Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Mechanical and Aerospace Engineering

Committee Chair

Mario G. Perhinschi.


This thesis explores a variety of path planning and trajectory generation schemes intended for small, fixed-wing Unmanned Aerial Vehicles. Throughout this analysis, discrete and pose-based methods are investigated. Pose-based methods are the focus of this research due to their increased flexibility and typically lower computational overhead.;Path planning in 3 dimensions is also performed. The 3D Dubins methodology presented is an extension of a previously suggested approach and addresses both the mathematical formulation of the methodology, as well as an assessment of numerical issues encountered and the solutions implemented for these.;The main contribution of this thesis is a 3-dimensional clothoid trajectory generation algorithm, which produces flyable paths of continuous curvature to ensure a more followable commanded path. This methodology is an extension of the 3D Dubins method and the 2D clothoid method, which have been implemented herein. To ensure flyability of trajectories produced by 3D pose-based trajectory generation methodologies, a set of criteria are specified to limit the possible solutions to only those flyable by the aircraft. Additionally, several assumptions are made concerning the motion of the aircraft in order to simplify the path generation problem.;The 2D and 3D clothoid and Dubins trajectory planners are demonstrated through a trajectory tracking performance comparison between first the 2D Dubins and 2D clothoid methods using a position proportional-integral-derivative controller, then the 3D Dubins and 3D clothoid methods using both a position proportional-integral-derivative controller and an outer-loop non-linear dynamic inversion controller, within the WVU UAV Simulation Environment. These comparisons are demonstrated for both nominal and off-nominal conditions, and show that for both 2D and 3D implementations, the clothoid path planners yields paths with better trajectory tracking performance as compared to the Dubins path planners.;Finally, to increase the effectiveness and autonomy of these pose-based trajectory generation methodologies, an immunity-based evolutionary optimization algorithm is developed to select a viable and locally-optimal trajectory through an environment while observing desired points of interest and minimizing threat exposure, path length, and estimated fuel consumption. The algorithm is effective for both 2D and 3D routes, as well as combinations thereof. A brief demonstration is provided for this algorithm. Due to the calculation time requirements, this algorithm is recommended for offline use.