Bucket Hooking Identification System Driven By Computer Vision and AI Technology

Assuring operators' safety and proper working conditions is a fundamental aspect in harsh and dangerous environments like the meltshop. For example, the automatic movement of buckets and ladles in a steel plant requires precise positioning and advanced vision systems to confirm proper material engagement. Danieli presents a computer vision-based system that complements the current open-loop positioning procedure, performing a pickup-and-deposit operation's visual confirmation, complete with on-field results. The system processes images captured from cameras through a deep convolutional neural network that identifies relevant objects and allows for the correct positioning of the hooks on the trunnions to be established.

Mr. Loris Busolini | Danieli Automation
 

Luigi Mariotto | Danieli & C. Officine Meccaniche S.p.A.
 

Mrs. Nicol Miculan | Danieli & C. Officine Meccaniche S.p.A.
 

Mr. Francesco Maria Rapolla | Danieli & C. Officine Meccaniche S.p.A.
 

Matteo Sandri | Danieli & C. Officine Meccaniche S.p.A.