Human and robot collaboration represents an interesting development direction for traditional industrial robotic solutions. Especially for those cases where the operations are difficult to automate or burdensome for manual execution, the mutual exchange of human sensitivity and robot repeatability represents an effective approach. Nevertheless, industrial robots are poorly involved for collaborative tasks since specific safety countermeasures are required to avoid all the potential hazards. Consequently, the design and assessment of safety solutions represents a fundamental phase to estimate feasibility of industrial collaborative solutions. The presented work proposes a computer-aided approach to identify, assess and optimize the safety systems that enables the collaborative usage of industrial robots. It exploits the capabilities of virtual controller-based offline programming packages to design in advance the safety countermeasures. An initial consistency test validates the response of the selected tool with respect to the safety functionalities. Subsequently, a virtual replica of a potential industrial collaborative solution has been developed. As a result, it has been possible to mimic the behaviour of such a system with respect to Speed and Separation Monitoring collaborative method.


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    Titel :

    Computer-Aided Assessment of Safety Countermeasures for Industrial Human-Robot Collaborative Applications


    Weitere Titelangaben:

    Springer Proceedings in Advanced Robotics


    Beteiligte:
    Ferraguti, Federica (Herausgeber:in) / Villani, Valeria (Herausgeber:in) / Sabattini, Lorenzo (Herausgeber:in) / Bonfè, Marcello (Herausgeber:in) / Pini, Fabio (Autor:in) / Leali, Francesco (Autor:in)

    Kongress:

    International Workshop on Human-Friendly Robotics ; 2019 ; Reggio Emilia, Italy October 24, 2019 - October 25, 2019



    Erscheinungsdatum :

    2020-02-21


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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