Advances in millimeter-scale fabrication processes have enabled rapid progress towards the development of flapping wing micro air vehicles with wing spans of several centimeters and a system mass on the order of 100mg. Concerning flight stability and control mechanisms for these mass and power limited devices, this dissertation explores the use of underactuated “mechanically intelligent” systems to passively regulate forces and torques encountered during flight. Several experiments demonstrate passive torque regulation in physical flapping wing systems. Finally, this dissertation concludes with a detailed description of the Printed Circuit MEMS manufacturing process, developed to address the practical problem of building complex insect-scale machines. / Engineering and Applied Sciences

Flapping wing propulsion has the potential to revolutionise the field of Micro Aerial Vehicles (MAVs), but little is known about the effect of flapping motion on the performance of flapping wings. Prototype MAVs have achieved flight with passive flapping wings moving in a sinusoidal flapping motion, but the possible benefits of alternative flapping motions have not been studied in detail. This thesis presents the development of an Integrated Testing System (ITS), which allows the evaluation of flapping wing performance for different flapping motions. A detailed parametric study of the effect of flapping motion on wing performance is performed, and the optimal flapping motion for several passive flapping wings is determined by hardware-in-the-loop optimisation of two wing performance metrics. The developed ITS was able to automatically test a variety of passive flapping wings, and demonstrated precise control of the flapping motion and accurate and repeatable measurements of average lift force, mechanical power, and wing twist angle. The parametric study revealed that of the three flapping motions tested, the sinusoidal flapping motion generated the highest lift force, but a smoothed triangular motion was able to generate lift significantly more efficiently under load. The optimal flapping motion was successfully determined for three flapping wings, and was found to increase the loaded effciency of the wings by an average of 31% over a sinusoidal flapping motion. The determined optimal motion was almost identical for the three tested wings, and was found to strongly resemble the flapping motion of insects These findings demonstrate that significant improvements in the performance of passive flapping wings can be achieved by relatively minor variations of the flapping motion. This increased understanding will ideally lead to more efficient flapping wing MAVs with higher payloads, longer flight times, and improved performance.

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This thesis documents the design and development of a robust backpackable proof-of-concept unmanned aerial vehicle. The unmanned aerial vehicle?s design departs from existing configurations in utilizing a keel beam fuselage which replaces the enclosed fuselage by a flat keel beam on which the sensors, the autopilot, their related power sources, and flight control systems are mounted. The keel beam fuselage is provides enhanced mounting capability for multiple sensors and quick reconfiguration in the field. The keel beam fuselage can also be manufactured quicker than a traditional enclosed fuselage. The objective of this study is to demonstrate that the keel beam configuration is a viable design for an unmanned aerial vehicle and the challenges of modular, plug-n-play hardware. The design, fabrication, and flight testing of the air vehicle are addressed.

The purpose of this thesis was to implement an Model Predictive Control based system identification method on a micro-aerial vehicle (DJI Matrice 100) as outlined in a study performed by ETH Zurich. Through limited test flights, data was obtained that allowed for the generation of first and second order system models. The first order models were robust, but the second order model fell short due to the fact that the data used for the model was not sufficient.

Master of Engineering (Research) / This thesis, by developing a Miniature Aerial Vehicle (MAV) hovering platform, presents a practical solution to allow researchers and students to implement their theoretical methods for guidance and navigation in the real world. The thesis is not concerned with the development of guidance and navigation algorithms, nor is it concerned with the development of external sensors. There have been some recent advances in guidance and navigation towards developing algorithms and simple sensors for MAVs. The task of developing a platform to test such advancements is the subject of this thesis. It is considered a difficult and time consuming process due to the complexities of autonomous flight control and the strict size, weight and computational requirements of this type of system. It would be highly beneficial to be able to buy a platform specifically designed for this task that already possesses autonomous hovering capability and the expansion connectivity for interfacing your own custom developed sensors and algorithms. Many biological and computer scientists would jump at the opportunity to maximize their research by real world implementation. The development of such a system is not a trivial task. It requires a great deal of understanding in a broad range of fields including; Aeronautical, Microelectronic, Mechanical, Computer and Embedded Software Engineering in order to create a successful prototype. The challenge of this thesis was to design a research platform to enable easy implementation of external sensors and guidance algorithms, in a real world environment for research and education. The system is designed so it could be used for a broad range of testing experiments. After extensive research in current MAV and avionics design it became obvious in several areas the best available products were not sufficient to meet the needs of the proposed platform. Therefore it was necessary to custom design and build; sensors, a data acquisition system and a servo controller. The latter two products are available for sale by Jimonics (www.jimonics.com). It was then necessary to develop a complete flight control system with integrated sensors, processor and wireless communications network which is called ‘The MicroBrain’. ‘The MicroBrain’ board measures only 45mm x 35mm x 11mm and weighs ~11 grams. The coaxial contra-rotating MAV platform design provides a high level of mechanical stability to help minimise the control system complexity. The platform was highly modified from a commercially available remotely controlled helicopter. The system incorporates a novel collision protection system that was designed to also double as a mounting place for external sensors around its perimeter. The platform equipped with ‘The MicroBrain’ is capable of fully autonomous hover. This provides a great base for testing guidance and navigational sensors and algorithms by decoupling the difficult task of platform design and low-level stability control. By developing a platform with these capabilities the researcher can now focus on the guidance and navigation task, as the difficulties in developing a custom platform have been taken care of. This therefore promotes a faster evolution of guidance and navigational control algorithms for MAVs.

