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Unpacking the Complexity of Autonomous Mobile Robot (AMR) Communication Intentions Through Ontology

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Human-Friendly Robotics 2023 (HFR 2023)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 29))

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Abstract

Autonomous Mobile Robots (AMRs) performing intralogistics tasks continue to have a growing presence on shop floors of warehouses and factories. In most cases, they operate in the same working space as human workers and therefore need to communicate with them. In research and industry, there are several communication tools addressing different communication intentions of the robots. In this paper we propose an ontology that provides an overview of the most common and essential intentions of intralogistics AMRs, enabling manufacturers and users to design, describe and verify their robot’s interaction capabilities. The set of intentions is created through an iterative process, including two workshops with experts from the industry. The resulting ontology contains twelve main intentions, each assigned to one or more categories (moving, idle, safety area, special status and safety-relevant). Possible applications include the aforementioned usage by manufacturers and users of AMRs in intralogistics but may be expanded to other robots and fields.

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Acknowledgment

The results presented in this article were developed within the research project “RoboLingo”. The research project was carried out under code 22234 N on behalf of the Research Association Bundesvereinigung Logistik e.V. (BVL). It was funded by the German Federal Ministry of Economics and Climate Protection via the German Federation of Industrial Research Associations “Otto von Guericke” e.V. (AiF).

We also thank Mr. Gabriel Kunkel for his work on the project during his Bachelor’s thesis. His effort has helped us move forward significantly.

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Correspondence to Nicolas Niessen .

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Niessen, N., Rothmeyer, F., Rücker, A., Fottner, J., Bengler, K. (2024). Unpacking the Complexity of Autonomous Mobile Robot (AMR) Communication Intentions Through Ontology. In: Piazza, C., Capsi-Morales, P., Figueredo, L., Keppler, M., Schütze, H. (eds) Human-Friendly Robotics 2023. HFR 2023. Springer Proceedings in Advanced Robotics, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-031-55000-3_16

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