We introduce Infinigen-Sim, a toolkit which enables users to create diverse and realistic articulated object procedural generators. These tools are composed of high-level utilities for use creating articulated assets in Blender, as well as an export pipeline to integrate the resulting assets into common robotics simulators. We demonstrate our system by creating procedural generators for 5 common articulated object categories. Experiments show that assets sampled from these generators are useful for movable object segmentation, training generalizable reinforcement learning policies, and sim-to-real transfer of imitation learning policies.
View on arXiv@article{joshi2025_2505.10755,
title={ Infinigen-Sim: Procedural Generation of Articulated Simulation Assets },
author={ Abhishek Joshi and Beining Han and Jack Nugent and Yiming Zuo and Jonathan Liu and Hongyu Wen and Stamatis Alexandropoulos and Tao Sun and Alexander Raistrick and Gaowen Liu and Yi Shao and Jia Deng },
journal={arXiv preprint arXiv:2505.10755},
year={ 2025 }
}