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Usage Identification of Anomaly Detection in an Industrial Context
Usage Identification of Anomaly Detection in an Industrial Context
- 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.
- Subjects :
- 0209 industrial biotechnology
Industry 4.0
business.industry
Computer science
020206 networking & telecommunications
Robotics
Context (language use)
02 engineering and technology
General Medicine
Automation
Task (project management)
020901 industrial engineering & automation
Human–computer interaction
0202 electrical engineering, electronic engineering, information engineering
Unsupervised learning
Robot
Anomaly detection
Artificial intelligence
business
Subjects
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