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Distributed haptic interactions with physically based 3D deformable models over lossy networks.

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    Area of Science:

    • Virtual Reality
    • Haptics
    • Computer Graphics
    • Networked Systems

    Background:

    • Simulating 3D deformable models in collaborative virtual environments faces challenges like high costs, communication load, and network instability.
    • Network issues (packet loss, delay, jitter) degrade visual and haptic experiences in HCVEs.

    Purpose of the Study:

    • To enable real-time sharing of physically based 3D deformable models and force simulations in distributed virtual environments over general networks.
    • To overcome network limitations for stable and consistent haptic interactions.

    Main Methods:

    • Combined linear modal analysis and corotational methods for simulating large deformations.
    • Developed a data compression technique using spectral domain accelerations (several KB) for efficient streaming.
    • Implemented loss compensation, prediction algorithms, and force prediction for network error correction and haptic stability.

    Main Results:

    • Achieved low communication load and effective streaming of 3D deformation data.
    • Demonstrated robustness and validity under various network conditions.
    • Ensured haptic stability and visual/haptic consistency.

    Conclusions:

    • The proposed approach effectively supports haptic interactions with 3D deformable models in distributed virtual environments.
    • The system is effective, robust, and valid across different network conditions and distribution topologies (client-server, peer-to-peer).