# Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing

arXiv: https://arxiv.org/abs/2110.01749 · HTML: https://mlsanity.com/paper/2110.01749/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Oct 2021.

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

- [System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models](https://mlsanity.com/paper/2312.06810/) (2023)

## Abstract (arXiv)

In this paper, we introduce a set-theoretic approach for mobile robot localization with infrastructure-based sensing. The proposed method computes sets that over-bound the robot body and orientation under an assumption of known noise bounds on the sensor and robot motion model. We establish theoretical properties and computational approaches for this set-theoretic localization approach and illustrate its application to an automated valet parking example in simulations and to omnidirectional robot localization problems in real-world experiments. We demonstrate that the set-theoretic localization method can perform robustly against uncertainty set initialization and sensor noises compared to the FastSLAM.