Perception

Gaussian Splatting

Gaussian splatting is a 3D scene representation and rendering technique, introduced as 3D Gaussian Splatting by Kerbl et al. (2023), that models a scene as millions of anisotropic 3D Gaussians with color and opacity, rendered by differentiable rasterization. It matches or exceeds NeRF visual quality while rendering orders of magnitude faster, and is fitted from posed images in minutes. Robotics applications include mapping, simulation asset creation, and photorealistic rendering for policy training.

Why it matters for physical AI

Fast, editable, photoreal scene reconstructions narrow the sim-to-real visual gap and enable real-to-sim pipelines where robots train in digital twins of the exact environments they will operate in.