# 2D SLAM Quality Evaluation Methods

arXiv: https://arxiv.org/abs/1708.02354 · HTML: https://mlsanity.com/paper/1708.02354/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Aug 2017.

## Built on by (most cited first, 2 of 2)

- [PSS-BA: LiDAR Bundle Adjustment with Progressive Spatial Smoothing](https://mlsanity.com/paper/2403.06124/) (2024)
- [Robust Second-order LiDAR Bundle Adjustment Algorithm Using Mean Squared Group Metric](https://mlsanity.com/paper/2409.01856/) (2024)

## Abstract (arXiv)

SLAM (Simultaneous Localization and mapping) is one of the most challenging problems for mobile platforms and there is a huge amount of modern SLAM algorithms. The choice of the algorithm that might be used in every particular problem requires prior knowledge about advantages and disadvantages of each algorithm. This paper presents the approach for comparison of SLAM algorithms that allows to find the most accurate one. The accent of research is made on 2D SLAM algorithms and the focus of analysis is 2D map that is built after algorithm performance. Three metrics for evaluation of maps are presented in this paper