OCRA - An Ontology for Collaborative Robotics and Adaptation

Abstract - Industrial collaborative robots will be used in unstructured scenarios and a large variety of tasks in the near future. These robots shall collaborate with humans, who will add uncertainty and safety constraints to the execution of industrial robotic tasks. Hence, trustworthy collaborative robots must be able to reason about their collaboration's requirements (e.g. safety), as well as the adaptation of their plans due to unexpected situations. A common approach for reasoning is to represent the knowledge of interest using logic-based formalisms, such as ontologies. However, there is not an established ontology defining notions such as collaboration or adaptation yet. In this article, we propose an Ontology for Collaborative Robotics and Adaptation (OCRA), which is built around two main notions: collaboration, and plan adaptation. We analyzed several works in the literature to ensure that our ontology was inclusive and covered the different perspectives. OCRA ensures a reliable human-robot collaboration, since robots can formalize, explain, and reason about their plan adaptations and collaborations in unstructured collaborative robotic scenarios. Furthermore, our ontology enhances the reusability of the domain's terminology, allowing robots to represent their knowledge about different collaborative and adaptive situations. We validate our implementation demonstrating which competency questions a robot may answer using OCRA. Specifically, we apply it in a use case where a human and a robot collaborate on the execution of a task.


Demo of the experiments done with one user who collaborated with a robot on the accomplisment of a shared task: filling a tray with tokens.


OCRA's OWL DL version was implemented using Protégé, the developed OWL file is publicly available to facilitate reuse and comparison OCRA. The application ontology that was implemented for the collaborative task of filling a tray can be downloaded here.