Date of Award
Fall 12-2018
Access Type
Thesis - Open Access
Degree Name
Master of Science in Aerospace Engineering
Department
Aerospace Engineering
Committee Chair
Hever Moncayo
First Committee Member
Richard Prazenica
Second Committee Member
Snorri Gudmundsson
Abstract
In recent years, the interest of investigating intelligent systems for Unmanned Aerial Vehicles (UAVs) have increased in popularity due to their large range of capabilities such as on-line obstacle avoidance, autonomy, search and rescue, fast prototyping and integration in the National Air Space (NAS). Many research efforts currently focus on system robustness against uncertainties but do not consider the probability of readjusting tasks based on the remaining resources to successfully complete the mission. In this thesis, an intelligent algorithm approach is proposed along with decision-making capabilities to enhance UAVs post-failure performance. This intelligent algorithm integrates a set of path planning algorithms, a health monitoring system and a power estimation approach. Post-fault conditions are considered as unknown uncertainties that unmanned vehicles could encounter during regular operation missions. In this thesis, three main threats are studied: the presence of unknown obstacles in the environment, sub-system failures, and low power resources. A solution for adapting to new circumstances is addressed by enabling autonomous decision-making and re-planning capabilities in real time.
Scholarly Commons Citation
Rivera, Karina, "Design and Implementation of Intelligent Guidance Algorithms for UAV Mission Protection" (2018). Doctoral Dissertations and Master's Theses. 433.
https://commons.erau.edu/edt/433