Runtime Verification and Field-based Testing for ROS-based Robotic Systems

TL;DR

This paper provides tailored guidelines for developers and QA teams to effectively implement runtime verification and field-based testing in ROS-based robotic systems, addressing real-world deployment challenges.

Contribution

It offers 20 practical guidelines for testing and verification in ROS robotics, filling a gap in existing research and practice.

Findings

20 guidelines for testing and verification in ROS systems

Validated guidelines through literature review and questionnaires

Mapped guidelines to open challenges and future research directions

Abstract

Robotic systems are becoming pervasive and adopted in increasingly many domains, such as manufacturing, healthcare, and space exploration. To this end, engineering software has emerged as a crucial discipline for building maintainable and reusable robotic systems. The robotics software engineering research field has received increasing attention, fostering autonomy as a fundamental goal. However, robotics developers are still challenged to achieve this goal because simulation cannot realistically deliver solutions to emulate real-world phenomena. Robots also need to operate in unpredictable and uncontrollable environments, which require safe and trustworthy self-adaptation capabilities implemented in software. Typical techniques to address the challenges are runtime verification, field-based testing, and mitigation techniques that enable fail-safe solutions. However, no clear guidance exists for architecting ROS-based systems to enable and facilitate runtime verification and field-based testing. This paper aims to fill this gap by providing guidelines to help developers and quality assurance (QA) teams develop, verify, or test their robots in the field. These guidelines are carefully tailored to address the challenges and requirements of testing robotics systems in real-world scenarios. We conducted (i) a literature review on studies addressing runtime verification and field-based testing for robotic systems, (ii) mined ROS-based applications repositories, and (iii) validated the applicability, clarity, and usefulness via two questionnaires with 55 answers overall. We contribute 20 guidelines: 8 for developers and 12 for QA teams formulated for researchers and practitioners in robotic software engineering. Finally, we map our guidelines to open challenges in runtime verification and field-based testing for ROS-based systems, and we outline promising research directions in the field.