Object SearchIntermediate
LOCUS: Landmark-Oriented Container Discrimination Using Spatial Graphs
This preprint presents LOCUS, a graph neural network that updates CLIP embeddings with spatial context from a scene graph to rank same-class containers when searching for occluded objects. In iTHOR simulation, it reduces expected containers opened per search to 0.257 of all containers, a 24% improvement over TidyBot, and transfers zero-shot to RoboCasa and a Stretch 3 real-kitchen pilot. It matters because real robots must choose among visually identical drawers or cabinets, which existing class-level methods cannot do.