Scaling Up Wearable Cognitive Assistance for Assembly Tasks

 Wearable Cognitive Assistance (WCA) applications run on wearable mobile de-
vices, to provide guidance for real world tasks. Physical assembly tasks have been a
significant focus of research on WCA. We introduce new techniques to support the
development of WCA applications for more complex assembly tasks than previous
techniques supported. In addition, our work reduces the load on developers creating
WCA applications by eliminating the need to collect and label real training images.
We accomplish this by training computer vision models on synthetically generated
images. This dissertation investigates escalation to human experts in cases when a
user is not satisfied with the automated guidance from an application. Lastly, we
develop a new version of a software framework for WCA applications, and evaluate
ways in which WCA applications can benefit from running computations directly on
mobile devices.