Published February 2024 | Version v2
Dataset Open

Event-based Dataset of Assembly Tasks (EDAT24)

  • 1. ROR icon University of Coimbra

Description

Version 2:

Re-upload to replace empty .npy files. 

IMPORTANT NOTE: pick/bridge_roof_2, pick/bridge_roof_3 and pick/bridge_roof_4 files have background movement (a walking person) and, as such, should be used carefully when deploying the dataset.

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Description:

The Event-based Dataset of Assembly Tasks (EDAT24), features four representative assembly primitive actions, idle, pick, place, and screw, collected by using the objects from the open-source benchmark CT-Benchmark. The dataset features a total of 400 recordings, with 100 samples for each primitive action.

Available Data:

The EDAT24 dataset contains a total of 400 sample videos recorded with the DAVIS240C where the event camera captured events and APS frames simultaneously with a resolution of 240 pixels × 180 pixels. DAVIS APS data are captured at 20 fps (frames per second). Event data is available in the original recorded format, .aedat (AEDAT 2.0), and is accompanied with a .csv file containing the timestamps with the start and end time of the recording, and with a .npy file which contains the information from the events (coordinates x and y, timestamp and polarity).

The videos are labelled using the format primitive/task_nSample.aedat, where:

  • primitive corresponds to the various primitive tasks (idle, pick, place, and screw)
  • task corresponds to the name of the part of the CT-Benchmark the user is interacting with.
  • nSample corresponds to the sample number for each task.

The Python code used to record, timestamp and convert into .npy is available at here.

Files

idle.zip

Files (6.7 GB)

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md5:06d2f77a92341a6ebb49a3fe66310f9d
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md5:c448b706c03b473c0965788ec27989fc
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md5:d91b08994f57fd072a91f35820f683d3
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Additional details

Related works

Is continued by
Dataset: 10.5281/zenodo.15005301 (DOI)
Is described by
Journal article: 10.1016/j.dib.2024.110340 (DOI)
Is supplemented by
Software: https://github.com/Robotics-and-AI/DAVIS-data-capture-system (URL)

Funding

Fundação para a Ciência e Tecnologia
Cognitive and safe robot interfaces through action anticipation for the classification of manufacturing primitives 2021.06508.BD