Publication
Ontological framework for high-level task replanning for autonomous robotic systems
| Summary: | 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. |
|---|---|
| Main Authors: | Bernardo, Rodrigo |
| Other Authors: | Sousa, João M.C.; Gonçalves, Paulo |
| Subject: | Semantic knowledge Ontologies Autonomous robotic systems Replanning Robot control platforms |
| Year: | 2025 |
| Country: | Portugal |
| Document type: | research article |
| Access type: | open access |
| Associated institution: | Universidade Politécnica de Castelo Branco |
| Language: | English |
| Origin: | Repositório Científico da Universidade Politécnica de Castelo Branco |
| Summary: | 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. |
|---|
Funded activities
No funded projects found.