We introduce Infinigen-Articulated, a toolkit for generating realistic, procedurally generated articulated assets for robotics simulation. We include procedural generators for 18 common articulated object categories along with high-level utilities for use creating custom articulated assets in Blender. We also provide an export pipeline to integrate the resulting assets along with their physical properties into common robotics simulators. Experiments demonstrate that assets sampled from these generators are effective for movable object segmentation, training generalizable reinforcement learning policies, and sim-to-real transfer of imitation learning policies.
@article{arxiv.2505.10755,
title = {Procedural Generation of Articulated Simulation-Ready Assets},
author = {Abhishek Joshi and Beining Han and Jack Nugent and Max Gonzalez Saez-Diez and Yiming Zuo and Jonathan Liu and Hongyu Wen and Stamatis Alexandropoulos and Karhan Kayan and Anna Calveri and Tao Sun and Gaowen Liu and Yi Shao and Alexander Raistrick and Jia Deng},
journal= {arXiv preprint arXiv:2505.10755},
year = {2025}
}
Comments
Updated to include information on newly implemented assets, new experimental results (both simulation and real world), and additional features including material and dynamics parameters