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Related Concept Videos

Virtual Work for a System of Connected Rigid Bodies01:06

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Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
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Motion-Aware Interplay between WiGig and WiFi for Wireless Virtual Reality.

Sanghyun Kim1, Ji-Hoon Yun1

  • 1Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea.

Sensors (Basel, Switzerland)
|December 2, 2020
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This study introduces a novel wireless virtual reality (VR) system that dynamically switches between WiGig and WiFi connections. By predicting user motion, it optimizes performance for enhanced VR experiences.

Keywords:
VRWiFiWiGigmulti-radiowireless virtual reality

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Human-Computer Interaction

Background:

  • Wireless virtual reality (VR) systems offload computation to remote servers, requiring high-bandwidth, reliable wireless connections.
  • WiGig and WiFi offer distinct bandwidth and reliability trade-offs for wireless VR implementation.
  • Existing wireless VR solutions often rely on a single communication protocol, limiting adaptability.

Purpose of the Study:

  • To develop an adaptive wireless VR system that leverages the strengths of both WiGig and WiFi.
  • To improve VR latency regulation and image quality by intelligently managing wireless link selection and frame encoding.
  • To enable a more robust and high-fidelity wireless VR experience through motion-aware performance prediction.

Main Methods:

  • Developed a testbed to analyze the correlation between user motion and wireless link performance (WiGig and WiFi).
  • Implemented a system that predicts wireless link capacity based on user motion patterns.
  • Designed an opportunistic link-switching mechanism to select the best available wireless connection.
  • Integrated motion-aware prediction to dynamically adjust VR frame encoding rates for latency and quality optimization.

Main Results:

  • Demonstrated a strong correlation between user motion and the performance of WiGig and VR traffic.
  • The proposed system successfully switches between WiGig and WiFi links based on predicted performance.
  • Motion-aware prediction enables dynamic adjustment of VR encoding rates, improving latency and image quality.
  • Evaluated testbed data shows the proposed system outperforms a fixed-rate WiGig-only system.

Conclusions:

  • User motion is a predictable indicator of wireless link performance for VR.
  • An adaptive wireless VR system combining WiGig and WiFi, guided by motion prediction, significantly enhances user experience.
  • The developed system offers a promising approach for future high-quality, low-latency wireless VR applications.