%Aigaion2 BibTeX export from Idiap Publications
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@ARTICLE{Giusti_RAM_2018,
         author = {Giusti, A. and Zeestraten, M. and Icer, E. and Pereira, A. and Caldwell, D. G. and Calinon, Sylvain and Althoff, M.},
       keywords = {learning from demonstration},
       projects = {Idiap},
          month = jun,
          title = {Flexible Automation Driven by Demonstration: Leveraging Strategies that Simplify Robotics},
        journal = {IEEE Robotics and Automation Magazine (RAM)},
         volume = {25},
         number = {2},
           year = {2018},
          pages = {18-27},
            url = {https://ieeexplore.ieee.org/document/8356588/},
            doi = {10.1109/MRA.2018.2810543},
       abstract = {How do I automate this task? This is a crucial question for production engineers. In classical industrial automation (think of a car factory) robots perform a small set of tasks for long periods of time. They were selected because their kinematic structure and strength suited the task requirements, and their motions were pre-programmed by a skilled programmer. In flexible manufacturing environments, tasks may change daily or hourly. The classical approach to automation is less suitable here: buying a dedicated robot for each set of tasks is uneconomical and coding each task is too time consuming. Further, qualified programmers with the requisite knowledge might not be available. To solve these problems, we propose a framework for modular robots that determines their structure and program based on human demonstrations.},
            pdf = {https://publications.idiap.ch/attachments/papers/2018/Giusti_RAM_2018.pdf}
}