Semantic knowledge-based framework to improve the situation awareness of autonomous underwater vehicles

Emilio Migueláñez, Pedro Patrón, Keith E. Brown, Yvan R. Petillot, David M. Lane

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

This paper proposes a semantic world model framework for hierarchical distributed representation of knowledge in autonomous underwater systems. This framework aims to provide a more capable and holistic system, involving semantic interoperability among all involved information sources. This will enhance interoperability, independence of operation, and situation awareness of the embedded service-oriented agents for autonomous platforms. The results obtained specifically affect the mission flexibility, robustness, and autonomy. The presented framework makes use of the idea that heterogeneous real-world data of very different type must be processed by (and run through) several different layers, to be finally available in a suited format and at the right place to be accessible by high-level decision-making agents. In this sense, the presented approach shows how to abstract away from the raw real-world data step by step by means of semantic technologies. The paper concludes by demonstrating the benefits of the framework in a real scenario. A hardware fault is simulated in a REMUS 100 AUV while performing a mission. This triggers a knowledge exchange between the status monitoring agent and the adaptive mission planner embedded agent. By using the proposed framework, both services can interchange information while remaining domain independent during their interaction with the platform. The results of this paper are readily applicable to land and air robotics. © 2006 IEEE.

Original languageEnglish
Article number5432174
Pages (from-to)759-773
Number of pages15
JournalIEEE Transactions on Knowledge and Data Engineering
Volume23
Issue number5
DOIs
Publication statusPublished - 2011

Keywords

  • Autonomous vehicles
  • mission planning
  • model-based diagnostics
  • ontology design

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