English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The deburring processes of parts with complex geometries usually present many challenges to be automated. This paper outlines the machine vision techniques involved in the design and set up of an automated adaptive cognitive robotic system for laser deburring of metal casting complex 3D high quality parts. To carry out deburring process operations of the parts autonomously, 3D machine vision techniques have been used for different purposes, explained in this paper. These machine vision algorithms used along with industrial robots and a high tech laser head, make a fully automated deburring process possible. This setup could potentially be applied to medium sized parts of different light casting alloys (Mg, AlZn, etc.).

Robust 3D Object Model Reconstruction and Matching for Complex Automated Deburring Operations