EmbodiedGen: Towards a Generative 3D World Engine for Embodied
  Intelligence
Constructing a physically realistic and accurately scaled simulated 3D world
is crucial for the training and evaluation of embodied intelligence tasks. The
diversity, realism, low cost accessibility and affordability of 3D data assets
are critical for achieving generalization and scalability in embodied AI.
However, most current embodied intelligence tasks still rely heavily on
traditional 3D computer graphics assets manually created and annotated, which
suffer from high production costs and limited realism. These limitations
significantly hinder the scalability of data driven approaches. We present
EmbodiedGen, a foundational platform for interactive 3D world generation. It
enables the scalable generation of high-quality, controllable and
photorealistic 3D assets with accurate physical properties and real-world scale
in the Unified Robotics Description Format (URDF) at low cost. These assets can
be directly imported into various physics simulation engines for fine-grained
physical control, supporting downstream tasks in training and evaluation.
EmbodiedGen is an easy-to-use, full-featured toolkit composed of six key
modules: Image-to-3D, Text-to-3D, Texture Generation, Articulated Object
Generation, Scene Generation and Layout Generation. EmbodiedGen generates
diverse and interactive 3D worlds composed of generative 3D assets, leveraging
generative AI to address the challenges of generalization and evaluation to the
needs of embodied intelligence related research. Code is available at
https://horizonrobotics.github.io/robot_lab/embodied_gen/index.html.
684b9aa43b733ba33368704c
Wang Xinjie
claimed_verified
2025-06-13T14:59:28.296Z
659b9ee689010f9c7ad674ed
https://cdn-avatars.huggingface.co/v1/production/uploads/659b9ee689010f9c7ad674ed/4vFsBx0FEzri5W9WUzI6p.png
xinjjj
user
xinjjj
684b9aa43b733ba33368704d
Liu Liu
684b9aa43b733ba33368704e
Cao Yu
684b9aa43b733ba33368704f
Wu Ruiqi
684b9aa43b733ba333687050
Qin Wenkang
684b9aa43b733ba333687051
Wang Dehui
684b9aa43b733ba333687052
Sui Wei
684b9aa43b733ba333687053
Su Zhizhong
EmbodiedGen: Towards a Generative 3D World Engine for Embodied
  Intelligence
Constructing a physically realistic and accurately scaled simulated 3D world
is crucial for the training and evaluation of embodied intelligence tasks. The
diversity, realism, low cost accessibility and affordability of 3D data assets
are critical for achieving generalization and scalability in embodied AI.
However, most current embodied intelligence tasks still rely heavily on
traditional 3D computer graphics assets manually created and annotated, which
suffer from high production costs and limited realism. These limitations
significantly hinder the scalability of data driven approaches. We present
EmbodiedGen, a foundational platform for interactive 3D world generation. It
enables the scalable generation of high-quality, controllable and
photorealistic 3D assets with accurate physical properties and real-world scale
in the Unified Robotics Description Format (URDF) at low cost. These assets can
be directly imported into various physics simulation engines for fine-grained
physical control, supporting downstream tasks in training and evaluation.
EmbodiedGen is an easy-to-use, full-featured toolkit composed of six key
modules: Image-to-3D, Text-to-3D, Texture Generation, Articulated Object
Generation, Scene Generation and Layout Generation. EmbodiedGen generates
diverse and interactive 3D worlds composed of generative 3D assets, leveraging
generative AI to address the challenges of generalization and evaluation to the
needs of embodied intelligence related research. Code is available at
https://horizonrobotics.github.io/robot_lab/embodied_gen/index.html.
EmbodiedGen is a platform that generates high-quality, photorealistic 3D assets at low cost, enabling scalable and realistic embodied AI research through generative AI techniques.
3D assets photo-realistic high-quality generative AI Image-to-3D Text-to-3D Texture Generation Articulated Object Generation Scene Generation Layout Generation physics simulation engines Unified Robotics Description Format (URDF) embodied intelligence