The featured dataset, the Event-based Dataset of Assembly Tasks (EDAT24), showcases a selection of manufacturing primitive tasks (idle, pick, place, and screw), which are basic actions performed by human operators in any manufacturing assembly. The data were captured using a DAVIS240C event camera, an asynchronous vision sensor that registers events when changes in light intensity value occur. Events are a lightweight data format for conveying visual information and are well-suited for real-time detection and analysis of human motion. Each manufacturing primitive has 100 recorded samples of DAVIS240C data, including events and greyscale frames, for a total of 400 samples. In the dataset, the user interacts with objects from the open-source CT-Benchmark in front of the static DAVIS event camera. All data are made available in raw form (.aedat) and in pre-processed form (.npy). Custom-built Python code is made available together with the dataset to aid researchers to add new manufacturing primitives or extend the dataset with more samples.

翻译：本数据集名为基于事件的装配任务数据集（EDAT24），展示了一系列制造基础任务（空闲、拾取、放置与拧紧），这些任务是人类操作员在任何制造装配过程中执行的基本动作。数据采集使用DAVIS240C事件相机完成，这是一种异步视觉传感器，可在光强值发生变化时记录事件。事件是一种用于传递视觉信息的轻量级数据格式，非常适用于人体运动的实时检测与分析。每种制造基础任务均包含100个DAVIS240C数据样本（含事件与灰度帧），总计400个样本。数据集中，用户在静态DAVIS事件相机前操作开源CT-Benchmark中的物体。所有数据均提供原始格式（.aedat）与预处理格式（.npy）。随数据集同时公开定制开发的Python代码，以帮助研究人员添加新的制造基础任务或扩展更多样本。