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arXiv · 2301.03364

Toward an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets

Rodrigo Hernangómez·Alexandros Palaios·Cara Watermann·Daniel Schäufele·Philipp Geuer·Rafail Ismayilov·Mohammad Parvini·Anton Krause·Martin Kasparick·Thomas Neugebauer·Oscar D. Ramos-Cantor·Hugues Tchouankem·Jose Leon Calvo·Bo Chen·Gerhard Fettweis·Sławomir Stańczak
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Abstract

This paper presents two wireless measurement campaigns in industrial testbeds: industrial Vehicle-to-vehicle (iV2V) and industrial Vehicle-to-infrastructure plus Sensor (iV2I+), together with detailed information about the two captured datasets. iV2V covers sidelink communication scenarios between Automated Guided Vehicles (AGVs), while iV2I+ is conducted at an industrial setting where an autonomous cleaning robot is connected to a private cellular network. The combination of different communication technologies within a common measurement methodology provides insights that can be exploited by Machine Learning (ML) for tasks such as fingerprinting, line-of-sight detection, prediction of quality of service or link selection. Moreover, the datasets are publicly available, labelled and prefiltered for fast on-boarding and applicability.

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Rodrigo Hernangómez, Alexandros Palaios, Cara Watermann, Daniel Schäufele, Philipp Geuer, Rafail Ismayilov, Mohammad Parvini, Anton Krause, Martin Kasparick, Thomas Neugebauer, Oscar D. Ramos-Cantor, Hugues Tchouankem, Jose Leon Calvo, Bo Chen, Gerhard Fettweis, Sławomir Stańczak. 2022-12-20. Toward an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets. https://doi.org/10.1109/mcom.001.2300494

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