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Ontological framework for high-level task replanning for autonomous robotic systems
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Orientador(es)
Resumo(s)
Several frameworks for robot control platforms have been developed in recent years. However, strategies that incorporate automatic replanning have to be explored, which is a requirement for Autonomous Robotic Systems (ARS) to be widely adopted. Ontologies can play an essential role by providing a structured representation of knowledge. This paper proposes a new framework capable of replanning high-level tasks in failure situations for ARSs. The framework utilizes an ontology-based reasoning engine to overcome constraints and execute tasks through Behavior Trees (BTs). The proposed framework was implemented and validated in a real experimental environment using an Autonomous Mobile Robot (AMR) sharing a plan with a human operator. The proposed framework uses semantic reasoning in the planning system, offering a promising solution to improve the adaptability and efficiency of ARSs.
Descrição
Palavras-chave
Semantic knowledge Ontologies Autonomous robotic systems Replanning Robot control platforms
Contexto Educativo
Citação
BERNARDO, Rodrigo ; SOUSA, João M.C. ; GOÇALVES, Paulo J.S. (2025) - Ontological framework for high-level task replanning for autonomous robotic systems. Robotics and Autonomous Systems. Vol. 184, p. 104861. DOI: 10.1016/j.robot.2024.104861.
Editora
Elsevier