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Author: Sameera S. Ponda Publisher: ISBN: Category : Languages : en Pages : 197
Book Description
(cont.) The UAV trajectory optimization is performed for stationary targets, dynamic targets and multiple targets, for many different scenarios of vehicle motion constraints. The resulting trajectories show spiral paths taken by the UAV, which focus on increasing the angular separation between measurements and reducing the relative range to the target, thus maximizing the information provided by each measurement and improving the performance of the estimation. The main drawback of information based trajectory design is the dependence of the Fisher Information Matrix on the true target location. This issue is addressed in this project by executing simultaneous target location estimation and UAV trajectory optimization. Two estimation algorithms, the Extended Kalman Filter and the Particle Filter are considered, and the trajectory optimization is performed using the mean value of the target estimation in lieu of the true target location. The estimation and optimization algorithms run in sequence and are updated in real-time. The results show spiral UAV trajectories that increase filter convergence and overall estimation accuracy, illustrating the importance of information-based trajectory design for target localization using small UAVs.
Author: Sameera S. Ponda Publisher: ISBN: Category : Languages : en Pages : 197
Book Description
(cont.) The UAV trajectory optimization is performed for stationary targets, dynamic targets and multiple targets, for many different scenarios of vehicle motion constraints. The resulting trajectories show spiral paths taken by the UAV, which focus on increasing the angular separation between measurements and reducing the relative range to the target, thus maximizing the information provided by each measurement and improving the performance of the estimation. The main drawback of information based trajectory design is the dependence of the Fisher Information Matrix on the true target location. This issue is addressed in this project by executing simultaneous target location estimation and UAV trajectory optimization. Two estimation algorithms, the Extended Kalman Filter and the Particle Filter are considered, and the trajectory optimization is performed using the mean value of the target estimation in lieu of the true target location. The estimation and optimization algorithms run in sequence and are updated in real-time. The results show spiral UAV trajectories that increase filter convergence and overall estimation accuracy, illustrating the importance of information-based trajectory design for target localization using small UAVs.
Author: Jenna Elisabeth Newcomb Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 56
Book Description
An unmanned aerial vehicle (UAV) swarm allows for a more time-efficient method of searching a specified area than a single UAV or piloted plane. There are a variety of factors that affect how well an area is surveyed. We specifically analyzed the effect both vehicle properties and communication had on the swarm search performance. We used non-dimensionalization so the results can be applied to any domain size with any type of vehicle. We found that endurance was the most important factor. Vehicles with good endurance sensed approximately 90% to 100% of the grid, even when other properties were lacking. If the vehicles lacked endurance, the amount of area the vehicles could sense at a given time step became more important and 10% more of the grid was sensed with the increase in sensed area. The maneuverability of the vehicles was measured as the vehicles' radii of turn compared to the search domain size. The maneuverability mattered the most in the middle-range endurance cases. In some cases 30% more of the grid was searched with improving vehicle maneuverability. In addition, we also examined four communication cases with different amounts of information regarding vehicle location. We found communication increased search performance by at least 6.3%. However, increasing the amount of information only changed the performance by 2.3%. We also studied the impact the range of vehicle communication had on search performance. We found that simulations benefited most from increasing the communication range when the amount of area sensed at a given time step was small and the vehicles had good maneuverability. We also extended the optimization to a multi-objective process with the inclusion of target tracking. We analyzed how the different weightings of the objectives affected the performance outcomes. We found that target tracking performance dramatically changes based on the given weighting of each objective and saw an increase of approximately 52%. However, the amount of the grid that was sensed only dropped by approximately 10%.
Author: David Linn Johansen Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 98
Book Description
Unmanned Aerial Vehicles (UAVs) equipped with lightweight, inexpensive cameras have grown in popularity by enabling new uses of UAV technology. However, the video retrieved from small UAVs is often unwatchable due to high frequency jitter. Beginning with an investigation of previous stabilization work, this thesis discusses the challenges of stabilizing UAV based video. It then presents a software based computer vision framework and discusses its use to develop a real-time stabilization solution. A novel approach of estimating intended video motion is then presented. Next, the thesis proceeds to extend previous target localization work by allowing the operator to easily identify targets rather than relying solely on color segmentation to improve reliability and applicability in real world scenarios. The resulting approach creates a low cost and easy to use solution for aerial video display and target localization.
