無人地上車両のためのオントロジー駆動型動的知識ベース
An Ontology-driven Dynamic Knowledge Base for Uninhabited Ground Vehicles
無人地上車両（UGV）の戦術エッジでの状況認識と自律意思決定を向上させるため、オントロジー駆動型の動的知識ベースを構築し、4台のUGVチームによる監視ミッションで有効性を検証した。
著者: Hsan Sandar Win, Andrew Walters, Cheng-Chew Lim, Daniel Webber, Seth Leslie, Tan Doan
分類: cs.MA, cs.DB, cs.RO
原文アブストラクト
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.