AI RESEARCH
ShelfAware: Real-Time Semantic Localization in Quasi-Static Environments with Low-Cost Sensors
arXiv CS.AI
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ArXi:2512.09065v2 Announce Type: replace-cross Many indoor workspaces are quasi-static: their global geometric layout is stable, but local semantics change continually, producing repetitive geometry, dynamic clutter, and perceptual noise that defeat standard vision-based localization. We present ShelfAware, a semantic particle filter for robust global localization that treats scene semantics as statistical evidence over object categories rather than fixed quantity landmarks.