The economic growth and vitality of the United States relies fundamentally on having a sound, robust, and resilient infrastructure. However, after extreme events such as hurricanes, storm surge, or earthquakes, vulnerable structures often have significant damage or may be collapsed. The goal of this project is to transform the efficiency, fidelity, and safety of current critical infrastructure inspection methods by using machine intelligence through the development of autonomous unmanned aerial vehicles to document damage after extreme events. Building on prior work of the investigators related to automated inspection strategies of intact structures, the proposed research will provide new capabilities for automated damage assessment that can become key to documenting a damaged environment to facilitate a quick return to full functionality. We propose that small aerial robots, coupled with three-dimensional imaging and the state-of-the-art in planning, modeling, and analysis, will provide safe and efficient, high-precision assessment of damaged structures.