This placeholder project focuses on how embodied agents maintain useful spatial memory over long time horizons while reasoning about goals, constraints, and uncertainty.
We are interested in navigation policies, memory-augmented world models, and planning systems that remain effective when tasks require multi-step reasoning across large spaces.
This page is a placeholder for future project details, papers, demos, and datasets.