The goal of this project is to use inspiration acquired from bird flight to optimize the wing planform of micro-air vehicle wings. Micro-air vehicles are used by the military for surveillance and for search and rescue missions by civilian first-responders. These vehicles fly in the same low Reynolds number regime as birds, and have low aspect ratios similar to the pheasants and grouse of the order Galliformes. Conventional analysis is difficult for low Reynolds numbers, prompting use of biologically inspired methods of optimization. Genetic algorithms, which mimic the process of evolution in nature, were used to define wing shapes that were tested in wind tunnel experiments. In these experiments, lift-drag ratios at various angles of attack were measured on scale model micro-air vehicle wings (with variable length feathers) similar in shape to a bird wing. The planform shape of the scale model wing evolved in the wind tunnel flow over successive generations to ultimately produce superior wings with higher lift-drag ratios. The low angle of attack wings were easily optimized into a wing shape different from and potentially more efficient than the oft-used Zimmerman planform. The process was repeated for a higher angle of attack, near stall conditions, which yielded a different wing planform shape. Chord distributions of the optimized low angle of attack wings were found to closely match the same distributions of birds from the order Galliformes. Results from flow visualization studies meant to illuminate possible physics responsible for the higher lift-drag ratios were also investigated.

Using robots to navigate through un-mapped environments, specially man-made infrastructures, for the purpose of exploration or inspection is a topic that has gathered a lot of interest in the last years. Micro Aerial Vehicles (MAV's) have the mobility and agility to move quickly and access hard-to-reach areas where ground robots would fail, but using MAV's for that purpose comes with its own set of problems since any collision with the environment results in a crash. The control architecture used in a MAV for such a task needs to perform obstacle avoidance and on-line path-planning in an unknown environment with low computation times as to not lose stability. In this thesis a Non-linear Model Predictive Controller (NMPC) for obstacle avoidance and path-planning on an aerial platform will be established. Included are methods for constraining the available state-space, simulations of various obstacle avoidance scenarios for single and multiple MAVs and experimental validation of the proposed control architecture. The validity of the proposed approach is demonstrated through multiple experimental and simulation results. In these approaches, the positioning information of the obstacles and the MAV are provided by a motion-capture system. The thesis will conclude with the demonstration of an experimental validation of a centralized NMPC for collision avoidance of two MAV's.

<p>Flapping flight is one of the most widespread mean of transportation. It is a complex unsteady aerodynamic problem that has been studied extensively in the past century. Nevertheless, by its complex nature, flapping flight remains a challenging subject. With the development of micro air vehicles, researchers need new computational methods to design these aircrafts efficiently. </p><p>In this dissertation, I will present three different methods of optimization for flapping flight with an emphasis on hovering with each their advantages and drawbacks. The first method was developed by Hall et al. It is an extremely fast and powerful three-dimensional approach. However, the assumptions made to develop this theory limit its use to lightly loaded wings. In addition, it only models the motion of the trailing edge and not the actual motion of the wing. </p><p>In a second part, I will present a two-dimensional unsteady potential method. It uses a freely convected wake which removes the lightly loaded restriction. This method shows the existence of an optimal combination of plunging and pitching motion. The motion is optimal in the sense that for a required force vector, the aerodynamic power is minimal.</p><p>The last method incorporates the three-dimensional effects. These effects are especially important for low aspect ratio wings. Thus, a three-dimensional unsteady potential vortex method was developed. This method also exhibits the presence of an optimal flapping/pitching motion. In addition, it agrees really well with the two previous methods and with the actual kinematics of birds during hovering flapping flight.</p><p>To conclude, some preliminary design tools for flapping wings in forward and hovering flight are presented in this thesis.</p> / Dissertation

In the last decade, the robotics community has pushed to develop increasingly small, autonomous flapping-wing robotic vehicles for a variety of civilian and military applications. The miniaturization of these vehicles has pushed the boundaries of technology in many areas, including electronics, artificial intelligence, and mechanics; as well as our understanding of biology. In particular, at the insect scale, fabrication, actuation, and flight control of a flapping-wing robot become especially challenging. This thesis addresses these challenges in the context of the “RoboBee” project, which has the goal of creating an autonomous swarm of at-scale robotic bees. A 100mg robot with a 3cm wingspan capable of generating roll, pitch and yaw torques in the range of \(\pm 1\mu Nm\) by using a large, central power actuator to flap the wings and smaller control actuators to steer is presented. A dynamic model is used to predict torque generation capabilities, and custom instrumentation is developed to measure and characterize the vehicle’s control torques. Finally, controlled flight experiments are presented, and the vehicle is capable of maintaining a stable pitch and roll attitude during ascending vertical flight. This is the first successful controlled flight of a truly insect-scale flapping-wing robot. / Engineering and Applied Sciences

Lilian Rocca Carbajal, máxima autoridad ejecutiva de la Superintendencia de Mercado de Valores, nos comenta brevemente algunas de las iniciativas promovidas por este organismo en los últimos años, que apuntan a posicionar al Mercado de Valores como una importante alternativa de financiamiento e inversión. Se comentan, entre otros aspectos significativos, las implicancias de la implementación del Mercado Alternativo de Valores (MAV), así como las novedades del nuevo Código de Buen Gobierno Corporativo y de la nueva regulación de Hechos de Importancia.

