Niantic Spatial 🌎

Introducing object interaction for real-to-sim training.

Identify, extract, move, or remove objects in captured environments to test navigation, obstacle avoidance, and baseline interactions.

Try scene variation in beta with up to 10 scenes: hubs.ly/Q04DVVKG0

#EmbodiedAI #Robotics #PhysicalAI #AI #RealtoSim

We’re building a 4D model of the world so machines can reason, learn, and act.

The foundation: photorealistic 3D reconstruction with accurate, metric-scale geometry for field operations, remote planning, robot policy training, and more. 

These possibilities are endless when real-world places become the foundation of where you build.
hubs.ly/Q04DPh1-0

#3DReconstruction #GaussianSplatting #SpatialAI #EmbodiedAI #Robotics #RealtoSim

Give robots a faithful reconstruction of their world.

Niantic Spatial’s depth-regularized reconstruction unifies photorealism and reliable geometry for meshes, collision surfaces, and robot training.

Learn more about the state-of-the-art geometry for autonomy: hubs.ly/Q04Dkxyh0

#Robotics #PhysicalAI #EmbodiedAI #AI #GaussianSplat #3DReconstruction #NeuralRendering

Are your robots ready for the real world?

Start with Niantic Spatial’s Embodied AI Places Library: 100 off-the-shelf warehouse, residential, and outdoor environments for real-to-sim training.

hubs.ly/Q04D1S6J0

#Robotics #EmbodiedAI #RealToSim #3DReconstruction #GaussianSplatting #3DGS #IsaacSim #AI

More accurate depth and geometry for robot training.

Niantic Spatial uses depth evidence to guide Gaussian splat optimization. By comparing rendered splat depth against per-view depth estimates, we encourage Gaussians to occupy the right locations and surfaces to remain consistent across viewpoints.

In our comparisons, this reduces noise in extracted surfaces, particularly across large planes and low-texture regions, combining photorealistic rendering with reliable geometry in one representation.

Learn more: hubs.ly/Q04CPnKt0

#EmbodiedAI #PhysicalAI #AI #Robotics #GaussianSplat #3DReconstruction #RealtoSim