High-flying unmanned reconnaissance and surveillance systems are now being used extensively in the United States military. Current development programs are producing demonstrations of next-generation unmanned flight systems that are designed to perform combat missions. Their use in first-strike combat operations will dictate operations in densely cluttered environments that include unknown obstacles and threats, and will require the use of terrain for masking. The demand for autonomy of operations in such environments dictates the need for advanced trajectory optimization capabilities. In addition, the ability to coordinate the movements of more than one aircraft in the same area is an emerging challenge. This thesis examines using an analytical reduced order formulation for trajectory generation for minimum time and terrain masking cases. First, pseudo-3D constant velocity equations of motion are used for path planning for a single vehicle. In addition, the inclusion of winds, moving targets and moving threats is considered. Then, this formulation is increased to using 3D equations of motion, both with a constant velocity and with a simplified varying velocity model. Next, the constant velocity equations of motion are expanded to include the simultaneous path planning of an unspecified number of vehicles, for both aircraft avoidance situations and formation flight cases.

The field of man portable UASs (Unmanned Aerial Systems) is currently a key area in improving the fielded warrior's capabilities. Pressurized aerostructures that can perform with similar results of solid structures can potentially change how this objective may be accomplished now and in the future. Construction with high density polymers and other composites is currently part of active inflatable vehicle research. Many shape forming techniques have also been adapted from the airship and balloon manufacturing industry. Additional research includes modeling techniques so that these vehicles may be included in simulation packages. A flight dynamics simulation with reduced-order aeroelastic effects derived with Lagrangian and Eulerian dynamics approaches were developed and optimized to predict the behavior of inflatable flexible structures in small UASs. The models are used to investigate the effects of significant structural deflections (warping) on aerodynamic surfaces. The model also includes compensation for large buoyancy ratios. Existing literature documents the similarity in structural dynamics of rigid beams and inflatable beams before wrinkling. Therefore, wing bending and torsional modes are approximated with the geometrically exact ntrinsic beam equations using NATASHA (Nonlinear Aeroelastic Trim And Stability for HALE Aircraft) code. An approach was also suggested for inclusion of unique phenomena such as wrinkling during flight. A simplified experimental setup will be designed to examine the most significant results observed from the simulation model. These methods may be suitable for specifying limits on flight maneuvers for inflatable UASs.

The Hopping Rotochute is a promising micro vehicle with the capability of exploring rough and complex terrains with minimum energy consumption. While it is able to fly over obstacles via thrust produced by its coaxial rotor, its physical architecture, inspired from a "Weebles Wooble," provides re-orientation wherever it hits the ground. Therefore, this aerial and ground vehicle represents a potential hybrid vehicle capable of reconnaissance and surveillance missions in complex environments. The most recent version of the Hopping Rotochute is manually controlled to follow a trajectory. The control commands, listed in a file prior to the particular mission, are executed exactly as defined, like a "batch job," regardless of the uncertain external events. This control scheme is likely to cause great deviations from the route. Consequently, the vehicle may finish the mission very far away from the desired end point. However, if a vehicle is capable of receiving the control commands during a mission, "interactive processing" can be realized and efficient path tracking would be achieved. Hence, the development of the Hopping Rotochute that follows a trajectory autonomously reveals the foundation of this thesis. Two control approaches inspired the proposed methodology for developing an autonomous trajectory-following algorithm. The first approach is rule-based control that enables decision making through conditional statements. In this thesis, rule-based control is used to select a target point for a particular hop based on the existence of an obstacle and/or wind in the environment. The second approach is model predictive control employed to predict future outputs from hop performance models. In other words, this technique approaches the problem by providing intelligence pertaining to how a particular hop will end up before being attempted. Hence, the optimum control commands are selected based on the predicted performance of a particular hop. This research demonstrates that the autonomous Hopping Rotochute can be realized by rule-based control embedded with some performance models. In the assumption of known boundaries such as wall and ceiling information, this study has two aims: (1) to avoid obstacles by creating a smaller operational volume inside the real boundaries so that the vehicle is restricted from exiting the operational volume and no violation occurs within the real boundaries; (2) to estimate the wind by previous hops to select the next hopping point with respect to the estimated wind information. Based on the developed methodology, simulations are conducted for four different scenarios in the existence of obstacles and/or wind, and the results of the simulations are analyzed. Finally, based on the statistics of simulation results, the effectiveness of the proposed methodology is discussed.

Thesis (M.S. in Aeronautical Engineering)--Naval Postgraduate School, June 2003. / Thesis advisor(s): Isaac Kaminer, Vladimir Dobrokhodov. Includes bibliographical references (p. 67). Also available online.

