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        Chapter RoCKIn@Work: Industrial Robot Challenge

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        Author(s)
        Hochgeschwender, Nico
        Bischoff, Rainer
        Kraetzschmar, Gerhard K.
        Friedrich, Tim
        Language
        English
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        Abstract
        RoCKIn@Work was focused on benchmarks in the domain of industrial robots. Both task and functionality benchmarks were derived from real world applications. All of them were part of a bigger user story painting the picture of a scaled down real world factory scenario. Elements used to build the testbed were chosen from common materials in modern manufacturing environments. Networked devices, machines controllable through a central software component, were also part of the testbed and introduced a dynamic component to the task benchmarks. Strict guidelines on data logging were imposed on participating teams to ensure gathered data could be automatically evaluated. This also had the positive effect that teams were made aware of the importance of data logging, not only during a competition but also during research as useful utility in their own laboratory. Tasks and functionality benchmarks are explained in detail, starting with their use case in industry, further detailing their execution and providing information on scoring and ranking mechanisms for the specific benchmark.
        URI
        https://library.oapen.org/handle/20.500.12657/49219
        Keywords
        robotics, robot competitions, benchmarking, domestic robots, industrial robots
        DOI
        10.5772/intechopen.70014
        Publisher
        InTechOpen
        Publisher website
        https://www.intechopen.com/
        Publication date and place
        2017
        Classification
        Automatic control engineering
        Rights
        https://creativecommons.org/licenses/by/3.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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