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HARU: Haptic Augmented Reality-Assisted User-Centric Industrial Network Planning

arXiv 2206.12139 ↗First posted 24 Jun 2022cs.NI cs.CVcited by 0

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Abstract (arXiv)

To support Industry 4.0 applications with haptics and human-machine interaction, 6G requires a new framework that is fully autonomous, visual, and interactive. In this paper, we provide an end-to-end solution, HARU, for private network planning services, especially industrial networks. The solution consists of the following functions: collecting visual and sensory data from the user device, reconstructing 3D radio propagation environment and conducting network planning on a server, and visualizing network performance with AR on the user device with enabled haptic feedback. The functions are empowered by three key technical components: 1) vision- and sensor fusion-based 3D environment reconstruction, 2) ray tracing-based radio map generation and network planning, and 3) AR-assisted network visualization enabled by real-time camera relocalization. We conducted the proof-of-concept in a Bosch plant in Germany and showed good network coverage of the optimized antenna location, as well as high accuracy in both environment reconstruction and camera relocalization. We also achieved real-time AR-supported network monitoring with an end-to-end latency of about 32 ms per frame.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 18 references that are in the map. First posted on arXiv 24 Jun 2022.

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References · 2

  1. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,795
  2. 2020ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAMcited by 878

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