PhD Defense: 'Process Oriented Ontology Based Robotic Task Planning and Modelling'

This PhD addresses the major obstacles preventing SMEs from effectively integrating robotic solutions into agile manufacturing workflows, such as lack of expertise and high programming costs. It introduces RTMN (Robot Task Modelling Notation), an intuitive modeling language for robotic task planning, supported by ORPP (Ontology for Robotic Task Planning), which provides structured knowledge.

The work evolves into RTMN 2.0, an extended framework targeting human-robot collaboration with built-in safety mechanisms and traceability between business processes and robot control. The final system includes a user-friendly graphical interface built on RTMN and leverages the ORPP ontology in the background for intelligent reasoning. The approach is validated in real-world use cases within the H2020 ACROBA project, confirming its relevance for robotic modeling, planning, and collaboration.

Supervisor: Juan Antonio Corrales

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