Guidance and visualization of optimized packing solutions

Nattaon Techasarntikul, Photchara Ratsamee, Jason Orlosky, Tomohiro Mashita, Yuki Uranishi, Kiyoshi Kiyokawa, Haruo Takemura

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Packing optimization is a challenging and time-consuming task for a number of industry and logistics ap-plications. Efficient packing can reduce the cost of storage and shipping and also guarantee that damage will not occur during shipping. To help address this problem, we propose a spatial augmented reality-based support system for assist-ing workers with packing optimization. Our packing support system first uses an RGB-D camera to acquire color and depth information of the items to be packed and the destination container. Then, object segmentation and dimension estimation are simultaneously carried out, and the position and orientation of packing items inside the container are calculated using a bin-packing algorithm. Finally, the optimized packing instructions are projected onto the user’s work area. We then developed and tested two user interfaces (UI) for visualizing instructions called Rotation and Object Movement. Experimental results showed that both methods help reduce packing time up to 57.89% in Rotation and 55.63% in Object Movement, compared to a non-UI method.

Original languageEnglish (US)
Pages (from-to)193-202
Number of pages10
JournalJournal of Information Processing
Volume28
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Packing support system
  • Spatial augmented reality

ASJC Scopus subject areas

  • Computer Science(all)

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