<p>This thesis project has been carried out at Linköpings universitet at the Department of Mechanical Engineering. The emphasis of the project lies in the exploration of automatic selection of components for a propulsion kit. Specifically for this project, propulsion based on electric power and meeting the requirements for use in a Micro Aerial Vehicle (MAV). The key features include a systematic selection method based on user criterias and a model for evaluating propeller performance. These are implemented in a program written as a part of the project. The conclusion is that it is possible to make a program capable of a component selection and that the programs usability is mainly reliant on three factors: model for propeller evaluation, method of selection and the quality of the component database.</p>

The success of unmanned aerial vehicles (UAV) in the Iraq and Afghanistan conflicts has led to increased interest in further digitalization of the United States armed forces. Although unmanned systems have been a tool of the military for several decades, only recently have advances in the field of Micro-Electro-Mechanical Systems (MEMS) technology made it possible to develop systems capable of being transported by an individual soldier. These miniature unmanned systems, more commonly referred to as micro air vehicles (MAV), are envisioned by the Department of Defense as being an integral part of maintaining America?s military superiority. As researchers continue to make advances in the miniaturization of flight hardware, a new problem with regard to MAV field operations is beginning to present itself. To date, little work has been done to determine an effective means of collecting, analyzing, and handling information that can satisfy the goal of using MAVs as tools for persistent surveillance. Current systems, which focus on the transmission of analog video streams, have been very successful on larger UAVs such as the RQ-11 Raven but have proven to be very demanding of the operator. By implementing a new and innovative data processing methodology, currently existing hardware can be adapted to effectively present critical information with minimal user input. Research currently being performed at Texas A&M University in the areas of attitude determination and image processing has yielded a new application of photographic projection. By replacing analog video with spatially aware high-resolution images, the present MAV handheld ground control stations (GCS) can be enhanced to reduce the number of functional manpower positions required during operation. Photographs captured by an MAV can be displayed above pre-existing satellite imagery to give an operator a lasting reference to the location of objects in his vicinity. This newly generated model also increases the functionality of micro air vehicles by allowing for target tracking and energy efficient perch and stare capabilities, both essential elements of persistent surveillance.

Master of Engineering (Research) / This thesis, by developing a Miniature Aerial Vehicle (MAV) hovering platform, presents a practical solution to allow researchers and students to implement their theoretical methods for guidance and navigation in the real world. The thesis is not concerned with the development of guidance and navigation algorithms, nor is it concerned with the development of external sensors. There have been some recent advances in guidance and navigation towards developing algorithms and simple sensors for MAVs. The task of developing a platform to test such advancements is the subject of this thesis. It is considered a difficult and time consuming process due to the complexities of autonomous flight control and the strict size, weight and computational requirements of this type of system. It would be highly beneficial to be able to buy a platform specifically designed for this task that already possesses autonomous hovering capability and the expansion connectivity for interfacing your own custom developed sensors and algorithms. Many biological and computer scientists would jump at the opportunity to maximize their research by real world implementation. The development of such a system is not a trivial task. It requires a great deal of understanding in a broad range of fields including; Aeronautical, Microelectronic, Mechanical, Computer and Embedded Software Engineering in order to create a successful prototype. The challenge of this thesis was to design a research platform to enable easy implementation of external sensors and guidance algorithms, in a real world environment for research and education. The system is designed so it could be used for a broad range of testing experiments. After extensive research in current MAV and avionics design it became obvious in several areas the best available products were not sufficient to meet the needs of the proposed platform. Therefore it was necessary to custom design and build; sensors, a data acquisition system and a servo controller. The latter two products are available for sale by Jimonics (www.jimonics.com). It was then necessary to develop a complete flight control system with integrated sensors, processor and wireless communications network which is called ‘The MicroBrain’. ‘The MicroBrain’ board measures only 45mm x 35mm x 11mm and weighs ~11 grams. The coaxial contra-rotating MAV platform design provides a high level of mechanical stability to help minimise the control system complexity. The platform was highly modified from a commercially available remotely controlled helicopter. The system incorporates a novel collision protection system that was designed to also double as a mounting place for external sensors around its perimeter. The platform equipped with ‘The MicroBrain’ is capable of fully autonomous hover. This provides a great base for testing guidance and navigational sensors and algorithms by decoupling the difficult task of platform design and low-level stability control. By developing a platform with these capabilities the researcher can now focus on the guidance and navigation task, as the difficulties in developing a custom platform have been taken care of. This therefore promotes a faster evolution of guidance and navigational control algorithms for MAVs.

This thesis project has been carried out at Linköpings universitet at the Department of Mechanical Engineering. The emphasis of the project lies in the exploration of automatic selection of components for a propulsion kit. Specifically for this project, propulsion based on electric power and meeting the requirements for use in a Micro Aerial Vehicle (MAV). The key features include a systematic selection method based on user criterias and a model for evaluating propeller performance. These are implemented in a program written as a part of the project. The conclusion is that it is possible to make a program capable of a component selection and that the programs usability is mainly reliant on three factors: model for propeller evaluation, method of selection and the quality of the component database.