This paper presents a comprehensive methodology for implementing knowledge graphs in ROS 2 systems, aiming to enhance the efficiency and intelligence of autonomous robotic missions. The methodology encompasses several key steps: defining initial and target conditions, structuring tasks and subtasks, planning their sequence, representing task-related data in a knowledge graph, and designing the mission using a high-level language. Each step builds on the previous one to ensure a cohesive process from initial setup to final execution. A practical implementation within the Aerostack2 framework is demonstrated through a simulated search and rescue mission in a Gazebo environment, where drones autonomously locate a target. This implementation highlights the effectiveness of the methodology in improving decision-making and mission performance by leveraging knowledge graphs.
@article{arxiv.2601.20797,
title = {A Methodology for Designing Knowledge-Driven Missions for Robots},
author = {Guillermo GP-Lenza and Carmen DR. Pita-Romero and Miguel Fernandez-Cortizas and Pascual Campoy},
journal= {arXiv preprint arXiv:2601.20797},
year = {2026}
}