Graduation Semester and Year
2019
Language
English
Document Type
Thesis
Degree Name
Master of Science in Electrical Engineering
Department
Electrical Engineering
First Advisor
Frank Lewis
Abstract
Unmanned Aerial Vehicles (UAVs) have gained mass popularity in fields such as Defense, Agriculture, Sport and Photography etc. Their wide adoption in such research projects have opened new horizons for opportunities. However, UAVs operate in a rather dynamic environment since various factors such as airspeed, temperature, pressure, turbulence etc. are capable of hampering the flight operation. There is a need for rather robust trajectory generation algorithm and system such that it provides an easy user interface to specify the path of UAV through space, alongside making the UAV capable enough to maneuver itself from the initial to final position. This project focuses on two aspects of UAV control, the first part focuses on trajectory generation using various mathematically modeled techniques for the position, velocity and acceleration expressed as a function of time. Their comparison is done based on the constraint-based optimization techniques followed by some discussions. The second part focuses on UAV simulators and lays out the foundations and requirements for them, followed by some proposed simulators and their comparison, which could be used not only for flight control simulation, but also have potential to integrate Reinforcement Learning techniques for Autonomous flight control and Autopilot systems. Finally, in-depth analysis of AirSim simulator is carried out along with its environment setup process which may be used as an Interfacing, Installation and set-up documentation for future work.
Keywords
UAV, UAV simulator, AirSim
Disciplines
Electrical and Computer Engineering | Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Bhushan, Neha, "UAV: Trajectory Generation and Simulation" (2019). Electrical Engineering Theses. 363.
https://mavmatrix.uta.edu/electricaleng_theses/363
Comments
Degree granted by The University of Texas at Arlington