Infinigen-Sim: Procedural Generation of Articulated Simulation Assets

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.

Publication Details

Journal
arXiv (Cornell University)
Published
2025-05-15
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
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article

Infinigen-Sim: Procedural Generation of Articulated Simulation Assets

arXiv (Cornell University)
Robot Manipulation and Learning
article

Infinigen-Sim: Procedural Generation of Articulated Simulation Assets

article en

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.

arXiv (Cornell University)
Openalex Percentile: Top 46%
Robot Manipulation and Learning
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Infinigen-Sim: Procedural Generation of Articulated Simulation Assets · arXiv (Cornell University) (2025) | TGRS Research Map | TGRS