View source for Labelled Force/Torque Time Series from Robotic Wheel Assembly Dataset

<strong>A time series dataset of forces and torques that can be used to develop and test ML models for anomaly detection in robotic assembly. </strong> [[File:Force torque dataset.png|thumb|right|<div style="font-size:88%;line-height: 1.5em">Image 1: Labelled Force/Torque Time Series from Robotic Wheel Assembly Dataset in Zenodo</div>]]

== Asset Description ==
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This dataset contains 524 recordings of 6-dimensional time series representing forces and torques during the assembly of small car model wheels using a Delta robot. The data includes labels indicating the success of each assembly and serves as a valuable resource for anomaly detection and quality control research in robotic assembly processes.
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== Dataset Details ==
=== Dataset Overview ===
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The dataset comprises recordings of forces in three directions (x, y, z) and torques in three directions (x, y, z), sampled at a rate of 0.004 seconds per sample. The data is provided in a CSV file (ForceTorqueTimeSeries.csv), with additional video and documentation files. The dataset is intended for use in anomaly detection models, particularly in the context of robotic assembly processes.
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== Usage ==
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Users can download the dataset and accompanying files from [https://zenodo.org/records/13641620 Zenodo] to develop and test machine learning models for anomaly detection in robotic assembly. The dataset can be used in conjunction with the other provided files, which describe the data acquisition process and preliminary experiments.
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=== Maturity===
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Already Implemented/Available
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=== Licence===
Open source - [https://creativecommons.org/licenses/by/4.0/legalcode CC BY 4.0] 

== Resources ==
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<li>The dataset is available for download in [https://zenodo.org/records/13641620 Zenodo]</li>
<li>Provided by [https://www.cvut.cz/en Czech Technical University in Prague - CTU]</li>
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==== Acknowledgement====
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''This work was co-funded partly by AI REDGIO 5.0 and partly by the European Union under the project [https://roboprox.eu/ ROBOPROX](reg. no. CZ.02.01.01/00/22_008/0004590). In the AI REDGIO 5.0 project it will be used in the Didactic Factory Pilot DFXI: AI-driven Monitoring of Robotic Assembly Process''
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== Relevant Categories==
[[Category:Dataset]][[Category:Machine Learning]][[Category:Anomaly Detection]][[Category:Quality Control]][[Category:Process Optimisation]][[Category:Process Monitoring]][[Category:Predictive Maintenance]][[Category:Fault Detection]][[Category:Edge]]