# MarketGen: A Scalable Simulation Platform with Auto-Generated Embodied Supermarket Environments

Source: [MarketGen: A Scalable Simulation Platform with Auto-Generated Embodied Supermarket Environments](<https://www.sota2.com/research/paper/6927db02d6b0dd3342930ce5>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-03-07T05:00:04.447Z

Authors: Xu Hu, Yiyang Feng, Junran Peng, Jiawei He, Liyi Chen, Wei Sui, Chuanchen Luo, Xucheng Yin, Qing Li, Zhaoxiang Zhang

Published: 2025-11-26T08:20:20.000Z

## Abstract

The development of embodied agents for complex commercial environments is hindered by a critical gap in existing robotics datasets and benchmarks, which primarily focus on household or tabletop settings with short-horizon tasks. To address this limitation, we introduce MarketGen, a scalable simulation platform with automatic scene generation for complex supermarket environments. MarketGen features a novel agent-based Procedural Content Generation (PCG) framework. It uniquely supports multi-modal inputs (text and reference images) and integrates real-world design principles to automatically generate complete, structured, and realistic supermarkets. We also provide an extensive and diverse 3D asset library with a total of 1100+ supermarket goods and parameterized facilities assets. Building on this generative foundation, we propose a novel benchmark for assessing supermarket agents, featuring two daily tasks in a supermarket: (1) Checkout Unloading: long-horizon tabletop tasks for cashier agents, and (2) In-Aisle Item Collection: complex mobile manipulation tasks for salesperson agents. We validate our platform and benchmark through extensive experiments, including the deployment of a modular agent system and successful sim-to-real transfer. MarketGen provides a comprehensive framework to accelerate research in embodied AI for complex commercial applications.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Checkout Unloading on GRUtopia](<https://www.sota2.com/research/sota/checkout-unloading-on-grutopia.md>): Checkout Unloading; GRUtopia; Success Rate: not recorded.

- [In-Aisle Item Collection on GRUtopia](<https://www.sota2.com/research/sota/in-aisle-item-collection-on-grutopia.md>): In-Aisle Item Collection; GRUtopia; SR: not recorded.

- [Modular Manipulation (Overall) on GRUtopia](<https://www.sota2.com/research/sota/modular-manipulation-overall-on-grutopia.md>): Modular Manipulation (Overall); GRUtopia; Success Rate (SR): not recorded.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2511.21161>)

[PDF](<https://arxiv.org/pdf/2511.21161.pdf>)