Author: Steven Andrew Provencio Quintero Publisher: ISBN: 9781321349955 Category : Languages : en Pages : 215
Book Description
Small unmanned aerial vehicles (UAVs) are relatively inexpensive mobile sensing platforms capable of reliably and autonomously performing numerous tasks, including mapping, search and rescue, surveillance and tracking, and real-time monitoring. The general problem of interest that we address is that of using small, fixed-wing UAVs to perform vision-based target tracking, which entails that one or more camera-equipped UAVs is responsible for autonomously tracking a moving ground target. In the single-UAV setting, the underactuated UAV must maintain proximity and visibility of an unpredictable ground target while having a limited sensing region. We provide solutions from two different vantage points. The first regards the problem as a two-player zero-sum game and the second as a stochastic optimal control problem. The resulting control policies have been successfully field-tested, thereby verifying the efficacy of both approaches while highlighting the advantages of one approach over the other.
Author: Benjamin Thomas Gatzke Publisher: ISBN: Category : Drone aircraft Languages : en Pages : 61
Book Description
This thesis explores the numerical methods and software development for optimal trajectories of a specific model of Helicopter Unmanned Aerial Vehicle (UAV) in an obstacle-rich environment. This particular model is adopted from the UAV Laboratory of the National University of Singapore who built and simulated flights for an X-Cell 60 small-scale UAV Helicopter. The code, which allowed the team to simulate flights, is a complex system of non-linear differential equations-5 state variables and four control variables-used to maneuver the state trajectories. This non-linear model is incorporated into a separate optimization algorithm code, which allows the user to set initial and final time conditions together with various constraints, and, using the same variable scheme, optimize a trajectory. The optimal trajectory is defined by using a cost function-the performance measure-and the system is subject to a set of constraints (such as mechanical limitations and physical three-dimensional obstacles). Simulations conclude that solutions are readily obtained; however, it is still very difficult to derive trajectories that are truly optimal, and our work calls for more future research in computational programs for optimal trajectory planning. All simulations in this thesis are modeled using the MATLAB program.
Author: Tristan Charles Flanzer Publisher: ISBN: Category : Languages : en Pages :
Book Description
A robust trajectory optimization method is formulated using a stochastic collocation based approach and is then applied to the design of periodic dynamic soaring trajectories for unmanned aerial vehicles (UAVs). Repetitive control is proposed and evaluated as a means for reducing tracking error for UAVs flying periodic trajectories both in simulation and experimentally. Experiments conducted in an indoor flying laboratory outfitted with a VICON motion capture system demonstrate significant reductions in tracking error even in the presence of large and unknown disturbances.
Author: Leonard Nathaniel Wholey Publisher: ISBN: Category : Languages : en Pages : 118
Book Description
Unmanned aerial vehicles (UAVs) play an essential role for the US Armed Forces by performing missions deemed as "dull, dirty and dangerous" for a pilot. As the capability of UAVs expand. they will perform a broader range of missions such as air-to-air combat. The focus of this thesis is forming trajectories for the closing phase of an air-to-air combat scenario. A UAV should close with the suspected aircraft in a manner that allows a ground operator to visually identify the suspected aircraft while avoiding visual/electronic detection from the other pilot. This thesis applies and compares three methods for producing trajectories which enable a visual identification. The first approach is formulated as a mixed integer linear programming problem which can be solved in real time. However, there are limitations to the accuracy of a radar detection model formed with only linear equations, which might justify using a nonlinear programming formulation. With this approach the interceptor's radar cross section and range between the suspected aircraft and interceptor can be incorporated into the problem formulation. The main limitation of this method is that the optimization software might not be able to reach online an optimal or even feasible solution. The third applied method is trajectory interpolation. In this approach, trajectories with specified boundary values and dynamics are formed offline; online, the method interpolates between the given trajectories to obtain similar maneuvers with different initial conditions and end- states. With this method, because the number of calculations required to produce a feasible trajectory is known, the amount of time to calculate a trajectory can be estimated.
Author: Sameera S. Ponda
Author: Sameera S. Ponda
Author: Jenna Elisabeth Newcomb
Author: David Linn Johansen
Author: Steven Andrew Provencio Quintero
Author: Benjamin Thomas Gatzke
Author: John Patrick Tisdale
Author: Tristan Charles Flanzer
Author: Leonard Nathaniel Wholey
Author: 
Author: Jeffrey B. Corbets