Year-end Sale % OFF 
Abstract
Artificial Intelligence (AI) based algorithms are being used increasingly to support industrial robots in the automation of assembly processes. The objective of this work is to detect bores of different geometry, appearance, and inner structure for automating a high-mix low-volume assembly line. Two most widely used AI algorithms namely, Single Shot Detection (SSD) and You Only Look Once (YOLO) have been used to perform the bore detection process. The results obtained by these algorithms have been compared with the conventional detection algorithm (Gradient filter) using the standard metrics used for evaluating the performance of the detection algorithms. The obtained results demonstrate the efficiency and robustness of AI-based algorithms for the detection as they exhibit better performance than the conventional detection method.
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
