Robo-Saber: Generating and Simulating Virtual Reality Players

Nam Hee Kim, Jingjing May Liu, Jaakko Lehtinen, Perttu Hämäläinen, James F. O'Brien +1 more
2/20/2026
cs.GRcs.AIcs.HC

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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 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.

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Cite this paper

@article{kim2026robosaber,
  title  = {Robo-Saber: Generating and Simulating Virtual Reality Players},
  author = {Nam Hee Kim and Jingjing May Liu and Jaakko Lehtinen and Perttu Hämäläinen and James F. O'Brien and Xue Bin Peng},
  year   = {2026},
  eprint = {2602.18319},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2602.18319v1}
}

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