Abstract
This paper presents a mixed-reality (MR) application called order picking with mixed reality (OP-MR) for the order-picking activities in a smart warehouse. OP-MR is a set of applications operated by an administrator through a computer server and by the staff using the HoloLens MR device. OP-MR is built to reduce the operational time of an order-picking activity by providing the shortest route to the staff. The HoloLens device displays the order-picking instructions through the MR window, renders virtual navigation, and virtually marks the positions of items. For determining the shortest distance for an order picking, the proposed OP-MR method combines two different algorithms, namely the Held–Karp algorithm in the server and A* algorithm in the client. The Held–Karp algorithm sorts the items in the pick-up list based on the nearest position. Next, the A* algorithm determines the shortest route to ensure that a user travels the shortest distance to pick all the items. To show the effectiveness of the proposed OP-MR method, OP-MR is implemented and experiments are performed. The experimental results show that OP-MR outperforms paper-based order-picking from the viewpoint of completing all the order picking.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Bartholdi, J.J., Hackman, S.T.: Warehouse and Distribution Science: Release 0.89. Supply Chain and Logistics Institute, Atlanta (2008)
Frazelle, E., Frazelle, E.: World-Class Warehousing and Material Handling, vol. 1. McGraw-Hill, New York (2002)
De Koster, M.: Warehousing in the Global Supply Chain, pp. 457–473. Springer, Berlin (2012)
Reif, R., Günthner, W.A.: Pick-by-vision: augmented reality supported order picking. Vis. Comput. 25(5–7), 461 (2009)
Schwerdtfeger, B., Klinker, G.: Supporting order picking with augmented reality. In: Proceedings of the 7th IEEE/ACM international Symposium on Mixed and Augmented Reality IEEE Computer Society, pp. 91–94 (2008)
Gerstweiler, G., Platzer, K., Kaufmann, H.: Dargs: dynamic ar guiding system for indoor environments. Computers 7(1), 5 (2017)
Gerstweiler, G., Vonach, E., Kaufmann, H.: Hymotrack: a mobile ar navigation system for complex indoor environments. Sensors 16(1), 17 (2015)
Shmoys, D.B., Williamson, D.P.: Analyzing the Held-Karp tsp bound: a monotonicity property with application. Inf. Process. Lett. 35(6), 281 (1990)
Cui, S.G., Wang, H., Yang, L.: A simulation study of A-star algorithm for robot path planning. In 16th International Conference on Mechatronics Technology. pp. 506–510 (2012)
Klein, G.: Visual Tracking for Augmented Reality. Ph.D. thesis, University of Cambridge (2006)
Ishii, H.: Augmented reality. Fundamentals and nuclear related applications. Int. Electron. J. Nucl. Saf. Simul. 1(4), 316 (2010)
Funk, M., Shirazi, A.S., Mayer, S., Lischke, L., Schmidt, A.: Pick from here!: an interactive mobile cart using in-situ projection for order picking. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing ACM, pp. 601–609 (2015)
paaron301. How Inside-out Tracking Works—Enthusiast Guide. https://docs.microsoft.com/en-us/windows/mixed-reality/enthusiast-guide/tracking-system. Accessed 7 May 2018
Isler, C., Righetto, G., Morabito, R.: Optimizing the order picking of a scholar and office supplies warehouse. Int. J. Adv. Manuf. Technol. 87(5–8), 2327 (2016)
Bowman, D., Kruijff, E., LaViola Jr., J.J., Poupyrev, I.P.: 3D User Interfaces: Theory and Practice, CourseSmart eTextbook. Addison-Wesley, Boston (2004)
Guo, A., Wu, X., Shen, Z., Starner, T., Baumann, H., Gilliland, S.: Order picking with head-up displays. Computer 48(6), 16 (2015)
Gerstweiler, G., Platzer, K., Kaufmann, H.: Dargs: dynamic AR guiding system for indoor environments. Computers 7(1), 5 (2018)
Bellman, R.: Dynamic programming treatment of the travelling salesman problem. J. ACM (JACM) 9(1), 61 (1962)
Johnson, R., Hoeller, J., Donald, K., Sampaleanu, C., Harrop, R., Risberg, T., Arendsen, A., Davison, D., Kopylenko, D., Pollack, M., et al.: The spring framework-reference documentation. Interface 21, 27 (2004)
Held, M., Karp, R.M.: A dynamic programming approach to sequencing problems. J. Soc. Ind. Appl. Math. 10(1), 196 (1962). https://doi.org/10.1137/0110015
Cui, X., Shi, H.: An overview of pathfinding in navigation mesh. Int. J. Comput. Sci. Netw. Secur. 12(12), 48 (2012)
Cui, X., Shi, H.: A*-based pathfinding in modern computer games. Int. J. Comput. Sci. Netw. Secur. 11(1), 125 (2011)
Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100 (1968)
Goyal, A., Mogha, P., Luthra, R., Sangwan, N.: Path finding: A* or dijkstra’s? IJITE 2, 13–14 (2014)
Acknowledgements
This work was supported by the Kumoh National Institute of Technology (KIT), Gumi, Republic of Korea (No.2019-104-139).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its subsequent amendments or comparable ethical standards.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary material 1 (mp4 32633 KB)
Rights and permissions
About this article
Cite this article
Latif, U.K., Shin, S.Y. OP-MR: the implementation of order picking based on mixed reality in a smart warehouse. Vis Comput 36, 1491–1500 (2020). https://doi.org/10.1007/s00371-019-01745-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00371-019-01745-z