<p>The use of Unmanned Aerial Vehicles (UAVs) has rapidly increased over the last years. This has been possible mainly due to the increased computing power of microcontrollers and computers. An UAV can be used in both civilian and military areas, for example surveillance and intelligence. The UAV concerned in this master's thesis is a prototype and is currently being developed at DST Control AB in Linköping.</p><p>With the use of UAVs, the need for a positioning and navigation system arises. Inertial sensors can often give a good position estimation, however, they need continuous calibration due to error build-up and drift in gyros. An external reference is needed to correct for this drift and other errors. The positioning system investigated in this master's thesis is supposed to work in an area defined by an inverted cone with the height of 25m and a diameter of 10m.</p><p>A comparison of different techniques suitable for position sensing has been performed. These techniques include the following: a radio method based on the Instrument Landing System (ILS), an optical method using a Position Sensing Detector (PSD), an optical method using the Indoor GPS system, a distance measurement method with ultrasound and also a discussion of the Global Positioning System (GPS).</p><p>An evaluation system has been built using the PSD sensor and tests have been performed to evaluate its possibilities for positioning. Accuracy in the order of a few millimetres has been achieved in position estimation with the evaluation system.</p>

In this thesis, a solution to the multi-Unmanned Aerial Vehicle (UAV) search and intercept problem for a moving target is presented. For the search phase, an adapted diffusion-based algorithm is used to manage the target uncertainty while individual UAVs are controlled with a hybrid receding horizon / potential method. The coordinated search is made possible by an uncertainty weighting process. The team intercept phase algorithm is a behavioural approach based on the analytical solution of Isaac's Single-Pursuer/Single-Evader (SPSE) homicidal chau ffeur problem. In this formulation, the intercepting control is taken to be a linear combination of the individual SPSE controls that would exist for each of the evader/pursuer pairs. A particle swarm optimizer is applied to find approximate optimal weighting coefficients for discretized intervals of the game time. Simulations for the team search, team intercept and combined search and intercept problem are presented.

In this thesis, a solution to the multi-Unmanned Aerial Vehicle (UAV) search and intercept problem for a moving target is presented. For the search phase, an adapted diffusion-based algorithm is used to manage the target uncertainty while individual UAVs are controlled with a hybrid receding horizon / potential method. The coordinated search is made possible by an uncertainty weighting process. The team intercept phase algorithm is a behavioural approach based on the analytical solution of Isaac's Single-Pursuer/Single-Evader (SPSE) homicidal chau ffeur problem. In this formulation, the intercepting control is taken to be a linear combination of the individual SPSE controls that would exist for each of the evader/pursuer pairs. A particle swarm optimizer is applied to find approximate optimal weighting coefficients for discretized intervals of the game time. Simulations for the team search, team intercept and combined search and intercept problem are presented.

Aeroelastic aspects of unmanned aerial vehicles (UAVs) is analyzed by treatment of a typical section containing geometrical nonlinearities. Equations of motion are derived and numerical integration of these equations subject to quasi-steady aerodynamic forcing is performed. Model properties are tailored to a high-altitude long-endurance unmanned aircraft. Harmonic balance approximation is employed based on the steady-state oscillatory response of the aerodynamic forcing. Comparisons are made between time integration results and harmonic balance approximation. Close agreement between forcing and displacement oscillatory frequencies is found. Amplitude agreement is off by a considerable margin. Additionally, stochastic forcing effects are examined. Turbulent flow velocities generated from the von Karman spectrum are applied to the same nonlinear structural model. Similar qualitative behavior is found between quasi-steady and stochastic forcing models illustrating the importance of considering the non-steady nature of atmospheric turbulence when operating near critical flutter velocity.

