Description
Human-Robot collaboration can be a challenging exercise especially when both the human and the robot want to work simultaneously on a given task. It becomes difficult for the human to understand the intentions of the robot and vice-versa. To overcome

Human-Robot collaboration can be a challenging exercise especially when both the human and the robot want to work simultaneously on a given task. It becomes difficult for the human to understand the intentions of the robot and vice-versa. To overcome this problem, a novel approach using the concept of Mixed-Reality has been proposed, which uses the surrounding space as the canvas to augment projected information on and around 3D objects. A vision based tracking algorithm precisely detects the pose and state of the 3D objects, and human-skeleton tracking is performed to create a system that is both human-aware as well as context-aware. Additionally, the system can warn humans about the intentions of the robot, thereby creating a safer environment to work in. An easy-to-use and universal visual language has been created which could form the basis for interaction in various human-robot collaborations in manufacturing industries.

An objective and subjective user study was conducted to test the hypothesis, that using this system to execute a human-robot collaborative task would result in higher performance as compared to using other traditional methods like printed instructions and through mobile devices. Multiple measuring tools were devised to analyze the data which finally led to the conclusion that the proposed mixed-reality projection system does improve the human-robot team's efficiency and effectiveness and hence, will be a better alternative in the future.
Reuse Permissions
  • Downloads
    PDF (3.2 MB)
    Download count: 2

    Details

    Title
    • Facilitating human-robot collaboration using a mixed-reality projection system
    Contributors
    Date Created
    2017
    Resource Type
  • Text
  • Collections this item is in
    Note
    • thesis
      Partial requirement for: M.S., Arizona State University, 2017
    • bibliography
      Includes bibliographical references (pages 40-41)
    • Field of study: Computer science

    Citation and reuse

    Statement of Responsibility

    by Yash K. Rathore

    Machine-readable links