Date of Award
Master of Science in Engineering
Mechanical and Aerospace Engineering
Dr. Kapseong Ro
Dr. Koorosh Naghshineh
Dr. James W. Kamman
Masters Thesis-Open Access
The research conducted explores the comparison of several trilateration algorithms as they apply to the localization of a quadcopter micro air vehicle (MAV). A localization system is developed employing a network of combined ultrasonic/radio frequency sensors used to wirelessly provide range (distance) measurements defining the location of the quadcopter in 3-dimensional space. A Monte Carlo simulation is conducted using the extrinsic parameters of the localization system to evaluate the adequacy of each trilateration method as it applies to this specific quadcopter application. The optimal position calculation method is determined.
Furthermore, flight testing is performed in which real range measurement data are collected for the purpose of post-processing and evaluation of the quadcopter’s high-level open-loop response to three basic inputs: pitch/roll, thrust, and yaw rate (heading angle). The raw range measurement data allow for the calculation of position data that are then brought into the System Identification Toolbox environment within Matlab. This tool is then used to generate ‘best fit’ transfer functions for each of the aforementioned dynamic responses.
Befus, Kenneth, "Localization and System Identification of a Quadcopter UAV" (2014). Master's Theses. 499.