Implementation of Unmanned aerial vehicles (UAVs) for assessment of transportation infrastructure - Phase II

Technological advances in unmanned aerial vehicle (UAV) technologies continue to enable these tools to become easier to use, more economical, and applicable for transportation-related operations, maintenance, and asset management while also increasing safety and decreasing cost. This Phase 2 project continued to test and evaluate five main UAV platforms with a combination of optical, thermal, and lidar sensors to determine how to implement them into MDOT workflows. Field demonstrations were completed at bridges, a construction site, road corridors, and along highways with data being processed and analyzed using customized algorithms and tools. Additionally, a cost-benefit analysis was conducted, comparing manual and UAV-based inspection methods. The project team also gave a series of technical demonstrations and conference presentations, enabling outreach to interested audiences who gained understanding of the potential implementation of this technology and the advanced research that MDOT is moving to implementation. The outreach efforts and research activities performed under this contract demonstrated how implementing UAV technologies into MDOT workflows can provide many benefits to MDOT and the motoring public; such as advantages in improved cost-effectiveness, operational management, and timely maintenance of Michigan’s transportation infrastructure

Automated flight planning for roof inspection using a face-based approach

The rapid proliferation of consumer small unmanned aerial systems (sUASs) has expanded ownership to include amateurs and professionals alike. These platforms in combination with numerous open source and proprietary applications tailored to gather aerial imagery and generate 3D point clouds and meshes from aerial imagery, have made 3D modeling available to anyone who can afford an entry-level sUAS. These flight plans force the sensor to remain at greater distances from their targets, resulting in varying spatial resolution of sloped surfaces. The work described here explains the development of a variety of 3D automated flight plans to provide vantage points not achievable by constant-altitude, nadir-looking imagery. Specifically, the issue of roof inspection is addressed in detail. This work generates an automated flight plan that positions the sUAS and orients its sensor such that the focal plane array is parallel to the roof plane based on a priori knowledge of the roof\u27s geometry, greatly reducing single- or two-point perspective. This a priori knowledge can come from a variety sources including databases, a site survey, or data extracted from an existing point cloud. Still images or video from orthogonal flight plans can be used for visual inspection, or the generation of dense point clouds and meshes. These products are compared to those generated from nadir imagery. This novel flight planning approach permits the aircraft to fly the orthogonal flight plans from start to finish without intervention from the remote pilot. This work is scalable to similar sUAS-based tasks including aerial-based thermography of buildings and infrastructure