Abstract
In this paper, the concept of Dynamic Contextual Mission Data (DCMD) is introduced to develop an ontology-driven dynamic knowledge base for Uninhabited Ground Vehicles (UGVs) at the tactical edge. The dynamic knowledge base with DCMD is added to the UGVs to: support enhanced situation awareness; improve autonomous decision making; and facilitate agility within complex and dynamic environments. As UGVs are heavily reliant on the a priori information added pre-mission, unexpected occurrences during a mission can cause identification ambiguities and require increased levels of user input. Updating this a priori information with contextual information can help UGVs realise their full potential. To address this, the dynamic knowledge base was designed using an ontology-driven representation, supported by near real-time information acquisition and analysis, to provide in-mission on-platform DCMD updates. This was implemented on a team of four UGVs that executed a laboratory based surveillance mission. The results showed that the ontology-driven dynamic representation of the UGV operational environment was machine actionable, producing contextual information to support a successful and timely mission, and contributed directly to the situation awareness.
Abstract (translated)
在这篇论文中，引入了动态情境任务数据（DCMD）的概念，旨在为战术边缘的无人地面车辆（UGVs）开发一个基于本体论的动态知识库。通过在UGVs上添加具有DCMD的动态知识库，可以支持增强的情景意识；提高自主决策能力；并促进在复杂和多变环境中灵活应对的能力。由于UGVs严重依赖于任务前预先加载的信息，在执行任务过程中出现的意外情况可能会导致识别模糊，并需要增加用户输入量。用情境信息更新这些预先存在的信息可以帮助UGVs充分发挥其潜力。 为解决这个问题，动态知识库采用基于本体论的表示方法设计，该方法通过接近实时的信息获取和分析支持，以在任务进行中提供平台上的DCMD更新。这一方案在一个由四个UGV组成的团队上实施，并执行了一项实验室环境下的监视任务。结果显示，基于本体论的动态表示法能够描述UGVs操作环境，并且这种机器可操作的方法产生了情境信息，支持了任务的成功和及时完成，并直接贡献于情况意识的提高。
URL
https://arxiv.org/abs/2602.10555
