Zebisch R, Merz N, Franke J, Reitelshöfer S, Schilp J (2026)
Publication Type: Conference contribution
Publication year: 2026
Publisher: IEEE Computer Society
Pages Range: 7-12
Conference Proceedings Title: Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO
Event location: Vienna, AUT
ISBN: 9798331564452
DOI: 10.1109/ARSO68304.2026.11536115
Ontological models have proven to be an effective approach in robot cognition with applications in task planning or semantic-driven communication. However, to the authors’ knowledge, no domain ontology currently exists for the specialized field of social robotics. Therefore, this paper introduces SoBots, a meta-model that provides a semantic foundation for social robotics. SoBots integrates the Sharework Ontology for Human-Robot Collaboration with DOLCE+DnS Ultralite and the Semantic Sensor Network ontology, and extends them with axioms for capability-based task execution, Belief-Desire-Intention modeling, and social interaction. The resulting domain-specific ontology explicitly links tasks, agent capabilities, intentions, and interaction structures. Beyond the theoretical level, a gap often remains between semantic modeling and practical applicability. To address this, the paper further presents an interactive simulation framework for human-robot collaboration that builds on the proposed semantic foundation. The framework leverages task-decomposition graphs from the Sharework Ontology to automatically derive discrete-event simulation contexts based on an agent’s occurrent desires and intentions.
APA:
Zebisch, R., Merz, N., Franke, J., Reitelshöfer, S., & Schilp, J. (2026). SoBots: A Domain Ontology for Social Robotics. In Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO (pp. 7-12). Vienna, AUT: IEEE Computer Society.
MLA:
Zebisch, Raoul, et al. "SoBots: A Domain Ontology for Social Robotics." Proceedings of the 2026 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2026, Vienna, AUT IEEE Computer Society, 2026. 7-12.
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