An Efficient Autonomous Exploration Method based on Frontier and Space Division for Quadrotors
Zhaoqi Wang, Haoxiang Chen, Jinting Liu, Kang Hu · 2025
The one of essential requirements for autonomous exploration is efficiency, but the performance of existing methods is not satisfactory for unreasonable paths, especially in complex, cluttered, and large-scale environments. To improve the efficiency of autonomous exploration, this paper proposes an efficient method that considers the coverage path to get the next division by dividing the entire exploration space into several uniform divisions, and the quadrotors will take the corresponding corner division from the next division as the target region for exploration path planning to get the best next viewpoint until there is no frontier cluster in the environment. The extensive simulation experiments demonstrate that the proposed method improves exploration efficiency by 5%-15% compared to three classic and mainstream methods in most scenarios.