Failure Recovery with Ontologically Generated Behaviour Trees

Master thesis (2023)

Authors

W. Jaber Mechanical Engineering

Contributors

Carlos Hernández Robot Dynamics - Mechanical, Maritime and Materials Engineering (supervisor 1)
L. Peternel Human-Robot Interaction - Mechanical, Maritime and Materials Engineering (supervisor 2)
Christian Pek Robot Dynamics - Mechanical, Maritime and Materials Engineering (coach)
Faculty
Mechanical Engineering
Copyright: © 2023 Wissam Jaber
Behaviour Trees Ontological reasoning Failure recovery Behaviour generation
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Published Date

22-09-2023

Language

English

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Faculty

Mechanical Engineering

Abstract

Behaviour trees (BTs) serve as a powerful hierarchical structure for task execution, simplifying complex tasks but posing challenges in their manual design. The automatic generation of BTs addresses this concern, yet often lacks robust failure recovery options. This study presents Failure Recovery with Ontologically Generated Behaviour Trees (FROGBT), a novel approach bridging this gap by integrating ontological reasoning into the process of automatically generating BTs. This integration establishes a profound link between an agent’s knowledge and its capabilities, offering contextual insights into the agent’s skills. FROGBT enhances skill representation for planning and recovery. The approach’s effectiveness is indicated by its efficiency compared to the state-of-the-art framework for skill-based control, SkiROS, in a similar task. It showcases generality, uniting diverse skills, developed by various engineers, for recurring tasks, and introduces innovative failure recovery strategies. FROGBT highlights ontological reasoning’s potential to enhance BT generation with context-awareness and reasoning abilities, paving the way for future research on failure recovery concepts in generated BTs.