A Survey on Trust Metrics for Autonomous Robotic Systems

Vincenzo DiLuoffo, W. Michalson
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Abstract

This paper surveys the area of “Trust Metrics” related to security for autonomous robotic systems. As the robotics industry undergoes a transformation from programmed, task oriented, systems to Artificial Intelligence-enabled learning, these autonomous systems become vulnerable to several security risks, making a security assessment of these systems of critical importance. Therefore, our focus is on a holistic approach for assessing system trust which requires incorporating system, hardware, software, cognitive robustness, and supplier level trust metrics into a unified model of trust. We set out to determine if there were already trust metrics that defined such a holistic system approach. While there are extensive writings related to various aspects of robotic systems such as, risk management, safety, security assurance and so on, each source only covered subsets of an overall system and did not consistently incorporate the relevant costs in their metrics. This paper attempts to put this prior work into perspective, and to show how it might be extended to develop useful systemlevel trust metrics for evaluating complex robotic (and other) systems.
自主机器人系统信任指标研究
本文研究了与自主机器人系统安全相关的“信任度量”领域。随着机器人行业经历从编程、任务导向系统到人工智能学习的转变,这些自主系统变得容易受到几种安全风险的影响,因此对这些系统进行安全评估至关重要。因此,我们的重点是评估系统信任的整体方法,这需要将系统,硬件,软件,认知稳健性和供应商级别的信任指标纳入统一的信任模型。我们开始确定是否已经存在定义这样一个整体系统方法的信任度量。虽然有大量的著作涉及机器人系统的各个方面,如风险管理、安全、安全保证等,但每个来源只涵盖了整个系统的子集,并且没有一致地将相关成本纳入其度量中。本文试图将这一先前的工作纳入视角,并展示如何将其扩展到开发有用的系统级信任度量来评估复杂的机器人(和其他)系统。
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