Towards 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, Sławomir Stańczak, Gerhard Fettweis

This paper presents two wireless measurement campaigns in industrial testbeds: industrial Vehicle-to-vehicle (iV2V) and industrial Vehicle-to-infrastructure plus Sensor (iV2I+). Detailed information about the two captured datasets is provided as well. 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, together with 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 labelled and pre-filtered for fast on-boarding and applicability. The corresponding testbeds and measurements are also presented in detail for both datasets.

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