Perception

Voxel Hashing

Voxel hashing is a sparse volumetric data structure, introduced by Niessner et al. in 2013, that stores only voxel blocks near observed surfaces in a spatial hash table instead of allocating a dense grid over the whole scene. It enables real-time TSDF fusion and large-scale 3D reconstruction at fine resolution with bounded memory, and it remains a standard component in GPU reconstruction pipelines.

Why it matters for physical AI

Reconstructing workspaces at millimeter resolution in real time is only tractable with sparse volumetric storage, making voxel hashing a key enabler for on-robot dense mapping and scene-level manipulation planning.