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A Hierarchical Monitoring and Diagnosis System for Autonomous Robots

Authors Gerald Steinbauer-Wagner , Leo Fürbaß, Marco De Bortoli, Louise Travé-Massuyès

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ACM Subject Classification
  • Computing methodologies → Artificial intelligence
  • Computing methodologies → Knowledge representation and reasoning
Keywords
  • Cognitive Architecture
  • Autonomous Agents
  • Dependability
  • Hierarchical Monitoring and Diagnosis

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Abstract

This paper addresses the capability of autonomous robots to achieve flexible goals in dynamic environments. In such a setting numerous challenges jeopardize the robustness of such systems. Thus, we propose a hierarchical diagnosis concept for layered control architectures, that can detect and deal with such challenges to maintain a consistent knowledge about the world and to allow reliable decision-making. Layered control systems use various knowledge representations and decision-making mechanisms teamed with specialized isolated fault-handling approaches. However, some issues can only be identified if the information from different layers is combined. Our approach addresses challenges like failing actions, uncertain observations, and unmodeled events by propagating observations and diagnoses results throughout the hierarchy. This enhances adaptability and dependability in various domains. In this paper, we present a prototype architecture following this approach.

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Gerald Steinbauer-Wagner, Leo Fürbaß, Marco De Bortoli, and Louise Travé-Massuyès. A Hierarchical Monitoring and Diagnosis System for Autonomous Robots. In 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024). Open Access Series in Informatics (OASIcs), Volume 125, pp. 1:1-1:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/OASIcs.DX.2024.1

Author Details

Gerald Steinbauer-Wagner
  • Institute for Software Technology, Graz University of Technology, Austria
Leo Fürbaß
  • Institute for Software, Technology Graz University of Technology, Austria
Marco De Bortoli
  • Institute for Software Technology, Graz University of Technology, Austria
Louise Travé-Massuyès
  • LAAS-CNRS, Université de Toulouse, CNRS, Toulouse, France

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