Knowledge Graphs Enhance Robotic Mission Design.

This paper outlines a detailed methodology for integrating knowledge graphs into ROS 2 (Robot Operating System 2) frameworks to significantly enhance the intelligence and efficiency of autonomous robotic missions. The proposed approach systematically guides users through several critical steps: defining the initial and target states of a mission, breaking down complex objectives into structured tasks and subtasks, and then logically sequencing these operations. A core component of this methodology involves representing all task-related data within a knowledge graph, which serves as a central repository for semantic information and relationships. This knowledge-driven design is then implemented using a high-level language to orchestrate the mission. A practical demonstration within the Aerostack2 framework showcased its effectiveness in a simulated search and rescue scenario, where drones autonomously located a target, illustrating how knowledge graphs can improve robotic decision-making and overall mission performance.