To fulfill the promises of Augmented Reality (AR) in the manufacturing and maintenance industry, the development of AR application has to become faster, simpler and cheaper. Since typical AR applications make use of basic functionality like reading markers and displaying simple overlays, a clever combination of such basic building blocks would ease the development of complex AR applications. In this paper, we present a distributed architecture for creating and managing basic AR services, e.g. for information management, user interaction, and documentation. This way, complex AR processes can be orchestrated from those services for being used in different application domains.

Order picking is the process of collecting items from an assortment in inventory. It represents one of the main activities performed in warehouses and accounts for about 60% of the total operational costs of a warehouse. In previous work, we demonstrated the advantages of a head-mounted display (HMD) based picking chart over a traditional text-based pick list, a paper-based graphical pick chart, and a mobile pick-by-voice system. Here we perform two user studies that suggest that adding color cues and context sensing via a laser rangefinder improves picking accuracy with the HMD system. We also examine other variants of the pick chart, such as adding symbols, textual identifiers, images, and descriptions and their effect on accuracy, speed, and subjective usability.

Evaluations of task guidance systems often focus on evaluations of new technologies rather than comparing the nuances of interaction across the various systems. One common domain for task guidance systems is warehouse order picking. We present a method involving an easily reproducible ecologically motivated order picking environment for quantitative user studies designed to reveal differences in interactions. Using this environment, we perform a 12 participant within-subjects experiment demonstrating the advantages of a head-mounted display based picking chart over a traditional text-based pick list, a paper-based graphical pick chart, and a mobile pick-by-voice system. The test environment proved sufficiently sensitive, showing statistically significant results along several metrics with the head-mounted display system performing the best. We also provide a detailed analysis of the strategies adopted by our participants.

Warehouse picking is a traditional part of assembly and inventory control, and several commercial wearable computers address this market. However, head mounted displays (HMDs) are not yet used in these company's products. We present a 16 person user study that compares the efficiency and perceived workload of paper picking lists versus a HMD system aided by contextual cueing. With practice, users of the HMD system made significantly faster picks and made less mistakes related to missing or additional picked items overall.

Audio interfaces for mobile and wearable computing are in an early state of development. User studies concentrate on the usability of audio interfaces as means of interacting with a device but leave out the question of how an audio interface can aid at performing a main task. Studying the impact of audio interfaces in computer aided tasks for wearable and mobile computing will provide guidelines for hands-free interface design and information presentation. To be able to measure the performance a simulated main task is used where varying mental loads can be setup. Providing an index of difficulty for the simulated task, users studies will reveal how effective an audio interface can be used to convey information to aid at a task.