标题： Sari沙盒：用于具身人工智能代理的虚拟零售商店环境 显示英文标题

标题： Sari Sandbox: A Virtual Retail Store Environment for Embodied AI Agents

摘要： 我们介绍了Sari Sandbox，这是一个高保真、逼真的3D零售店模拟环境，用于在购物任务中与人类表现进行基准测试。 解决在具身代理训练中的零售特定模拟环境的不足，Sari Sandbox包含三个商店配置中的250多个可交互的杂货商品，可通过API进行控制。 它支持虚拟现实（VR）用于人机交互和基于视觉语言模型（VLM）的具身代理。 我们还介绍了SariBench，一个跨不同任务难度的标注人类演示数据集。 我们的沙盒使具身代理能够导航、检查和操作零售商品，提供与人类表现的基准。 最后，我们给出了基准测试、性能分析和提升真实感和可扩展性的建议。 源代码可通过https://github.com/upeee/sari-sandbox-env获取。 显示英文摘要

摘要： We present Sari Sandbox, a high-fidelity, photorealistic 3D retail store simulation for benchmarking embodied agents against human performance in shopping tasks. Addressing a gap in retail-specific sim environments for embodied agent training, Sari Sandbox features over 250 interactive grocery items across three store configurations, controlled via an API. It supports both virtual reality (VR) for human interaction and a vision language model (VLM)-powered embodied agent. We also introduce SariBench, a dataset of annotated human demonstrations across varied task difficulties. Our sandbox enables embodied agents to navigate, inspect, and manipulate retail items, providing baselines against human performance. We conclude with benchmarks, performance analysis, and recommendations for enhancing realism and scalability. The source code can be accessed via https://github.com/upeee/sari-sandbox-env.