# Efficient Dense Frontier Detection for 2D Graph SLAM Based on Occupancy Grid Submaps

## TL;DR

This paper introduces an efficient frontier detection method for 2D graph SLAM using occupancy grid submaps, enhancing autonomous exploration by improving map building and localization robustness.

## Contribution

It proposes a specialized frontier detection approach that is constrained to active submaps and robust to SLAM loop closures, advancing exploration efficiency.

## Key findings

- Improved frontier detection efficiency in 2D SLAM
- Robustness to SLAM loop closures demonstrated
- Enhanced autonomous exploration capabilities

## Abstract

In autonomous robot exploration, the frontier is the border in the world map between the explored space and unexplored space. The frontier plays an important role when deciding where in the environment the robots should go explore next. We examine a modular control system pipeline for autonomous exploration where a 2D graph SLAM algorithm based on occupancy grid submaps performs map building and localization. We provide an overview of the state of the art in frontier detection and the relevant SLAM concepts and propose a specialized frontier detection method which is efficiently constrained to active submaps, yet robust to SLAM loop closures.