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    Q-Model: An Artificial Intelligence Based Methodology for the Development of Autonomous Robots

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 006::page 061006-1
    Author:
    Kurrek, Philip
    ,
    Zoghlami, Firas
    ,
    Jocas, Mark
    ,
    Stoelen, Martin
    ,
    Salehi, Vahid
    DOI: 10.1115/1.4046992
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The increasing individualization of products reinforces the importance of decoupled factories in production processes. Artificial intelligence (AI) is a recognized technology for problem solving and accelerates automation by enabling systems to act independently. In the field of robotics, there are new deep learning approaches which make robotic control systems human independent. This work provides a literature overview of the current state of development methodologies, showing that there are only limited methods available for the development of artificial intelligent robots. We present a novel development methodology based on artificial intelligence, particularly deep reinforcement learning. The so-called Q-model can enable robots to learn specific tasks independently. In summary, we show how an AI-based methodology assists the development of autonomous robots along the product lifecycle.
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      Q-Model: An Artificial Intelligence Based Methodology for the Development of Autonomous Robots

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4274914
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    contributor authorKurrek, Philip
    contributor authorZoghlami, Firas
    contributor authorJocas, Mark
    contributor authorStoelen, Martin
    contributor authorSalehi, Vahid
    date accessioned2022-02-04T22:07:13Z
    date available2022-02-04T22:07:13Z
    date copyright6/9/2020 12:00:00 AM
    date issued2020
    identifier issn1530-9827
    identifier otherjcise_20_6_061006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274914
    description abstractThe increasing individualization of products reinforces the importance of decoupled factories in production processes. Artificial intelligence (AI) is a recognized technology for problem solving and accelerates automation by enabling systems to act independently. In the field of robotics, there are new deep learning approaches which make robotic control systems human independent. This work provides a literature overview of the current state of development methodologies, showing that there are only limited methods available for the development of artificial intelligent robots. We present a novel development methodology based on artificial intelligence, particularly deep reinforcement learning. The so-called Q-model can enable robots to learn specific tasks independently. In summary, we show how an AI-based methodology assists the development of autonomous robots along the product lifecycle.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleQ-Model: An Artificial Intelligence Based Methodology for the Development of Autonomous Robots
    typeJournal Paper
    journal volume20
    journal issue6
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4046992
    journal fristpage061006-1
    journal lastpage061006-9
    page9
    treeJournal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 006
    contenttypeFulltext
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