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Research PaperResearchia:202602.24073

Robo-Saber: Generating and Simulating Virtual Reality Players

Nam Hee Kim

Abstract

We present the first motion generation system for playtesting virtual reality (VR) games. Our player model generates VR headset and handheld controller movements from in-game object arrangements, guided by style exemplars and aligned to maximize simulated gameplay score. We train on the large BOXRR-23 dataset and apply our framework on the popular VR game Beat Saber. The resulting model Robo-Saber produces skilled gameplay and captures diverse player behaviors, mirroring the skill levels and mov...

Submitted: February 24, 2026Subjects: AI; Artificial Intelligence

Description / Details

We present the first motion generation system for playtesting virtual reality (VR) games. Our player model generates VR headset and handheld controller movements from in-game object arrangements, guided by style exemplars and aligned to maximize simulated gameplay score. We train on the large BOXRR-23 dataset and apply our framework on the popular VR game Beat Saber. The resulting model Robo-Saber produces skilled gameplay and captures diverse player behaviors, mirroring the skill levels and movement patterns specified by input style exemplars. Robo-Saber demonstrates promise in synthesizing rich gameplay data for predictive applications and enabling a physics-based whole-body VR playtesting agent.


Source: arXiv:2602.18319v1 - http://arxiv.org/abs/2602.18319v1 PDF: https://arxiv.org/pdf/2602.18319v1 Original Link: http://arxiv.org/abs/2602.18319v1

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Submission Info
Date:
Feb 24, 2026
Topic:
Artificial Intelligence
Area:
AI
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