基于ros2的自治应用的启用跟踪的定时模型合成

Hazem Abaza, Debayan Roy, Shiqing Fan, Selma Saidi, Antonios Motakis
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引用次数: 0

摘要

自主应用程序通常是在机器人操作系统2.0 (ROS2)上开发的,即使在像汽车这样的时间关键系统中也是如此。近年来,人们对开发基于模型的时序分析和基于ros2的应用程序的调度优化方法越来越感兴趣。为了补充这些方法,我们提出了一个跟踪和测量框架来\emph{获得基于ros2的应用程序的时序模型}。它提供了一个基于\emph{扩展Berkeley包过滤器}的跟踪器,可以探测ros2中间件中的不同函数,并读取它们的参数或返回值来推断应用程序中的数据流。它将来自ROS2和操作系统的事件跟踪结合起来,生成一个有\emph{向无循环图},显示ROS2回调、它们之间的优先级关系以及它们的定时属性。在与现有分析兼容的同时,我们还展示了如何建模(i)消息同步,例如在传感器融合中,以及(ii)来自多个客户端的服务请求,例如在运动规划中。考虑到,在现实世界的场景中,应用程序代码可能是\emph{保密}的,并且没有正式的模型,我们的框架仍然支持现有分析和优化技术的应用。
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Trace-enabled Timing Model Synthesis for ROS2-based Autonomous Applications
Autonomous applications are typically developed over Robot Operating System 2.0 (ROS2) even in time-critical systems like automotive. Recent years have seen increased interest in developing model-based timing analysis and schedule optimization approaches for ROS2-based applications. To complement these approaches, we propose a tracing and measurement framework to \emph{obtain timing models} of ROS2-based applications. It offers a tracer based on \emph{extended Berkeley Packet Filter} that probes different functions in ROS2 middleware and reads their arguments or return values to reason about the data flow in applications. It combines event traces from ROS2 and the operating system to generate a \emph{directed acyclic graph} showing ROS2 callbacks, precedence relations between them, and their timing attributes. While being compatible with existing analyses, we also show how to model (i)~message synchronization, e.g., in sensor fusion, and (ii)~service requests from multiple clients, e.g., in motion planning. Considering that, in real-world scenarios, the application code might be \emph{confidential} and formal models are unavailable, our framework still enables the application of existing analysis and optimization techniques.
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