Failure Recovery with Ontologically Generated Behaviour Trees

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.