OP-MR: the implementation of order picking based on mixed reality in a smart warehouse

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.

[1]  Abhishek Goyal,et al.  PATH FINDING: A* OR DIJKSTRA’S? , 2014 .

[2]  Ben Blachnitzky,et al.  Augmented reality , 2012, 2012 IEEE Hot Chips 24 Symposium (HCS).

[3]  M. Held,et al.  A dynamic programming approach to sequencing problems , 1962, ACM National Meeting.

[4]  Edward H. Frazelle,et al.  World-Class Warehousing and Material Handling , 2001 .

[5]  Willibald A. Günthner,et al.  Pick-by-vision: augmented reality supported order picking , 2009, The Visual Computer.

[6]  Richard Bellman,et al.  Dynamic Programming Treatment of the Travelling Salesman Problem , 1962, JACM.

[7]  Kees Jan Roodbergen,et al.  Warehousing in the Global Supply Chain , 2012 .

[8]  Markus Funk,et al.  Pick from here!: an interactive mobile cart using in-situ projection for order picking , 2015, UbiComp.

[9]  Hannes Kaufmann,et al.  HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments , 2015, Sensors.

[10]  Hao Shi,et al.  An Overview of Pathfinding in Navigation Mesh , 2012 .

[11]  M. B. M. de Koster Warehouse Assessment in a Single Tour , 2012 .

[12]  Xiao Cui,et al.  A*-based Pathfinding in Modern Computer Games , 2011 .

[13]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[14]  Reinaldo Morabito,et al.  Optimizing the order picking of a scholar and office supplies warehouse , 2016 .

[15]  Ishii Hirotake Augmented reality: fundamentals and nuclear related applications , 2010 .

[16]  Dieter Schmalstieg,et al.  Visual tracking for Augmented Reality , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

[17]  Gudrun Klinker,et al.  Supporting order picking with Augmented Reality , 2008, 2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality.

[18]  Hannes Kaufmann,et al.  DARGS: Dynamic AR Guiding System for Indoor Environments , 2018, Comput..

[19]  Xiaolong Wu,et al.  Order Picking with Head-Up Displays , 2015, Computer.

[20]  David P. Williamson,et al.  Analyzing the Held-Karp TSP Bound: A Monotonicity Property with Application , 1990, Inf. Process. Lett..