迈向基于成熟度的具身AI认证：通过测量机制量化可信度
Toward Maturity-Based Certification of Embodied AI: Quantifying Trustworthiness Through Measurement Mechanisms
AI总结：
本文提出基于成熟度的具身AI认证框架，通过量化机制评估可信度，并通过无人机检测案例验证其可行性。
摘要：
我们提出了一种基于成熟度的框架，用于通过明确的测量机制对具身AI系统进行认证。我们认为，可认证的具身AI需要结构化的评估框架、定量评分机制以及处理可信度评估中固有的多目标权衡的方法。我们通过不确定性量化作为示例测量机制来展示这种方法，并通过无人机系统（UAS）检测案例研究来证明其可行性。
英文摘要：
We propose a maturity-based framework for certifying embodied AI systems through explicit measurement mechanisms. We argue that certifiable embodied AI requires structured assessment frameworks, quantitative scoring mechanisms, and methods for navigating multi-objective trade-offs inherent in trustworthiness evaluation. We demonstrate this approach using uncertainty quantification as an exemplar measurement mechanism and illustrate feasibility through an Uncrewed Aircraft System (UAS) detection case study.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
