Hazards&Robots: A dataset for visual anomaly detection in robotics.
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ABSTRACT:
SUBMITTER: Mantegazza D
PROVIDER: S-EPMC10294035 | biostudies-literature | 2023 Jun
REPOSITORIES: biostudies-literature
Publications
Hazards&Robots: A dataset for visual anomaly detection in robotics.
Mantegazza Dario D Xhyra Alind A Gambardella Luca M LM Giusti Alessandro A Guzzi Jérôme J
Data in brief 20230524
We propose Hazards&Robots, a dataset for Visual Anomaly Detection in Robotics. The dataset is composed of 324,408 RGB frames, and corresponding feature vectors; it contains 145,470 normal frames and 178,938 anomalous ones categorized in 20 different anomaly classes. The dataset can be used to train and test current and novel visual anomaly detection methods such as those based on deep learning vision models. The data is recorded with a DJI Robomaster S1 front facing camera. The ground robot, con ...[more]
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