Augmented Reality Circuit Learning

• Published in: IEEE International Symposium on Circuits and Systems proceedings pp. 1 - 5
• Main Authors: Wang, Hao, Cheung, Sen-Ching S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2021
• Subjects: Augmented reality; Breadboard; circuit learning; Pipelines; Real-time systems; Software; Solid modeling; Three-dimensional displays; vision-based circuit inspection
• ISBN: 9781728192017; 1728192013
• ISSN: 2158-1525
• DOI: 10.1109/ISCAS51556.2021.9401464

Building electronic circuits is one of the most common hands-on activities in learning STEM subjects. Beginning students often find it difficult to translate a circuit schematic into the construction of the physical circuit on a breadboard. In this paper, we describe an Augmented Reality circuit learning software that can provide students with step-by-step instructions by placing virtual circuit components on a physical breadboard. We propose a novel image processing pipeline that can robustly identify the planar structure of a breadboard, even in the presence of occluding circuit components on the breadboard. Using a commercially available library of 3D circuit component models, the estimated 3D structure of the breadboard allows us to render arbitrary circuit components on it in real time. Experimental results demonstrate that our algorithms are accurate and can produce realistic-looking virtual circuits.