Guide for Verification of Autonomous Systems

Scope

This Guide for Verification of Autonomous Systems enables the user to define a customized process for verification of their autonomous system based on their available resources. It documents best practices across all levels of abstraction within a given system. It describes a conceptual model that assists in the development of new verification processes for autonomous systems and provides both integration guidance for developing a verification process and techniques, methodologies, and tool types supporting verification process development. ©IEEE 2022. All rights reserved.

Purpose

The purpose of this Guide is to identify existing best practices and provide instruction sets that define valid verification processes for a range of autonomous system configurations. These best practices apply from the lowest level components and software to the highest level learning or decision making elements (specifically including verification of the inputs to any learning algorithms, such as training data). The guidelines are intended to include both robots and immobots, singly and in groups, focusing primarily on systems that can operate autonomously rather than on automated or supervised robots. They may also be applicable to systems that do not directly interact with the external world (e.g. intelligence networks).

Verification process templates are provided as examples based on differing available sets of verification techniques and/or methodologies. The criteria for selecting a particular existing template are outlined. Different types of verification techniques, methodologies, and processes are enumerated and described, and a list of different tool types that should be part of any autonomous system verification toolbox is provided. The tool types captured in this Guide encompass techniques and/or methodologies that can be used for verification processes (such as those that quantify the completeness of coverage-guided test suites) and include both theoretical and software tools. ©IEEE 2022. All rights reserved.

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