基于ros的自动驾驶软件执行流程感知分析

Workshop Proceedings of the 51st International Conference on Parallel Processing Pub Date : 2022-08-29 DOI:10.1145/3547276.3548516

Shao-Hua Wang, Chia-Heng Tu, C. Huang, J. Juang

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引用次数: 0

摘要

随着自动驾驶汽车越来越智能，基于机器人操作系统(ROS)的自动驾驶软件的复杂性也在增长。对于系统设计人员来说，快速理解这些复杂软件的运行时行为和性能是一个巨大的挑战，因为传统的工具不足以描述软件中模块的高级交互。本文设计了一种新的图形表示方式——执行流图，来表示ROS模块的执行顺序和相关性能统计数据。在自主软件Autoware和Navigation Stack上应用了执行流感知分析，取得了良好的效果。

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Execution Flow Aware Profiling for ROS-based Autonomous Vehicle Software

The complexity of the Robot Operating System (ROS) based autonomous software grows as autonomous vehicles get more intelligent. It is a big challenge for system designers to rapidly understand runtime behaviors and performance of such sophisticated software because the conventional tools are insufficient for characterizing the high-level interactions of the modules within the software. In this paper, a new graphical representation, execution flow graph, is devised to represent the execution sequences and related performance statistics of the ROS modules. The execution flow aware profiling is applied on the autonomous software, Autoware and Navigation Stack, with encouraging results.

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Workshop Proceedings of the 51st International Conference on Parallel Processing

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