Dissertations and Theses 2016 A Biomimetic, Energy-Harvesting, Obstacle-Avoiding, Path- Planning Algorithm for UAVs Snorri Gudmundsson Follow this and additional works at: https://commons.erau.edu/edt Part of the Automotive Engineering Commons, and the Mechanical Engineering Commons Scholarly Commons Citation Gudmundsson, Snorri, "A Biomimetic, Energy-Harvesting, Obstacle-Avoiding, Path-Planning Algorithm for UAVs" (2016). Dissertations and Theses. 306. https://commons.erau.edu/edt/306 This Dissertation - Open Access is brought to you for free and open access by Scholarly Commons. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of Scholarly Commons. For more information, please contact
[email protected]. A BIOMIMETIC, ENERGY-HARVESTING, OBSTACLE-AVOIDING, PATH-PLANNING ALGORITHM FOR UAVs A DISSERTATION SUBMITTED TO THE DEPARTMENT OF MECHANICAL ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF EMBRY-RIDDLE AERONAUTICAL UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Snorri Gudmundsson 2016 © Copyright by Snorri Gudmundsson, 2016 All Rights Reserved ii THIS PAGE INTENTIONALLY LEFT BLANK iv ABSTRACT This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class.