This work introduces a three-stage approach, called the Reduced Unsupervised Reconstruction Anomaly Detection (RURAD). RURAD detects occurring pose anomalies, ...
Aug 11, 2021 · Combining the learned features with a prediction system, we can detect irregularities in high dimensional data feed (e.g. video of a robot ...
Unsupervised Pose Anomaly Detection for Dynamic Robotic ...
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RURAD detects occurring pose anomalies, which allow the robot to react to dynamic events by adjusting the placing pose, and achieves a state-of-the-art ...
These environments require the robots to adjust the calculated poses while they are conducting their tasks in the grip- ping and the post gripping phase. This ...
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Anomaly detection is used as a trigger for the pose adjustment step in a dynamic environment where an external event changes the initial relative pose of two ...
Unsupervised anomaly detection in time series using lstm-based autoencoders. In 2019 IEEE International Conference on Advanced Trends in Information Theory ...
Unsupervised pose anomaly detection for dynamic robotic environments. F Zoghlami, P Kurrek, M Jocas, G Masala, V Salehi. 2020 IEEE Conference on Industrial ...
Abstract—On-line detection of anomalies in time series is a key technique used in various event-sensitive scenarios such as robotic.
This study suggests an alternative approach to identifying anomalous behavior within ICSs by means of unsupervised machine learning.
UAD-GAN can fit the data distribution and detect anomalies efficiently. Extensive experiments show that UAD-GAN achieves state-of-the-art performance compared ...