Robo-Saber: Generating and Simulating Virtual Reality Players

TL;DR

Robo-Saber is a novel system that generates realistic VR player movements from game scenarios, aiding in game testing and analysis by producing diverse, skilled gameplay behaviors based on style exemplars.

Contribution

It introduces the first motion generation system for VR playtesting, trained on a large dataset, capable of producing diverse and skilled player movements aligned with style exemplars.

Findings

Produces skilled gameplay in Beat Saber

Captures diverse player behaviors

Mirrors input style exemplars

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.