Building domain-specific accelerators for autonomous unmanned aerial vehicles (UAVs) is challenging due to a lack of systematic methodology for designing onboard compute. Balancing a computing system for a UAV requires considering both the cyber (e.g., sensor rate, compute performance) and physical (e.g., payload weight) characteristics that affect overall performance. Iterating over the many component choices results in a combinatorial explosion of the number of possible combinations: from 10s of thousands to billions, depending on implementation details. Manually selecting combinations of these components is tedious and expensive. To navigate the {cyber-physical design space} efficiently, we introduce \emph{AutoPilot}, a framework that automates full-system UAV co-design. AutoPilot uses Bayesian optimization to navigate a large design space and automatically select a combination of autonomy algorithm and hardware accelerator while considering the cross-product effect of other cyber and physical UAV components. We show that the AutoPilot methodology consistently outperforms general-purpose hardware selections like Xavier NX and Jetson TX2, as well as dedicated hardware accelerators built for autonomous UAVs, across a range of representative scenarios (three different UAV types and three deployment environments). Designs generated by AutoPilot increase the number of missions on average by up to 2.25x, 1.62x, and 1.43x for nano, micro, and mini-UAVs respectively over baselines. Our work demonstrates the need for holistic full-UAV co-design to achieve maximum overall UAV performance and the need for automated flows to simplify the design process for autonomous cyber-physical systems.
翻译:用于自动无人驾驶飞行器(UAVs)的域性加速器的建设之所以具有挑战性,是因为缺乏系统化的在船上进行计算的方法。为UAV平衡计算系统需要考虑影响总体性能的网络特性(例如传感器率、计算性能)和物理特性(例如载荷重量),对许多组成部分的选择进行循环,导致可能的组合数量的组合发生组合式爆炸:从10万到数十亿个,这取决于执行细节。手工选择这些组件的组合是乌币和昂贵的。要高效率地浏览 {cyber-物理设计空间},我们引入了\emph{AutopiPilot},这是一个自动连接整个系统UAVAV-共同设计特征的框架。 AutoPilot使用巴伊斯优化来操作大型设计空间,自动选择自控算算算法和硬件加速器的组合,同时考虑其他网络和物理UAVAV组件的交叉产品效应。我们显示,AutPILO方法始终超越了通用硬件选择的通用选择,例如XAVAV-AV-AVx的高级设计系统, 和高级设计的高级自动设计流程需要不同类型, 和自动设计流程的自动生成的自动生成和自动生成的自动生成的自动生成的自动操作,需要在三个的自动设计流程中进行。