is able to achieve end-to-end latencies within the predicted time bounds derived by analysis.
机译:时序保证对于嵌入式和网络物理应用至关重要,这些应用必须限制传感,处理和启动之间的端到端延迟。例如,在用于多旋翼无人机的飞行控制器中,必须收集并处理来自陀螺仪或惯性传感器的数据,以确定飞机的姿态。传感器数据融合之后是控制输出,这些输出会改变转子速度以调整无人机的飞行速度。如果传感器输入和致动之间的处理管道不受限制,则无人机将失去控制并可能无法维持飞行。本文介绍了用于传感器数据处理和执行任务的可组合管道模型。管道模型用于分析两个端到端语义:1)新鲜度和2)反应时间。我们提供了一个数学框架,以得出既满足可调度性又满足端到端时间要求的可行任务期和预算。我们通过将Cleanflight飞行控制器固件移植到我们称为Quest的内部实时操作系统中的方法,证明了我们设计方法的适用性。实验表明,移植到Quest的Cleanflight能够在通过分析得出的预测时间范围内实现端到端延迟。

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