TY - JOUR
T1 - Guidance and visualization of optimized packing solutions
AU - Techasarntikul, Nattaon
AU - Ratsamee, Photchara
AU - Orlosky, Jason
AU - Mashita, Tomohiro
AU - Uranishi, Yuki
AU - Kiyokawa, Kiyoshi
AU - Takemura, Haruo
N1 - Funding Information:
Jason Orlosky received a bachelors de- gree in Computer Engineering from the Georgia Institute of Technology in 2006. He then worked in information technol-ogy for three years in the United States before returning to school in 2010 to study Japanese language and literature. In 2011, he studied abroad as a research student at Osaka University, where he graduated with his Ph.D. in 2016. He has received a fellowship from the Japan Society for the Promotion of Science from 2015–2017, and is currently a specially appointed Assistant Professor at Osaka University and adjunct Faculty at Augusta University. His topics include Augmented Reality, Artificial Intelligence, and Vision Augmentation.
Publisher Copyright:
© 2020 Information Processing Society of Japan.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Packing support system
KW - Spatial augmented reality
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U2 - 10.2197/ipsjjip.28.193
DO - 10.2197/ipsjjip.28.193
M3 - Article
AN - SCOPUS:85083224096
SN - 0387-5806
VL - 28
SP - 193
EP - 202
JO - Journal of Information Processing
JF - Journal of Information Processing
ER -