AS2FM: Enabling Statistical Model Checking of ROS 2 Systems for Robust Autonomy

TL;DR

This paper introduces AS2FM, a tool that extends formal verification techniques to ROS 2 autonomous systems, enabling efficient and scalable statistical model checking for robust robotic control.

Contribution

We developed AS2FM, an extension of the SCXML format and a translation tool to JANI, supporting comprehensive system features and scalable verification for ROS 2 autonomous robots.

Findings

Verification of a robotic manipulation case takes less than one second.

AS2FM supports more system features than existing methods.

Verification runtime scales linearly with model size.

Abstract

Designing robotic systems to act autonomously in unforeseen environments is a challenging task. This work presents a novel approach to use formal verification, specifically Statistical Model Checking (SMC), to verify system properties of autonomous robots at design-time. We introduce an extension of the SCXML format, designed to model system components including both Robot Operating System 2 (ROS 2) and Behavior Tree (BT) features. Further, we contribute Autonomous Systems to Formal Models (AS2FM), a tool to translate the full system model into JANI. The use of JANI, a standard format for quantitative model checking, enables verification of system properties with off-the-shelf SMC tools. We demonstrate the practical usability of AS2FM both in terms of applicability to real-world autonomous robotic control systems, and in terms of verification runtime scaling. We provide a case study, where we successfully identify problems in a ROS 2-based robotic manipulation use case that is verifiable in less than one second using consumer hardware. Additionally, we compare to the state of the art and demonstrate that our method is more comprehensive in system feature support, and that the verification runtime scales linearly with the size of the model, instead of exponentially.