![[2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players
Summary
The paper presents Robo-Saber, a motion generation system designed for playtesting virtual reality games, specifically focusing on generating player movements based on in-game scenarios and style exemplars.
Why It Matters
Robo-Saber addresses a significant gap in VR game development by providing a method to simulate player behavior, which can enhance game testing and development processes. This innovation can lead to better gameplay experiences and more efficient testing protocols, ultimately benefiting both developers and players.
Key Takeaways
- Robo-Saber generates VR player movements from game scenarios.
- It utilizes a large dataset (BOXRR-23) for training its models.
- The system captures diverse player behaviors and skill levels.
- It enhances predictive applications in game development.
- Robo-Saber can serve as a physics-based playtesting agent.
Computer Science > Graphics arXiv:2602.18319 (cs) [Submitted on 20 Feb 2026] Title:Robo-Saber: Generating and Simulating Virtual Reality Players Authors:Nam Hee Kim, Jingjing May Liu, Jaakko Lehtinen, Perttu Hämäläinen, James F. O'Brien, Xue Bin Peng View a PDF of the paper titled Robo-Saber: Generating and Simulating Virtual Reality Players, by Nam Hee Kim and 5 other authors View PDF HTML (experimental) 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. Comments: Subjects: Graphics (cs.GR); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Machine Learning (cs.LG) Cite as: arXiv:2602.18319 [cs.GR] (or arXiv:2602.18319v1 [cs.GR] for this version) https://doi.org/10.48550/arXiv.2602.18319 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Nam Hee Kim ...
