Leveraging VR Robot Games to Facilitate Data Collection for Embodied Intelligence Tasks

2026-04-18

AI Summary

This work addresses the high cost and limited accessibility of traditional interfaces that hinder large-scale embodied interaction data collection. The authors propose a Unity-based, gamified data collection framework that integrates procedural scene generation, VR-driven humanoid robot control, automated task evaluation, and trajectory logging, validated through a trash pickup-and-placement task. By enabling dynamic adjustment of task difficulty, the approach significantly increases physical engagement and expands the exploration range of the robotic arm’s workspace. This facilitates the efficient generation of diverse demonstration data spanning a broad state-action space, establishing a scalable new paradigm for data collection in embodied intelligence research.

Technology Category

• Intelligent Robots: Embodied AI
• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Machine Learning: Imitation Learning & Inverse Reinforcement Learning

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

Collecting embodied interaction data at scale remains costly and difficult due to the limited accessibility of conventional interfaces. We present a gamified data collection framework based on Unity that combines procedural scene generation, VR-based humanoid robot control, automatic task evaluation, and trajectory logging. A trash pick-and-place task prototype is developed to validate the full workflow.Experimental results indicate that the collected demonstrations exhibit broad coverage of the state-action space, and that increasing task difficulty leads to higher motion intensity as well as more extensive exploration of the arm's workspace. The proposed framework demonstrates that game-oriented virtual environments can serve as an effective and extensible solution for embodied data collection.

Problem

• embodied intelligence
• data collection
• VR robot games
• humanoid robot control
• state-action space

Innovation

• VR-based robot control
• procedural scene generation
• gamified data collection
• embodied intelligence
• trajectory logging