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@INCOLLECTION{Blanc_SPRINGER_2025,
         author = {Blanc, C. and Jankowski, Julius and Sonderegger, A. and Calinon, Sylvain and D{\'{e}}gallier Rochat, S.},
         editor = {Barresi, G. and Wischniewski, S.},
       keywords = {learning from demonstration, robot learning, robot programming},
       projects = {Idiap},
          title = {Intuitive Robot Programming},
      booktitle = {Ergonomics in Robotics: Advances and Innovations},
           year = {2025},
      publisher = {Springer},
       abstract = {The introduction of robots in SMEs requires a drastic reconsideration of existing programming techniques and interfaces. The growing versatility of the market essentially demands the robots to be re-programmed frequently, calling for interfaces that are intuitive enough to require no robotic expertise, yet flexible enough to meet industrial needs. Rather than limiting the intervention of the workers, the technology should empower them to take control over the machine. Only then, the human-machine complementarity can be leveraged, combining the efficiency of automation with the flexibility of human work. Ergonomics and human factors are critical to the development of these new programming interfaces, which should typically be developed and tested in a cyclic fashion with the end-users. In this chapter, we highlight the differences between easy-to-learn and easy-to-use interfaces, as well as the differences between interfaces targeting naive/casual users and interfaces targeting expert/professional workers. We discuss the design of robot programming interfaces based on a user-centric perspective. The research developments in this project target different methods to collect demonstrations (including tracked devices and kinesthetic teaching), different graphical user interfaces (including block-based and timeline representations), and different approaches to augmented reality (including tablets/smartphones, headsets or actuated projection devices). Through this multi-modular approach, we aim at providing workers with the most natural way possible to interact with the robot depending on the task or their preferences.}
}