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APF-S2T: Steering to Target Redirection Walking Based on Artificial Potential Fields.

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    A new redirected walking (RDW) controller, APF Steer-to-Target (APF-S2T), reduces resets in virtual environments. This artificial potential field (APF) method outperforms existing RDW controllers by minimizing user interruptions.

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    Area of Science:

    • Virtual Reality
    • Human-Computer Interaction
    • Robotics

    Background:

    • Redirected walking (RDW) allows natural movement in virtual environments larger than physical spaces.
    • Existing artificial potential field (APF) and alignment-based controllers like APF-S2G and APF-RDW face challenges, particularly frequent resets in confined areas like corridors.
    • These limitations stem from controllers localizing to user position, causing vectors to point towards walls.

    Purpose of the Study:

    • Introduce APF Steer-to-Target (APF-S2T), a novel RDW controller designed to mitigate resets.
    • Evaluate APF-S2T's performance against state-of-the-art RDW controllers through simulation.
    • Enhance user immersion and reduce interruptions in large-scale virtual environments.

    Main Methods:

    • Developed APF-S2T, which identifies a target sample point with the lowest score within the user's walkable area.
    • The score is a combination of the APF value and distance from the user.
    • The direction to this target point dictates the RDW gains, optimizing steering.
    • Conducted simulation-based evaluations comparing APF-S2T with APF-S2G, APF-RDW, Visibility Polygon-based alignment, and Alignment-Optimized controllers.

    Main Results:

    • APF-S2T significantly reduced the number of resets compared to all other evaluated controllers.
    • The average distance between resets was also substantially increased using APF-S2T.
    • Simulation results demonstrated superior performance of APF-S2T in minimizing user interruptions.

    Conclusions:

    • APF-S2T represents a significant advancement in redirected walking controller technology.
    • The proposed method effectively overcomes limitations of previous APF and alignment-based controllers, especially in constrained virtual spaces.
    • APF-S2T offers a more seamless and immersive virtual reality experience by minimizing disruptive resets.