Search

Skip to main content Accessibility help

Home
Search

Only show content I have access to (1)

Only show open access (1)

Articles (1)

Over 3 years (1)

From year:

To year:

Apply

robotics perception

Proceedings of the Design Society: International Conference on Engineering Design (1)

View selected items
Save to my bookmarks
Export citations
Download PDF (zip)
Save to Kindle
Save to Dropbox
Save to Google Drive
Save content to
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to .

To save content items to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Please be advised that item(s) you selected are not available.
You are about to save
Your Kindle email address

Please provide your Kindle email.

@free.kindle.com @kindle.com (service fees apply)

By using this service, you agree that you will only keep content for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services

1 results

Usage Identification of Anomaly Detection in an Industrial Context
Part of
- Systems Engineering
Firas Zoghlami, Philip Kurrek, Mark Jocas, Giovanni Masala, Vahid Salehi
Journal:

Proceedings of the Design Society: International Conference on Engineering Design / Volume 1 / Issue 1 / July 2019

Published online by Cambridge University Press:

26 July 2019, pp. 3761-3770

Print publication:

July 2019
- Article
- - You have access
  - Open access
- PDF
- Export citation
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.