CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots
CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots
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DOI：
10.1109/lra.2023.3280810
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发表时间：
2023-01
影响因子：
5.2
通讯作者：
Md. Abir Hossen;Sonam Kharade;B. Schmerl;Javier C'amara;Jason M. O'Kane;E. Czaplinski;K. Dzurilla;D. Garlan;Pooyan Jamshidi
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文献类型：
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作者：
Md. Abir Hossen;Sonam Kharade;B. Schmerl;Javier C'amara;Jason M. O'Kane;E. Czaplinski;K. Dzurilla;D. Garlan;Pooyan Jamshidi
机器人系统的子系统具有组合的大配置空间和数百或数千个可能的软件和硬件配置选项，这些选项进行非平凡的交互。可配置参数设置为针对特定目标，但如果配置不正确，可能会导致功能故障。由于配置空间呈指数级大，并且机器人的配置设置与性能之间存在依赖关系，因此找到此类故障的根本原因具有挑战性。本文提出了一种通过因果关系的透镜诊断功能故障根本原因的方法--关怀。CaRE通过学习因果结构和估计选项对机器人性能指标的因果影响来抽象各种配置选项与机器人性能目标之间的因果关系。我们证明了CaRE的有效性，找到所观察到的功能故障的根本原因，并通过在物理机器人（哈士奇和海龟3）和模拟（凉亭）进行实验，验证诊断的根本原因。此外，我们证明了从机器人模拟中学习的因果模型（例如，Husky in Gazebo）可以跨不同平台（例如，哈士奇和乌龟3）。
Robotic systems have subsystems with a combinatorially large configuration space and hundreds or thousands of possible software and hardware configuration options interacting non-trivially. The configurable parameters are set to target specific objectives, but they can cause functional faults when incorrectly configured. Finding the root cause of such faults is challenging due to the exponentially large configuration space and the dependencies between the robot's configuration settings and performance. This paper proposes CaRE—a method for diagnosing the root cause of functional faults through the lens of causality. CaRE abstracts the causal relationships between various configuration options and the robot's performance objectives by learning a causal structure and estimating the causal effects of options on robot performance indicators. We demonstrate CaRE’s efficacy by finding the root cause of the observed functional faults and validating the diagnosed root cause by conducting experiments in both physical robots (Husky and Turtlebot 3) and in simulation (Gazebo). Furthermore, we demonstrate that the causal models learned from robots in simulation (e.g., Husky in Gazebo) are transferable to physical robots across different platforms (e.g., Husky and Turtlebot 3).