Autonomous exploration using unmanned aerial vehicles (UAVs) is essential for various tasks such as building inspections, rescue operations, deliveries, and warehousing. However, there are two main limitations to previous approaches: they may not be able to provide a complete map of the environment and assume that the map built during exploration is accurate enough for safe navigation, which is usually not the case. To address these limitations, a novel exploration method is proposed that combines frontier-based exploration with a collector strategy that achieves global exploration and complete map creation. In each iteration, the collector strategy stores and validates frontiers detected during exploration and selects the next best frontier to navigate to. The collector strategy ensures global exploration by balancing the exploitation of a known map with the exploration of unknown areas. In addition, the online path replanning ensures safe navigation through the map created during motion. The performance of the proposed method is verified by exploring 3D simulation environments in comparison with the state-of-the-art methods. Finally, the proposed approach is validated in a real-world experiment.

翻译：利用无人机进行自主探索在建筑检查、搜救任务、物资投递和仓储管理等诸多领域具有重要价值。然而，现有方法存在两个主要局限：既无法提供完整的环境地图，又假设探索过程中构建的地图足以支持安全导航——而这通常并不成立。针对这些问题，本文提出一种融合前沿探索与收集策略的新型探索方法，该方法能够实现全局探索与完整地图构建。在每次迭代中，收集策略会存储并验证探索过程中检测到的前沿区域，并选择最优的下一个导航前沿。通过平衡已知地图的利用与未知区域的探索，收集策略确保了全局探索的有效性。此外，在线路径重规划机制保障了运动过程中基于实时构建地图的安全导航。通过三维仿真环境下的对比实验，验证了所提方法相较于当前最优技术的性能优势。最终，真实场景实验进一步证实了该方法的有效性。