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The design and implementation of a morphing unmanned aircraft using smart materials is presented. Articulated lifting surfaces and articulated wing sections actuated by servos are difficult to instrument and fabricate in a repeatable fashion on thin, composite-wing micro-air-vehicles. Assembly is complex and time consuming. A type of piezoceramic composite actuator commonly known as Macro Fiber Composite (MFC) is used for wing morphing. The actuation capability of this actuator on fiberglass unimorph was modeled by the Rayleigh-Ritz method and quantified by experimentation. Wind tunnel tests were performed to compare conventional trailing edge control surface effectiveness to an MFC actuated wing section. The continuous surface of the MFC actuated composite airfoil produced lower drag and wider actuation bandwidth. The MFC actuators were implemented on a 0.76 m wingspan aircraft. The remotely piloted experimental vehicle was flown using two MFC patches in an elevator/aileron (elevon) configuration. Preliminary testing has proven the stability and control of the design. Flight tests were performed to quantify roll control using the actuators. Force and moment coefficients were measured in a low-speed, open section wind tunnel, and the database of aerodynamic derivatives were used to analyze control response. / Master of Science

<p>The use of drones, also called unmanned aerial vehicles (UAVs), is increasing every day. These aircraft are piloted either remotely by a human pilot or completely autonomously by an on-board computer. UAVs are typically equipped with a video camera providing a live video feed to the operator. While they were originally developed mainly for military purposes, many civil applications start to emerge as they become more affordable.<p><p><p>Micro air vehicles are a subgroup of UAVs with a size and weight limitation; many are designed also for indoor use. Designs with rotary wings are generally preferred over fixed wings as they can take off vertically and operate at low speeds or even hover. At small scales, designs with flapping wings are being explored to try to mimic the exceptional flight capabilities of birds and insects. <p><p><p>The objective of this thesis is to develop a control mechanism for a robotic hummingbird, a bio-inspired tail-less hovering flapping wing MAV. The mechanism should generate moments necessary for flight stabilization and steering by an independent control of flapping motion of each wing.<p><p><p>The theoretical part of this work uses a quasi-steady modelling approach to approximate the flapping wing aerodynamics. The model is linearised and further reduced to study the flight stability near hovering, identify the wing motion parameters suitable for control and finally design a flight controller. Validity of this approach is demonstrated by simulations with the original, non-linear mathematical model.<p><p><p>A robotic hummingbird prototype is developed in the second, practical part. Details are given on the flapping linkage mechanism and wing design, together with tests performed on a custom built force balance and with a high speed camera. Finally, two possible control mechanisms are proposed: the first one is based on wing twist modulation via wing root bars flexing; the second modulates the flapping amplitude and offset via flapping mechanism joint displacements. The performance of the control mechanism prototypes is demonstrated experimentally. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Micro Autonomous Systems and Technologies (MAST) is an Army Research Laboratory (ARL) sponsored project based on a consortium of revolutionary academic and industrial research institutions working together to develop new technologies in the field of microelectronics, autonomy, micromechanics and integration. The overarching goal of the MAST consortium is to develop autonomous, multifunctional, and collaborative ensembles of microsystems to enhance small unit tactical situational awareness in urban and complex terrain. Unmanned systems are used to obtain intelligence at the macro level, but there is no real-time intelligence asset at the squad level. MAST seeks to provide that asset. Consequently, multiple integrated MAST heterogeneous platforms (e.g. crawlers, flyers, etc.) working together synergistically as an ensemble shall be capable of autonomously performing a wide spectrum of operational functions based on the latest developments in micro-mechanics, micro-electronics, and power technologies to achieve the desired operational objectives. The design of such vehicles is, by nature, highly constrained in terms of size, weight and power. Technologists are trying to understand the impacts of developing state-of-the-art technologies on the MAST systems while the operators are trying to define strategies and tactics on how to use these systems. These two different perspectives create an integration gap. The operators understand the capabilities needed on the field of deployment but not necessarily the technologies, while the technologists understand the physics of the technologies but not necessarily how they will be deployed, utilized, and operated during a mission. This not only results in a major requirements disconnect, representing the difference of perspectives between soldiers and the researchers, but also demonstrates the lack of quantified means to assess the technology gap in terms of mission requirements. This necessitates the quantification and resolution of the requirements disconnect and technology gap leading to re-definitions of the requirements based on mission scenarios. A research plan, built on a technical approach based on the simultaneous application of decomposition and re-composition or 'Top-down' and 'Bottom-up' approaches, was used for development of a structured and traceable methodology. The developed methodology is implemented through an integrated framework consisting of various decision-making tools, modeling and simulation, and experimental data farming and validation. The major obstacles in the development of the presented framework stemmed from the fact that all MAST technologies are revolutionary in nature, with no available historical data, sizing and synthesis codes or reliable physics-based models. The inherently multidisciplinary, multi-objective and uncertain nature of MAST technologies makes it very difficult to map mission level objectives to measurable engineering metrics. It involves the optimization of multiple disciplines such as Aero, CS/CE, ME, EE, Biology, etc., and of multiple objectives such as mission performance, tactics, vehicle attributes, etc. Furthermore, the concept space is enormous with hundreds of billions of alternatives, and largely includes future technologies with low Technology Readiness Level (TRL) resulting in high uncertainty. The presented framework is a cyber-physical design and analysis suite that combines Warfighter mission needs and expert technologist knowledge with a set of design and optimization tools, models, and experiments in order to provide a quantitative measure of the requirements disconnect and technology gap mentioned above. This quantification provides the basis for re-definitions of the requirements that are realistic in nature and ensure mission success. The research presents the development of this methodology and framework to address the core research objectives. The developed framework was then implemented on two mission scenarios that are of interest to the MAST consortium and Army Research Laboratory, namely, Joppa Urban Dwelling and Black Hawk Down Interior Building Reconnaissance. Results demonstrate the framework’s validity and serve as proof of concept for bridging the requirements disconnect between the Warfighter and the technologists. Billions of alternative MAST vehicles, composed of current and future technologies, were modeled and simulated, as part of a swarm, to evaluate their mission performance. In-depth analyses of the experiments, conducted as part of the research, presents quantitative technology gaps that needs to be addressed by technologist for successful mission completion. Quantitative values for vehicle specifications and systems' Measures of Performance were determined for acceptable level of performance for the given missions. The consolidated results were used for defining mission based requirements of MAST systems.

