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This study introduces RoSA, a Robot System Assistant, enabling safe human-machine interaction via speech and gestures. The contactless system demonstrates comparable usability to human-controlled robots, enhancing user experience.

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Artificial Intelligence

Background:

  • Intuitive human-machine interaction is crucial for robot system assistants.
  • Previous research highlighted user preference for speech and gestures in human-robot interaction.
  • Developing contactless interaction methods is essential for safety and efficiency.

Purpose of the Study:

  • To implement and evaluate RoSA (Robot System Assistant) for safe and intuitive human-machine interaction.
  • To design a multi-modal contactless system integrating speech, facial, and gesture recognition.
  • To assess the user experience and interaction efficiency of the developed system.

Main Methods:

  • A Wizard of Oz study was conducted to determine preferred interaction modalities.
  • A multi-modal system was designed and implemented using speech, facial, and gesture recognition.
  • The system was evaluated through an extensive user study with multiple subjects.

Main Results:

  • The RoSA system achieved usability scores comparable to human-controlled robot interaction.
  • The multi-modal approach proved effective for contactless human-machine interaction.
  • The Robot Operating System (ROS) framework facilitated modularity and extendability.

Conclusions:

  • The implemented RoSA system offers a safe and intuitive solution for human-machine interaction.
  • The multi-modal, contactless approach enhances user experience and interaction efficiency.
  • The ROS-based framework supports adaptable and scalable robot system applications.