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Usage Identification of Anomaly Detection in an Industrial Context

Usage Identification of Anomaly Detection in an Industrial Context

Authors :
Vahid Salehi
Philip Kurrek
Mark Jocas
Giovanni Luca Masala
Firas Zoghlami
Source :
Proceedings of the Design Society: International Conference on Engineering Design. 1:3761-3770
Publication Year :
2019
Publisher :
Cambridge University Press (CUP), 2019.

Abstract

The use of flexible and autonomous robotics systems is the solution for the automation task of the production and intra-logistics environments. This dynamic context requires the robot to be aware of its surroundings through the whole task, also after accomplishing the gripping action. We present an anomaly detection approach based on unsupervised learning and reconstruction fidelity of image data. We design our method to enhance the dynamic environment perception of robotics systems and apply it in a palletizing robot, in order to perceive and detect changes to its surrounding and process after the gripping step. Our proposed approach achieves the performance targeted by the considered industrial requirements.

Details

ISSN :
22204342
Volume :
1
Database :
OpenAIRE
Journal :
Proceedings of the Design Society: International Conference on Engineering Design
Accession number :
edsair.doi...........961b358e9ca77ac97beef449b1dc7648
Full Text :
https://doi.org/10.1017/dsi.2019.383