Comparative Analysis of Autonomous Indoor Exploration Strategies: Floodfill algorithm vs. Frontier-Based Method
Naufaldo, Hsiu‐Ming Wu · 2024
This paper investigates the efficiency of autonomous indoor exploration utilizing simulation testing environments in Gazebo. Two exploration methods, Floodfill algorithm and Frontier-based algorithm, using the 2D LiDAR sensor are compared. The Floodfill algorithm employs a systematic traversal approach, while the Frontier-based method dynamically detects and navigates towards frontiers. Results indicate that the Frontier-based approach outperforms Flood-fill Algorithm in terms of efficiency and map completeness, particularly in complex environments. The study underscores the importance of the Frontier-based strategy for autonomous indoor exploration and paves the way for enhanced robotic applications in diverse domains.