4 accepted papers
This paper presents the largest known benchmark dataset for road damage assessment and road alignment, and provides 18 baseline models trained on the CRASAR-U-DRIODs dataset
This paper presents the first AI/ML system for automating building damage assessment in uncrewed aerial systems (sUAS) imagery to be deployed operationally during federally declared disasters (Hurricanes Debby and Helene). In response to major disasters, sUAS teams are dispatched to collect imagery
This letter proposes a formal robot motion risk reasoning framework and develops a risk-aware path planner that minimizes the proposed risk. While robots locomoting in unstructured or confined environments face a variety of risk, existing risk only focuses on collision with obstacles. Such risk is c
This work provides a case study of both fixed-wing and rotorcraft small unmanned aerial systems (SUAS) used in a deployment at the SR530 mudslides in Washington state and compares the types of flight paths used by each vehicle type. Previously aerial imagery from SUAS have produced 2D and 3D reconst…