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This paper introduces an autonomous system employing multirotor unmanned aerial vehicles for fast 3D exploration and inspection of vast, unknown, dynamic, and complex environments containing large open spaces as well as narrow passages. The system exploits the advantage of small‐size aerial vehicles capable of carrying all necessary sensors and computational power while providing full autonomy and mobility in constrained unknown environments. Particular emphasis is put on the robustness of the algorithms with respect to challenging real‐world conditions and the real‐time performance of all algorithms that enable fast reactions to changes in environment and thus also provide effective use of limited flight time. The system presented here was employed as a part of a heterogeneous ground and aerial system in the modeled Search & Rescue scenario in an unfinished nuclear power plant during the Urban Circuit of the Subterranean Challenge (SubT Challenge) organized by the Defense Advanced Research Projects Agency. The main goal of this simulated disastrous scenario is to autonomously explore and precisely localize specified objects in a completely unknown environment and to report their position before the end of the mission. The proposed system was part of the multirobot team that finished in third place overall and in first place among the self‐funded teams. The proposed unmanned aerial vehicle system outperformed all aerial systems participating in the SubT Challenge with respect to versatility, and it was also the self‐deployable autonomous aerial system that explored the largest part of the environment. [ABSTRACT FROM AUTHOR]