Failure Recovery with Ontologically Generated Behaviour Trees

Master Thesis (2023)
Author(s)

W. Jaber (TU Delft - Mechanical Engineering)

Contributor(s)

Carlos Hernandez – Mentor (TU Delft - Robot Dynamics)

L. Peternel – Graduation committee member (TU Delft - Human-Robot Interaction)

Christian Pek – Coach (TU Delft - Robot Dynamics)

Faculty
Mechanical Engineering
Copyright
© 2023 Wissam Jaber
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Wissam Jaber
Graduation Date
22-09-2023
Awarding Institution
Delft University of Technology
Programme
['Mechanical Engineering | Vehicle Engineering | Cognitive Robotics']
Faculty
Mechanical Engineering
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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.

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