Map Learning, Localization and Navigation

Overview

How does an agent know where it is? This line of work asks how a map can be learned rather than measured — building representations of space that support localization and navigation directly from an agent’s own motion, without GPS.

The projects below explore that question from several directions: topological map representations, trajectory-based localization with sequence models, and geometric reconstruction from imagery.