M.Phil. / This work proposes a fast local image feature detector and descriptor that is im- plementable on a GPU. The BFROST feature detector is the first published GPU implementation of the popular FAST detector. A simple but novel method of feature orientation estimation which can be calculated in constant time is proposed. The robustness and reliability of the orientation estimation is validated against rotation invariant descriptors such as SIFT and SURF. Furthermore, the BFROST feature descriptor is robust to noise, scalable, rotation invariant, fast to compute in parallel and maintains low memory usage. It is demonstrated that BFROST is usable in real-time applications such as vision-based localization and mapping of images captured from micro aerial platforms.

Aerial recovery of autonomous micro air vehicles (MAVs) presents many unique challenges due to the difference in size and speed of the recovery vehicle and MAV. This thesis presents algorithms to enable an autonomous MAV to estimate the orbit of a recovery vehicle and track the orbit until the final docking phase. Methods for estimating ellipses that are rotated out of the x − y plane are developed and demonstrated through simulation. These algorithms are shown to be robust to noise and stable numerically. Parameter update methods that are computationally inexpensive, such as recursive least squares and Kalman filtering, are discussed and simulated. A discussion is given of orbit tracking algorithms for circular orbits, and these methods are expanded to include elliptical orbits. These algorithms enable the MAV to track the recovery vehicle's orbit, based on a vector field approach. The tracking algorithms are divided into lateral and longitudinal controllers that allow for tracking of inclined orbits. Finally, the hardware and software setup for live flight tests is discussed. Flight test results are given that validate the functionality of the orbit estimation and orbit tracking algorithms.

Biological phenomena found in nature can be learned and customized to obtain innovative engineering solutions. In recent years, biologists found that birds and bats use their mechanoreceptors to sense the airflow information and use this information directly to achieve their agile flight performance. Inspired by this phenomenon, an attitude control system for micro air vehicles using rich amount of airflow sensor information is proposed, designed and tested. The dissertation discusses our research findings on this topic. First, we quantified the errors between the calculated and measured lift and moment profiles using a limited number of micro pressure sensors over a straight wing. Then, we designed a robust pitching controller using 20 micro pressure sensors and tested the closed-loop performance in a simulated environment. Additionally, a straight wing was designed for the pressure sensor based pitching control with twelve pressure sensors, which was then tested in our low-speed wind tunnel. The closed-loop pitching control system can track the commanded angle of attack with a rising time around two seconds and an overshoot around 10%. Third, we extended the idea to the three-axis attitude control scenarios, where both of the pressure and shear stress information are considered in the simulation. Finally, a fault tolerant controller with a guaranteed asymptotically stability is proposed to deal with sensor failures and calculation errors. The results show that the proposed fault tolerant controller is robust, adaptive, and can guarantee an asymptotically stable performance even in case that 50% of the airflow sensors fail in flight.

