Date of Award:
8-2023
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Electrical and Computer Engineering
Committee Chair(s)
Calvin Coopmans
Committee
Calvin Coopmans
Committee
Jacob Gunther
Committee
Greg Droge
Abstract
Drones (also known as sUAS or small Uncrewed Aerial Systems) are often flown with cameras to take images of an area of land. These images can then be used to create a map by stitching these images together. This map can then be analyzed using scientific principles to learn things about the land and make decisions or take action based on the information.
The scientific application of drones is very advantageous, but flying a drone is inherently dangerous, impacting the safety of the airspace (particularly in the event of a crash), and drones are more dangerous the bigger they are. Smaller off-the-shelf drones are readily available to the public and are quite safe and easy to use. Larger near 55-lb fixed-wing mapping drones that can fly for 2.5 hours are quite costly and bring new risks into the equation. There are many barriers and risks to being able to successfully test equipment and to improving drone mapping technology.
This research focuses on creating a simulator that can simulate the entire process of creating these scientific maps. Simulating a drone, a camera payload, and a world for the drone to fly over. By having a simulator, researchers will be able to test out new technologies without having to risk flying a drone or without having to overcome the challenges mentioned above.
This research also focuses on creating a smaller simple camera payload that can be attached to a drone for performing test flights. This allows researchers to do scientific tests without risking flying larger systems.
This work enables the testing of sUAS payload systems many times in the simulation and then, when the system works as it should, the test flights with an actual drone can commence. This reduces the amount of time it takes to develop scientific drone systems and reduces the risk of flight.
Checksum
3a7a27d32da495862145b42cee8bc2cb
Recommended Citation
Slack, Stockton G., "A Cohesive Simulation and Testing Platform for Civil Autonomous Aerial Sensing and Operations" (2023). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 8838.
https://digitalcommons.usu.edu/etd/8838
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