An augmented reality-based training system with a natural user interface for manual milling operations

Abstract

This study developed an augmented reality (AR)-based training system for conventional manual milling operations. An Intel RealSense R200 depth camera and a Leap Motion controller were mounted on an HTC Vive head-mounted display to allow users freely walk around in a room-size AR environment to operate a full-size virtual milling machine with their barehands, using their natural operation behaviors, as if they were operating a real milling machine in the real world, without additional worn or handheld devices. GPU parallel computing was used to handle dynamic occlusions and accelerate the machining simulation to achieve a real-time simulation. Using the developed AR-based training system, novices can receive a hands-on training in a safe environment, without any injury or damage. User test results showed that using the developed AR-based training resulted in lower failure rates and inquiry times than using video training. Users also commented that the AR-based training was interesting and helpful for novices to learn the basic manual milling operation techniques.

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Acknowledgements

The authors would like to thank the Ministry of Science and Technology, Taiwan, Republic of China for financially supporting this research under Contract MOST 108-2221-E-002-161-MY2.

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Correspondence to Shana Smith.

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Yang, CK., Chen, YH., Chuang, TJ. et al. An augmented reality-based training system with a natural user interface for manual milling operations. Virtual Reality 24, 527–539 (2020). https://doi.org/10.1007/s10055-019-00415-8

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Keywords

  • Augmented reality
  • Natural operation behavior
  • Manual milling operation
  • Occlusion