An Ontology-driven Dynamic Knowledge Base for Uninhabited Ground Vehicles

TL;DR

This paper presents an ontology-driven dynamic knowledge base for Uninhabited Ground Vehicles that enhances situation awareness and decision-making through real-time contextual updates during missions.

Contribution

It introduces a novel ontology-based dynamic knowledge base with real-time updates for UGVs to improve autonomy and adaptability in complex environments.

Findings

Enhanced situation awareness through dynamic knowledge updates

Successful implementation on a team of four UGVs in laboratory tests

Improved decision-making and mission success rate

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.