Automation, Control and Intelligent Systems

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Design Optimization of Amazon Robotics

Received: 04 May 2016    Accepted: 14 May 2016    Published: 30 May 2016
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Abstract

In the era of e-commerce, the logistic distribution center is put in the center role of order picking for the sake of meeting the needs of different customer orders, hence, improving the automation and work capacity of distribution center becomes research priority in the fields of logistics and warehousing. The objective of this article is to solve the shortcomings of currently traditional distribution center picking system with high automation by introducing a new method of picking provided by Amazon’s Kiva system, that is, mobile racking with goods is broke out to sorting table by Kiva mobile robots named AGVs (automated guided vehicles), which could not only reduce the walk time and labor cost, but improve efficiency. This article starts with the constitutive requirements of the Amazon KIVA robotic systems, and then some key problems of Kiva picking system and design optimization about task allocation and path planning of multi-robots are demonstrated respectively in this article. Finally, the content is summarized and the application of robotic system in is simply demonstrated and prospected.

DOI 10.11648/j.acis.20160402.17
Published in Automation, Control and Intelligent Systems (Volume 4, Issue 2, April 2016)
Page(s) 48-52
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Amazon Kiva Robotics, Picking System, Design Optimization

References
[1] News & Trends. “Amazon is equipped with robots to meet holiday season”. World vision, vol. 23, pp. 36-37, 2014.
[2] Industry dynamics. “Amazon use robots handle orders”. Journal of Robot Technique and Application, vol 1, pp58-60, 2015.
[3] X. M. Zhang. “The order picking optimization and algorithm research based on Kiva system,” Master Thesis, Beijing: Beijing University of Posts and Telecommunications, 2015.
[4] D’Andrea R, Wuman P. Future challenges of coordinating hundreds of autonomous vehicles in distribution facilities//Techonologies for Practical Robot Applications, 2008. TePRA2008. IEEE International Conference on. IEEE, pp 80-83, 2008.
[5] J. P. Wu. “Analysis and prospect of Amazon kiva robot application,” Journal of Logistics & Material Handling, vol. 10, pp 159-162, 2015.
[6] M. Zamirian, A. V. Kamyad, M. H. Farahi. “A novel algorithm for solving optimal path planning problems based on parametrization method and fuzzy aggregation,” Journal of Physics Letters A. 2009 (38).
[7] P. Klaus. Logistics research: a 50 years’ march of ideas. Logistics Research. 2009.
[8] J. Enright, P. R. Wurman. “Optimization and Coordinated Autonomy in Mobile Fulfillment Systems. Automated Action Planning for Autonomous Mobile Robots,” 2011.
[9] S. Qi. “Study on path planning of AGV system,” Master Thesis, Zhejiang: Zhejiang University, 2012.
[10] R. Peter. Wurman, Raffaello D’Andrea, and Mick Mountz. “Coordinating hundreds of cooperative, autonomous vehicles in warehouses,” Journal of AI Magazine, vol 29, no. 1, 2008.
[11] Ruey-Jer "Bryan" Jean, R. R Sinkovics, D. Kim. “The impact of technological, organizational and environmental characteristivs on electronic collaboration and relationship performance in international customer-supplier relationships,” Journal of Information and Management, 2014.
[12] T. Frank, C. Q. Zhang. “To the robot era of apple, amazon and Google,” Journal of World Science, vol 3, pp 53-54, 2014.
Author Information
  • School of Information, Beijing Wuzi University, Beijing, China

  • Graduate Department, Beijing Wuzi University, Beijing, China

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    Jun-tao Li, Hong-jian Liu. (2016). Design Optimization of Amazon Robotics. Automation, Control and Intelligent Systems, 4(2), 48-52. https://doi.org/10.11648/j.acis.20160402.17

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    ACS Style

    Jun-tao Li; Hong-jian Liu. Design Optimization of Amazon Robotics. Autom. Control Intell. Syst. 2016, 4(2), 48-52. doi: 10.11648/j.acis.20160402.17

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    AMA Style

    Jun-tao Li, Hong-jian Liu. Design Optimization of Amazon Robotics. Autom Control Intell Syst. 2016;4(2):48-52. doi: 10.11648/j.acis.20160402.17

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  • @article{10.11648/j.acis.20160402.17,
      author = {Jun-tao Li and Hong-jian Liu},
      title = {Design Optimization of Amazon Robotics},
      journal = {Automation, Control and Intelligent Systems},
      volume = {4},
      number = {2},
      pages = {48-52},
      doi = {10.11648/j.acis.20160402.17},
      url = {https://doi.org/10.11648/j.acis.20160402.17},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.acis.20160402.17},
      abstract = {In the era of e-commerce, the logistic distribution center is put in the center role of order picking for the sake of meeting the needs of different customer orders, hence, improving the automation and work capacity of distribution center becomes research priority in the fields of logistics and warehousing. The objective of this article is to solve the shortcomings of currently traditional distribution center picking system with high automation by introducing a new method of picking provided by Amazon’s Kiva system, that is, mobile racking with goods is broke out to sorting table by Kiva mobile robots named AGVs (automated guided vehicles), which could not only reduce the walk time and labor cost, but improve efficiency. This article starts with the constitutive requirements of the Amazon KIVA robotic systems, and then some key problems of Kiva picking system and design optimization about task allocation and path planning of multi-robots are demonstrated respectively in this article. Finally, the content is summarized and the application of robotic system in is simply demonstrated and prospected.},
     year = {2016}
    }
    

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    T1  - Design Optimization of Amazon Robotics
    AU  - Jun-tao Li
    AU  - Hong-jian Liu
    Y1  - 2016/05/30
    PY  - 2016
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    JO  - Automation, Control and Intelligent Systems
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    PB  - Science Publishing Group
    SN  - 2328-5591
    UR  - https://doi.org/10.11648/j.acis.20160402.17
    AB  - In the era of e-commerce, the logistic distribution center is put in the center role of order picking for the sake of meeting the needs of different customer orders, hence, improving the automation and work capacity of distribution center becomes research priority in the fields of logistics and warehousing. The objective of this article is to solve the shortcomings of currently traditional distribution center picking system with high automation by introducing a new method of picking provided by Amazon’s Kiva system, that is, mobile racking with goods is broke out to sorting table by Kiva mobile robots named AGVs (automated guided vehicles), which could not only reduce the walk time and labor cost, but improve efficiency. This article starts with the constitutive requirements of the Amazon KIVA robotic systems, and then some key problems of Kiva picking system and design optimization about task allocation and path planning of multi-robots are demonstrated respectively in this article. Finally, the content is summarized and the application of robotic system in is simply demonstrated and prospected.
    VL  - 4
    IS  - 2
    ER  - 

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