Navigation & SLAM

Semantic SLAM

Semantic SLAM is simultaneous localization and mapping augmented with semantic information, producing maps that contain labeled objects and regions rather than only geometry. Systems detect and segment objects during mapping, insert them as landmarks in the factor graph, and can exploit semantics for data association and loop closure — recognizing a place by its objects rather than raw appearance. Object-level SLAM systems and 3D scene graph builders are representative examples.

Why it matters for physical AI

Maps that know what things are, not just where surfaces lie, are the substrate for instruction following, mobile manipulation, and long-term autonomy in changing environments.