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

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