We report on the long process of exploring, evaluating and refining augmented reality-based methods to support the order picking process of logistics applications. Order picking means that workers have to pick items out of numbered boxes in a warehouse, according to a work order. To support those workers, we have evaluated different HMD-based visualizations in six user studies, starting in a laboratory setup and continuing later in an industrial environment. This was a challenging task, as we had to conquer different kinds of navigation problems from very coarse to very fine granularity and accuracy. The resulting setup consists of a combined and adaptive visualization to precisely and efficiently guide the user even if the actual picking target is not always in the field of view of the HMD.
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To be able to adapt with minimal effort to global dynamic changes.
And probably resulting in one of the most outworn HMDs.
Repeated Measure ANOVA using a General Linear Model.
Fisher’s Least Significant Difference test.
Original statement in German: “Wie sollte es auch sonst funktionieren!”
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The authors would like to thank T. Frimor, E. Yükselgil, M. Stadter, X. Pan, M. Stadtler, M. Meister and all our test persons. Furthermore, we thank ART GmbH, Germany for lending the equipment. This work was partially supported by the ForLog and trackframe projects of the Bayerische Forschungsstiftung (BFS).
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Schwerdtfeger, B., Reif, R., Günthner, W.A. et al. Pick-by-vision: there is something to pick at the end of the augmented tunnel. Virtual Reality 15, 213–223 (2011). https://doi.org/10.1007/s10055-011-0187-9