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.

翻译：本文引入动态情境任务数据（DCMD）概念，旨在为战术边缘的无人地面车辆（UGV）开发一个基于本体的动态知识库。为UGV添加具备DCMD的动态知识库旨在：支持增强的态势感知；改进自主决策能力；并促进在复杂动态环境中的敏捷性。由于UGV严重依赖任务前加载的先验信息，任务期间发生的意外事件可能导致识别模糊，并需要增加用户输入。利用情境信息更新这些先验信息有助于UGV充分发挥其潜力。为此，本研究设计了一个基于本体表示、并辅以近实时信息获取与分析支持的知识库，以提供任务期间平台上的DCMD更新。该知识库在一个由四辆UGV组成的车队上进行了实现，执行了一项基于实验室的监视任务。结果表明，UGV操作环境的这种基于本体的动态表示具有机器可操作性，能够生成情境信息以支持任务成功及时完成，并直接提升了态势感知能力。