Infinigen-Sim: Procedural Generation of Articulated Simulation Assets
Published in Arxiv: 2505.10755, 2025
Abhishek Joshi, Beining Han, Jack Nugent, Yiming Zuo, Jonathan Liu, Hongyu Wen, Stamatis Alexandropoulos, Tao Sun, Alexander Raistrick, Gaowen Liu, Yi Shao, Jia Deng
Abstract
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.