Planetary
simulation environments for spatial AI
A procedural world generator with semantic object system, environment randomization, and an RL training interface.
Preview to World in one click
Use cases
- Train physical AI, such as humanoid robots and drones
- Test out agentic avatars in a game-like environment
Features
- Create procedurally generated infinite worlds from noise functions
- Instantly add procedural assets with semantic labelling and affordances
- Train RL agents in headless simulations sampled from a world distribution, for thousands of variations of the same 3D space
Upcoming
- Full in-house procedural asset library, all equipped with affordances
- Headless RL mode for parallel training
- Accurate weather and environmental conditions
- Buildings and cities