Cooperative control for miniature air vehicles (MAVs) is currently a highly researched topic. There are many application for which MAVs are well suited, including fire monitoring, surveillance and reconaissance, and search and rescue missions. All of these applications can be carried out more effictively by a team of MAVs than by a single vehicle. As technologies for microcontrollers and small sensors have improved so have the capabilities of MAVs. This improvement in MAV performance abilities increases the possibility for cooperative missions. The focus of this research was on cooperative timing missions. The issues faced when dealing with multi-MAV flight include information transfer, real time path planning, and maintenance of a fleet of flight-worthy MAVs. Additional challenges associated with timing missions include path following and velocity control. Two timing scenarios were studied and both of these scenarios were flight tested. The first scenario was a sequenced arrival of the MAVs over a target at a predetermined fly-through heading. The second scenario was a simultaneous arrival of the team ofMAVs over a known target location. The ideas of coordination functions and coordination variables have been employed to achieve coordination. Experimental results verify the feasibility of real time coperative control for a team of MAVs. Initial cooperative timing tests revealed the need for more accurate path following. Accordingly, a new method for path following using vector fields was developed. A vector field of desired ground track headings is calculated and commanded ground track headings are calculated such that ground track heading error and lateral following error decay asymptotically even in the presence of constant wind disturbances. The utilization of ground track heading and ground speed in the path following control, in combination with the vector field methods is what makes this zero-error following possible. Methods for following straight lines and orbits as well as combinations of the lines and circular arcs are presented. The assertions that minimal following errors result when using these methods have been verified experimentally.

No description available.

Miniature air vehicles (MAVs) are particularly well suited for short-distance, over-the-horizon, low-altitude surveillance and reconnaissance tasks. New camera and battery technologies have greatly increased a MAVs potential for these tasks. This thesis focuses on aerial surveillance of borders and roads, where a strap-down camera is used in-the-loop to track a border or road pathway. It is assumed that quality tracking requires that the pathway always remain in the footprint of the camera. The objective of this thesis is to explore roll-angle and altitude-above-ground-level constraints imposed on a bank-to-turn MAV due to the requirement to keep the pathway in the footprint of a downward-looking strap-down camera. This thesis derives the required altitude to maintain the pathway in the footprint of the camera and associated bank-angle constraints. Constraints are derived for both roads whose geometry is unknown a priori and roads with known geometry obtained from digital elevation map (DEM) data. MAV geometry and camera localization are used to derive these constraints. The thesis also discusses simple computer vision techniques for pathway following and a corresponding guidance law. The pixels of the captured color video are statistically classified into road and non-road components. Standard computer vision functions are used to eliminate classification noise and obtain a road heading direction. The effectiveness of the result is explored using a high fidelity simulator. Flight test results on small UAVs demonstrate the practicality of the road-following method.

Autonomous miniature air vehicles (MAVs) are becoming increasingly popular platforms for the collection of data about an area of interest for military and commercial applications. Two challenges that often present themselves in the process of collecting this data. First, winds can be a significant percentage of the MAV's airspeed and can affect the analysis of collected data if ignored. Second, the majority of MAV's video is transmitted using RF analog transmitters instead of the more desirable digital video due to the computational intensive compression requirements of digital video. This two-part thesis addresses these two challenges. First, this thesis presents an innovative method for estimating the wind velocity using an optical flow sensor mounted on a MAV. Using the flow of features measured by the optical flow sensor in the longitudinal and lateral directions, the MAV's crab-angle is estimated. By combining the crab-angle with measurements of ground track from GPS and the MAV's airspeed, the wind velocity is computed. Unlike other methods, this approach does not require the use of a “varying” path (flying at multiple headings) or the use of magnetometers. Second, this thesis presents an efficient and effective method for video compression by drastically reducing the computational cost of motion estimation. When attempting to compress video, motion estimation is usually more than 80% of the computation required to compress the video. Therefore, we propose to estimate the motion and reduce computation by using (1) knowledge of camera locations (from available MAV IMU sensor data) and (2) the projective geometry of the camera. Both of these methods are run onboard a MAV in real time and their effectiveness is demonstrated through simulated and experimental results.

In this thesis we develop methods that facilitate an aerial rendezvous between two air vehicles. The objective of this research is to produce a method that can be used to insert a miniature air vehicle behind a rendezvous vehicle and then track that vehicle to enable a visual rendezvous. For this research we assume the rendezvous vehicle is following a relatively stable and roughly elliptical orbit. Path planners and controllers have been developed that can be used to effectively intercept the rendezvous vehicle by inserting the MAV onto the orbit of interest. A method for planning and following time-optimal Dubins airplane interception paths between a miniature air vehicle and the rendezvous vehicle is presented. We demonstrate how a vector field path following a scheme can be used for navigation along these time-optimal Dubins airplane paths. A post-orbit insertion tracking method is also presented which can be used to track the target vehicle on an arbitrarily oriented elliptical orbit while maintaining a specified following distance. We also present controllers that can be used for disturbance rejection during the orbit-insertion and interception operations. All of these methods were implemented in simulation and with hardware. Results from these implementations are presented and analyzed.