HARU: Haptic Augmented Reality-Assisted User-Centric Industrial Network Planning
This addresses the need for interactive and autonomous network planning in industrial settings, though it appears incremental as it combines existing technologies like vision fusion, ray tracing, and AR.
The paper tackles the problem of planning industrial networks for Industry 4.0 by proposing HARU, an end-to-end solution that uses haptic augmented reality to assist users, resulting in good network coverage, high accuracy in environment reconstruction and camera relocalization, and real-time monitoring with an end-to-end latency of about 32 ms per frame.
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.