No description available.

This dissertation broadly seeks to understand the effect different kinematic parameters, external forces, and dynamic wing conformation have on the fluid dynamics of flapping flight. The primary motivation is to better grasp the fundamental fluid phenomena driving efficient flapping flight in the Reynolds number regime of birds, bats, and man made fliers of similar scale. The CFD solver (GenIDLEST) used is a Navier-Stokes solver in a finite volume formulation on non-staggered structured multiblock meshes. It has the capability for both body-fitted moving grid simulations and Immersed Boundary Method (IBM) for simulating complex bodies moving within a fluid. To that purpose we investigate the response of a rigid flapping thin surface planar wing in forward flight, at Re=10,000, subjected to frontal gusts. Gusts are a common ecological hazard for flapping fliers, especially in crowded environments. Among the various temporal and spatial scales of gust possible, we look at the phasing and duration of very large spatial scale gusts and their impact on the unsteady fluid dynamics of flapping within a single flapping cycle. The gust is characterized by a step function with time scale much smaller than the flapping time period. Having the advantage of prescribing the motion, as well as the timing and duration of the gust, this allowed the observation of the effect of angle of attack (AOA) and wing rotation on the evolution of the Leading Edge Vortex (LEV) and, hence the instantaneous lift and thrust profiles, by varying the parameters. During the downstroke, frontal gusts accelerated the flow development resulting in early separation of existing LEVs and formation of new ones on the wing surface which influenced the force generation by increasing the lift and thrust. These phenomena underscored the importance of the unsteady vortex structures as the primary force generators in flapping flight.The effect of the gust is observed to be diminished when it occurs during rapid supination of the wing. Unlike the influence of the vortices during the downstroke, the upstroke primarily reacted to effective AOA changes. A key characteristic of the kinematics of fliers in nature is stroke deviation. We investigate this phenomenon using a similar framework as above on a rigid thin surface flat-plate flapping wing in forward flight. Stroke deviation happens due to a variety of factors including wing flexion, wing lateral translation, and wing area change and here we investigate the different stroke deviation trajectories. Various trajectories were analyzed to assess the different capabilities that such kinematics might offer. The instantaneous lift and thrust profiles were observed to be influenced by a combination of the Leading Edge Vortex (LEV) and the Trailing Edge Vortex (TEV) structures existing in the flow at any given time. As an index of the cost of performance across all cases, the power requirements for the different cases, based on the fluid torques, are analyzed. Anti-clockwise figure-of-eight-cycle deviation is shown to be very complex with high power costs while having better performance. The clockwise elliptic-cycle held promise in being utilized as a viable stroke deviation trajectory for forward flight over the base non stroke deviation case. Armed with insight gained from these simple flapping structures, we are able to conduct the analysis of the flapping flight data obtained on a fruit bat. Understanding the full complexity of bat flight and the ways in which bat flight differs from that of other vertebrate flight requires attention to the intricate functional mechanics and architecture of the wings and the resulting unsteady transient mechanisms of the flow around the wings. We extract the detailed kinematic motion of the bat wing from the recorded data and then simulate the bat wing motion in the CFD framework for a range of Reynolds numbers. The Strouhal number calculated from the data is high indicating that the flow physics is dominated by the oscillatory motion. From the data the bat exhibits fine control of its mechanics by actively varying wing camber, wing area, torsional rotation of the wing, forward and backward translational sweep of the wing, and wing conformation to dictate the fluid dynamics. As is common in flapping flight, the primary force generation is through the attached unsteady vortices on the wing surface. This force output is modulated by the bat through varying wing camber and the wing area. Proper orthogonal decomposition of the wing kinematics is undertaken to compile a simpler set of kinematic modes that can approximate the original motion used by the fruit bat. These modes are then analyzed based on aerodynamic performance and power cost for more efficient flight. Understanding the physics of these modes will help us use them as prescribed kinematics for mechanical flappers as well as improve upon them from nature. / Ph. D.