# Machine Learning aided Precise Indoor Positioning

arXiv: https://arxiv.org/abs/2204.03990 · HTML: https://mlsanity.com/paper/2204.03990/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2022.

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

- [Indoor Localization for Autonomous Robot Navigation](https://mlsanity.com/paper/2502.20731/) (2025)

## Abstract (arXiv)

This study describes a UWB and Machine Learning (ML)-based indoor positioning system. We propose a simple mathematical strategy to create data to reduce the job of measurements for fingerprint-based indoor localization systems. A considerable number of measurements can be avoided this way. The paper compares and contrasts the performance of four distinct models. Most test locations' average error may be reduced to less than 150 mm using the best model.