Technology Category
Humans and AI: Game Design — Procedural Content Generation & StorytellingMachine Learning: Imitation Learning & Inverse Reinforcement LearningNatural Language Processing: Generation
Infinigen-Sim: Procedural Generation of Articulated Simulation Assets
🤖 AI Summary
To address low modeling efficiency, limited diversity, and poor cross-platform compatibility in articulated object simulation for robotics, this paper proposes the first end-to-end procedural asset generation framework tailored for articulated object segmentation, generalizable reinforcement learning, and sim-to-real transfer. The method leverages Blender to implement parametric articulated structure modeling—supporting joint constraints and physical plausibility—integrates differentiable rendering for automated semantic annotation, and establishes a unified export pipeline compatible with PyBullet, Isaac Gym, and MuJoCo. We develop dedicated generators for five common articulated object categories (e.g., cabinet doors, drawers, folding chairs). Experiments demonstrate that the generated assets significantly improve semantic segmentation accuracy (+12.3% mIoU), policy generalization across tasks (+18.7% success rate), and sim-to-real transfer performance (+24.1% success rate).
Technology Category
Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Procedural generation of diverse articulated objects
Integration of assets into robotics simulators
Enhancing sim-to-real transfer for learning policies
Innovation
Methods, ideas, or system contributions that make the work stand out.
Procedural generation of articulated objects
Blender utilities for asset creation
Export pipeline for robotics simulators
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