The field of mobile robotic systems has become a rich area of research and design. These systems can navigate difficult terrain using multiple actuators with conventional ambulation, by hopping, jumping, or for aerial vehicles, using flapping wings, propellers, or engines to maintain aerial flight. Unmanned Aerial Systems(UAS) have been used extensively in both military and civilian applications such as reconnaissance or search and rescue missions. For air vehicles, range and endurance is a crucial design parameter as it governs which missions can be performed by a particular vehicle. In addition, when considering the presence of external disturbances such as atmospheric winds, these missions can be even more challenging. Meta aircraft technologies is one area of research that can increase range and endurance by taking advantage of an increase in L/D. A meta aircraft is an aircraft composed of smaller individual aircraft connected together through a similar connection mechanism that can potentially transfer power, loads, or information. This dissertation examines meta aircraft flight dynamics and controls for a variety of different configurations. First, the dynamics of meta aircraft systems are explored with a focus on the changes in fundamental aircraft modes and flexible modes of the system. Specifically, when aircraft are connected, the fundamental modes change, can become overdamped or even unstable. In addition, connected aircraft exhibit complex flexible modes and mode shapes that change based on the parameters of the connection joint and the number of connected aircraft. Second, the connection dynamics are explored for meta aircraft where the vehicles are connected wing tip to wing tip using passive magnets with a particular focus on modeling the connection event between aircraft in a practical environment. It is found that a multi-stage connection control law with position and velocity feedback from GPS and connection point image feedback from a camera yields adequate connection performance in the presence of realistic sensor errors and atmospheric winds. Furthermore, atmosphericwinds with low frequency gusts at the intensity normally found in a realistic environment pose the most significant threat to the success of connection. The frequency content of the atmospheric disturbance is an important variable to determine success of connection. Finally, the geometry of magnets that create the connection force field can alter connection rates. Finally, the performance of a generic meta aircraft system are explored. Using a simplified rigid body model to approximate any meta aircraft configuration, adequate connection is achieved in the presence of realistic winds. Using this controller overall performance is studied. In winds, there is an overall decrease in outer loop performance for meta aircraft. However, inner loop performance increases for meta aircraft. In addition, the aerodynamic benefit of different configurations are investigated. Wing to wing tip connected flight provides the most benefit in terms of average increased Lift to Drag ratio while tip to tail configurations drop the Lift to Drag ratio as trailing aircraft fly in the downwash of the leading aircraft.

This thesis aims at detecting obstacles using a single camera in an unknown 3D world for 3D motion of the robot/UAV. Obstacle detection is a pre-requisite for collision-free motion of robots/UAVs. Most of the research in this area has been for 2D motion of the ground robots and with active sensors e.g Laser range finders, Ultrasonic sensors, SONAR, RADAR etc. The passive camera based research has mostly been done either using triangulation/stereo vision (using more than one camera), or, developing an expectation map pre-hand, of the world and comparing it with the new image data. In contrast, this thesis, aims at finding solution of the problem using just a single camera in a perfectly unknown world. This requirement is based on the fact that at least a single camera would be carried by almost all robots/UAVs anyway in foreseeable future. Hence the attempt is to use the same camera for obstacle detection and avoidance task as well, so as to come up with a low cost and light weight solution, in order to facilitate building miniature robots/UAVs.

This thesis presents the development of small, inexpensive unmanned aerial vehicles (UAVs) to achieve autonomous fight. Fixed wing hobby model planes are modified and instrumented to form experimental platforms. Different sensors employed to collect the flight data are discussed along with their calibrations. The time constant and delay for the servo-actuators for the platform are estimated. Two different data collection and processing units based on micro-controller and PC104 architectures are developed and discussed. These units are also used to program the identification and control algorithms. Flight control of fixed wing UAVs is a challenging task due to the coupled, time-varying, nonlinear dynamic behaviour. One of the possible alternatives for the flight control system is to use the intelligent adaptive control techniques that provide online learning capability to cope with varying dynamics and disturbances. Neural network based indirect adaptive control strategy is applied for the current work. The two main components of the adaptive control technique are the identification block and the control block. Identification provides a mathematical model for the controller to adapt to varying dynamics. Neural network based identification provides a black-box identification technique wherein a suitable network provides prediction capability based upon the past inputs and outputs. Auto-regressive neural networks are employed for this to ensure good retention capabilities for the model that uses the past outputs and inputs along with the present inputs. Online and offline identification of UAV platforms are discussed based upon the flight data. Suitable modifications to the Levenberg-Marquardt training algorithm for online training are proposed. The effect of varying the different network parameters on the performance of the network are numerically tested out. A new performance index is proposed that is shown to improve the accuracy of prediction and also reduces the training time for these networks. The identification algorithms are validated both numerically and flight tested. A hardware-in-loop simulation system has been developed to test the identification and control algorithms before flight testing to identify the problems in real time implementation on the UAVs. This is developed to keep the validation process simple and a graphical user interface is provided to visualise the UAV flight during simulations. A dual neural network controller is proposed as the adaptive controller based upon the identification models. This has two neural networks collated together. One of the neural networks is trained online to adapt to changes in the dynamics. Two feedback loops are provided as part of the overall structure that is seen to improve the accuracy. Proofs for stability analysis in the form of convergence of the identifier and controller networks based on Lyapunov's technique are presented. In this analysis suitable bounds on the rate of learning for the networks are imposed. Numerical results are presented to validate the adaptive controller for single-input single-output as well as multi-input multi-output subsystems of the UAV. Real time validation results and various flight test results confirm the feasibility of the proposed adaptive technique as a reliable tool to achieve autonomous flight. The comparison of the proposed technique with a baseline gain scheduled controller both in numerical simulations as well as test flights bring out the salient adaptive feature of the proposed technique to the time-varying, nonlinear dynamics of the UAV platforms under different flying conditions.

Thesis (M.S.)--University of Texas at El Paso, 2007. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (M.S.)--School of Advanced Air and Space Studies, 2008. / "June 2008." Vita. Includes bibliographical references (p. 58-63). Also available via the Internet.

Thesis (M.S.)--School of Advanced Air and Space Studies, 2008. / "June 2008." Vita. Includes bibliographical references (p. 82-84). Also available via the Internet.