Imagination-to-real by SmilingRobo
Train your robot using GenAI
Listed in categories:
Open SourceArtificial IntelligenceDeveloper Tools
Description
imaginationtoreal empowers robotics developers by bridging the gap between generative AI and classical physics simulators. Our library prepares realistic, diverse, and geometrically accurate visual data from generative models. This data enables robots to learn complex and highly dynamic tasks such as parkour without requiring depth sensors.
How to use Imagination-to-real by SmilingRobo?
Use ImageMaker for text-to-image generation tailored to your simulation needs. Combine the generated data with your preferred training framework to develop robust robot learning models.
Core features of Imagination-to-real by SmilingRobo:
1️⃣
Integrates generative models with simulators to create rich synthetic datasets
2️⃣
Ensures temporal consistency with tools like Dreams In Motion (DIM)
3️⃣
Offers compatibility with MuJoCo environments for seamless data preparation
4️⃣
Provides a graphical interface for designing custom workflows
5️⃣
Supports distributed setups for scaling image generation.
Why could be used Imagination-to-real by SmilingRobo?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Training robots to perform complex tasks like parkour | ✅ | |
| # 2 | Generating synthetic datasets for robotics simulations | ✅ | |
| # 3 | Augmenting physics simulations with photorealistic images. | ✅ | |
Who developed Imagination-to-real by SmilingRobo?
SmilingRobo is dedicated to advancing robotics through innovative solutions that integrate generative AI with classical physics simulations, enabling developers to create more capable and intelligent robotic systems.