ROCLFLSep 28, 2022

Monitoring ROS2: from Requirements to Autonomous Robots

arXiv:2209.14030v110 citationsh-index: 18
Originality Incremental advance
AI Analysis

This work addresses safety-critical monitoring for autonomous robots, but it is incremental as it builds on existing tools like FRET and Copilot.

The paper tackles the challenge of ensuring safe operation in complex ROS2 applications by generating runtime monitors from structured natural language requirements, resulting in an automated toolchain that produces hard-real time C99 code and ROS2 packages for integration.

Runtime verification (RV) has the potential to enable the safe operation of safety-critical systems that are too complex to formally verify, such as Robot Operating System 2 (ROS2) applications. Writing correct monitors can itself be complex, and errors in the monitoring subsystem threaten the mission as a whole. This paper provides an overview of a formal approach to generating runtime monitors for autonomous robots from requirements written in a structured natural language. Our approach integrates the Formal Requirement Elicitation Tool (FRET) with Copilot, a runtime verification framework, through the Ogma integration tool. FRET is used to specify requirements with unambiguous semantics, which are then automatically translated into temporal logic formulae. Ogma generates monitor specifications from the FRET output, which are compiled into hard-real time C99. To facilitate integration of the monitors in ROS2, we have extended Ogma to generate ROS2 packages defining monitoring nodes, which run the monitors when new data becomes available, and publish the results of any violations. The goal of our approach is to treat the generated ROS2 packages as black boxes and integrate them into larger ROS2 systems with minimal effort.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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