A Review of The Optimization of The Manual Picking System

2021 ◽  
Author(s):  
Min Du ◽  
Xin Wang ◽  
Jie Geng ◽  
Liangpeng Ye
Keyword(s):  
Author(s):  
Jiaxin Guo ◽  
Lian Fu ◽  
Mingkai Jia ◽  
Kaijun Wang ◽  
Shan Liu
Keyword(s):  

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2813
Author(s):  
Muslikhin Muslikhin ◽  
Jenq-Ruey Horng ◽  
Szu-Yueh Yang ◽  
Ming-Shyan Wang ◽  
Baiti-Ahmad Awaluddin

In this study, an Artificial Intelligence of Things (AIoT)-based automated picking system was proposed for the development of an online shop and the services for automated shipping systems. Speed and convenience are two key points in Industry 4.0 and Society 5.0. In the context of online shopping, speed and convenience can be provided by integrating e-commerce platforms with AIoT systems and robots that are following consumers’ needs. Therefore, this proposed system diverts consumers who are moved by AIoT, while robotic manipulators replace human tasks to pick. To prove this idea, we implemented a modified YOLO (You Only Look Once) algorithm as a detection and localization tool for items purchased by consumers. At the same time, the modified YOLOv2 with data-driven mode was used for the process of taking goods from unstructured shop shelves. Our system performance is proven by experiments to meet the expectations in evaluating efficiency, speed, and convenience of the system in Society 5.0’s context.


2021 ◽  
pp. 759-767
Author(s):  
Sawssen Souiden ◽  
Audrey Cerqueus ◽  
Xavier Delorme ◽  
Jean-Lucien Rascle

2019 ◽  
Vol 51 (5) ◽  
pp. 486-500 ◽  
Author(s):  
J. P. van der Gaast ◽  
René B. M. de Koster ◽  
Ivo J. B. F. Adan

Author(s):  
Ching-Chang Wong ◽  
Ren-Jie Chen ◽  
Sheng-Kai Yang ◽  
Shao-Yu Chien ◽  
Shang-Wen Wong ◽  
...  

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