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    Human–Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence

    Source: Journal of Manufacturing Science and Engineering:;2020:;volume( 143 ):;issue: 003::page 031009-1
    Author:
    Nicora, Matteo Lavit
    ,
    Ambrosetti, Roberto
    ,
    Wiens, Gloria J.
    ,
    Fassi, Irene
    DOI: 10.1115/1.4048950
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: To enable safe and effective human–robot collaboration (HRC) in smart manufacturing, seamless integration of sensing, cognition, and prediction into the robot controller is critical for real-time awareness, response, and communication inside a heterogeneous environment (robots, humans, and equipment). The specific research objective is to provide the robot Proactive Adaptive Collaboration Intelligence (PACI) and switching logic within its control architecture in order to give the robot the ability to optimally and dynamically adapt its motions, given a priori knowledge and predefined execution plans for its assigned tasks. The challenge lies in augmenting the robot’s decision-making process to have greater situation awareness and to yield smart robot behaviors/reactions when subject to different levels of human–robot interaction, while maintaining safety and production efficiency. Robot reactive behaviors were achieved via cost function-based switching logic activating the best suited high-level controller. The PACI’s underlying segmentation and switching logic framework is demonstrated to yield a high degree of modularity and flexibility. The performance of the developed control structure subjected to different levels of human–robot interactions was validated in a simulated environment. Open-loop commands were sent to the physical e.DO robot to demonstrate how the proposed framework would behave in a real application.
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      Human–Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4276148
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    contributor authorNicora, Matteo Lavit
    contributor authorAmbrosetti, Roberto
    contributor authorWiens, Gloria J.
    contributor authorFassi, Irene
    date accessioned2022-02-05T21:41:32Z
    date available2022-02-05T21:41:32Z
    date copyright12/16/2020 12:00:00 AM
    date issued2020
    identifier issn1087-1357
    identifier othermanu_143_3_031009.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4276148
    description abstractTo enable safe and effective human–robot collaboration (HRC) in smart manufacturing, seamless integration of sensing, cognition, and prediction into the robot controller is critical for real-time awareness, response, and communication inside a heterogeneous environment (robots, humans, and equipment). The specific research objective is to provide the robot Proactive Adaptive Collaboration Intelligence (PACI) and switching logic within its control architecture in order to give the robot the ability to optimally and dynamically adapt its motions, given a priori knowledge and predefined execution plans for its assigned tasks. The challenge lies in augmenting the robot’s decision-making process to have greater situation awareness and to yield smart robot behaviors/reactions when subject to different levels of human–robot interaction, while maintaining safety and production efficiency. Robot reactive behaviors were achieved via cost function-based switching logic activating the best suited high-level controller. The PACI’s underlying segmentation and switching logic framework is demonstrated to yield a high degree of modularity and flexibility. The performance of the developed control structure subjected to different levels of human–robot interactions was validated in a simulated environment. Open-loop commands were sent to the physical e.DO robot to demonstrate how the proposed framework would behave in a real application.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleHuman–Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence
    typeJournal Paper
    journal volume143
    journal issue3
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4048950
    journal fristpage031009-1
    journal lastpage031009-9
    page9
    treeJournal of Manufacturing Science and Engineering:;2020:;volume( 143 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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