Systems composed of simple, reliable tools are needed to facilitate adoption of Uncrewed Aerial Vehicles (UAVs) into incident response teams. Existing systems require operators to have highly skilled level of knowledge of UAV operations, including mission planning, low-level system operation, and data analysis. In this paper, a system is introduced to reduce required operator knowledge level via streamlined mission planning, in-flight object detection, and data presentation. For mission planning, two software programs are introduced that utilize geographic data to: (1) update existing missions to a constant above ground level altitude; and (2) auto-generate missions along waterways. To test system performance, a UAV platform based on the Tarot 960 was equipped with an Nvidia Jetson TX2 computing device and a FLIR GigE camera. For demonstration of on-board object detection, the You Only Look Once v8 model was trained on mock propane tanks. A Robot Operating System package was developed to manage communication between the flight controller, camera, and object detection model. Finally, software was developed to present collected data in easy to understand interactive maps containing both detected object locations and surveyed area imagery. Several flight demonstrations were conducted to validate both the performance and usability of the system. The mission planning programs accurately adjust altitude and generate missions along waterways. While in flight, the system demonstrated the capability to take images, perform object detection, and return estimated object locations with an average accuracy of 3.5 meters. The calculated object location data was successfully formatted into interactive maps, providing incident responders with a simple visualization of target locations and surrounding environment. Overall, the system presented meets the specified objectives by reducing the required operator skill level for successful deployment of UAVs into incident response scenarios. / Master of Science / Systems composed of simple, reliable tools are needed to facilitate adoption of Uncrewed Aerial Vehicles (UAVs) into incident response teams. Existing systems require operators to have a high level of knowledge of UAV operations. In this paper, a new system is introduced that reduces required operator knowledge via streamlined mission planning, in-flight object detection, and data presentation. Two mission planning computer programs are introduced that allow users to: (1) update existing missions to maintain constant above ground level altitude; and (2) to autonomously generate missions along waterways. For demonstration of in-flight object detection, a computer vision model was trained on mock propane tanks. Software for capturing images and running the computer vision model was written and deployed onto a UAV equipped with a computer and camera. For post-flight data analysis, software was written to create image mosaics of the surveyed area as well as to plot detected objects on maps. The mission planning software was shown to appropriately adjust altitude in existing missions and to generate new missions along waterways. Through several flight demonstrations, the system appropriately captured images and identified detected target locations with an average accuracy of 3.5 meters. Post-flight, the collected images were successfully combined into single-image mosaics with detected objects marked as points of interest. Overall, the system presented meets the specified objectives by reducing the required operator skill level for successful deployment of UAVs into incident response scenarios.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115602 |
| Date | 29 June 2023 |
| Creators | Link, Eric Matthew |
| Contributors | Mechanical Engineering, Kochersberger, Kevin Bruce, Leonessa, Alexander, Komendera, Erik |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf, application/pdf |
| Rights | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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