# ShelfAware: Real-Time Semantic Localization in Quasi-Static Environments with Low-Cost Sensors

arXiv: https://arxiv.org/abs/2512.09065 · HTML: https://mlsanity.com/paper/2512.09065/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 39 references that are in the map.
- First posted on arXiv 9 Dec 2025.

## Builds on (most cited first, 14 of 14)

- [Reloc3r: Large-Scale Training of Relative Camera Pose Regression for Generalizable, Fast, and Accurate Visual Localization](https://mlsanity.com/paper/2412.08376/) (2024)
- [Precise Detection in Densely Packed Scenes](https://mlsanity.com/paper/1904.00853/) (2019)
- [A Survey on Global LiDAR Localization: Challenges, Advances and Open Problems](https://mlsanity.com/paper/2302.07433/) (2023)
- [IR-MCL: Implicit Representation-Based Online Global Localization](https://mlsanity.com/paper/2210.03113/) (2022)
- [Long-Term Localization using Semantic Cues in Floor Plan Maps](https://mlsanity.com/paper/2210.01456/) (2022)
- [Alligat0R: Pre-Training Through Co-Visibility Segmentation for Relative Camera Pose Regression](https://mlsanity.com/paper/2503.07561/) (2025)
- [CDDT: Fast Approximate 2D Ray Casting for Accelerated Localization](https://mlsanity.com/paper/1705.01167/) (2017)
- [Robust Onboard Localization in Changing Environments Exploiting Text Spotting](https://mlsanity.com/paper/2203.12647/) (2022)
- ["I am the follower, also the boss": Exploring Different Levels of Autonomy and Machine Forms of Guiding Robots for the Visually Impaired](https://mlsanity.com/paper/2302.03481/) (2023)
- [Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective](https://mlsanity.com/paper/2003.12122/) (2020)
- ["We are at the mercy of others' opinion": Supporting Blind People in Recreational Window Shopping with AI-infused Technology](https://mlsanity.com/paper/2405.06611/) (2024)
- [Robust Lifelong Indoor LiDAR Localization using the Area Graph](https://mlsanity.com/paper/2308.05593/) (2023)
- [Beyond Omakase: Designing Shared Control for Navigation Robots with Blind People](https://mlsanity.com/paper/2503.21997/) (2025)
- [ShelfHelp: Empowering Humans to Perform Vision-Independent Manipulation Tasks with a Socially Assistive Robotic Cane](https://mlsanity.com/paper/2405.20501/) (2024)

## Built on by (most cited first, 1 of 1)

- [VLM-GLoc: Vision-Language Model Enhanced Monte Carlo Localization for Robust Semantic Global Localization in Cluttered Quasi-Static Environments](https://mlsanity.com/paper/2605.30506/) (2026)

## Abstract (arXiv)

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. ShelfAware fuses a depth likelihood with a category-centric semantic similarity and uses a precomputed bank of semantic viewpoints to perform inverse semantic proposals inside Monte Carlo Localization (MCL), yielding fast, targeted hypothesis generation on low-cost, vision-only hardware. To demonstrate perception-agnostic scalability, we evaluate ShelfAware across two domains. In a rigorously controlled mock retail environment, ShelfAware achieves a 97% global localization success rate, maintaining the highest tracking success (66%) across cart, wearable, and dynamic occlusion conditions. Furthermore, in a 3,500 sq. ft. operational grocery store leveraging an open-vocabulary vision pipeline, ShelfAware significantly outperforms both geometric and fixed-quantity semantic baselines. By modeling semantics distributionally and leveraging inverse proposals, ShelfAware resolves geometric aliasing, providing an infrastructure-free building block for mobile and assistive robots in dynamic real-world environments.