This thesis investigates the crucial problem of collision avoidance for autonomous vehicles.  An anti-collision system for an unmanned aerial vehicle (UAV) is studied in particular. The purpose of this system is to make sure that the own vehicle avoids collision with other aircraft in mid-air. The sensor used to track any possible threat is for a UAV limited basically to a digital video camera. This sensor can only measure the direction to an intruding vehicle, not the range, and is therefore denoted an angle-only sensor. To estimate the position and velocity of the intruder a tracking system, based on an extended Kalman filter, is used. State estimates supplied by this system are very uncertain due to the difficulties of angle-only tracking. Probabilistic methods are therefore required for risk calculation. The risk assessment module is one of the essential parts of the collision avoidance system and has the purpose of continuously evaluating the risk for collision. To do this in a probabilistic way, it is necessary to assume a probability distribution for the tracking system output. A common approach is to assume normality, more out of habit than on actual grounds. This thesis investigates the normality assumption, and it is found that the tracking output rapidly converge towards a good normal distribution approximation. The thesis furthermore investigates the actual risk assessment module to find out how the collision risk should be determined. The traditional way to do this is to focus on a critical time point (time of closest point of approach, time of maximum collision risk etc.). A recently proposed alternative is to evaluate the risk over a horizon of time. The difference between these two concepts is evaluated. An approximate computational method for integrated risk, suitable for real-time implementations, is also validated. It is shown that the risk seen over a horizon of time is much more robust to estimation accuracy than the risk from a critical time point. The integrated risk also gives a more intuitively correct result, which makes it possible to implement the risk assessment module with a direct connection to specified aviation safety rules.

This thesis describes the work performed at Saab Aeronautics in Linkoping during 2011. The work was to study and develop distributed and centralized methods for analysis of the decision making in a group of unmanned aerial vehicles (UAVs). In addition to this, some simple scenarios were studied and the work was implemented in C++ as the simulator ComDec. The literature review presented in the report provides knowledge of strategies for collaborative UAVs (communication and decision making), understanding of the problems/constraints that are relevant for data links and insight into the algorithms for decision making and autonomy. This work has resulted in a theoretical analysis of suitable design for decision making in a group of interacting autonomous UAVs. Existing methods for distributed and centralized decision making are implemented and a demonstration ofthe outcome are presented in the thesis. It is further shown how various communication problems and disturbances affect the decision making process. Finally, advantages and disadvantages of the selected strategies (communication and decision making) are discussed.

The use of Unmanned Aerial Vehicles (UAVs) has rapidly increased over the last years. This has been possible mainly due to the increased computing power of microcontrollers and computers. An UAV can be used in both civilian and military areas, for example surveillance and intelligence. The UAV concerned in this master's thesis is a prototype and is currently being developed at DST Control AB in Linköping. With the use of UAVs, the need for a positioning and navigation system arises. Inertial sensors can often give a good position estimation, however, they need continuous calibration due to error build-up and drift in gyros. An external reference is needed to correct for this drift and other errors. The positioning system investigated in this master's thesis is supposed to work in an area defined by an inverted cone with the height of 25m and a diameter of 10m. A comparison of different techniques suitable for position sensing has been performed. These techniques include the following: a radio method based on the Instrument Landing System (ILS), an optical method using a Position Sensing Detector (PSD), an optical method using the Indoor GPS system, a distance measurement method with ultrasound and also a discussion of the Global Positioning System (GPS). An evaluation system has been built using the PSD sensor and tests have been performed to evaluate its possibilities for positioning. Accuracy in the order of a few millimetres has been achieved in position estimation with the evaluation system.

The development and testing for a UAV testbed to be used in academic research and undergraduate education is proposed in this thesis. Analysis on commercial off-the-shelf UAV systems and autopilots lead to the development of a custom, open-architecture and modular UAV testbed. The main focus is to support research in UAV control field and education of the undergraduate students. The integration and use of commercial-off-the-shelf avionics and air vehicle are described in detail. System performance is examined both in flight and on the ground. Results of the system tests show that the developed system is a functional UAV testbed to be used in research of different flight control algorithms.

The Global Positioning System (GPS) is a cornerstone in Unmanned Aerial Vehicle (UAV) navigation and is by far the most common way to obtain the position of a UAV. However, since there are many scenarios in which GPS measurements might not be available, the possibility of estimating the UAV position without using the GPS would greatly improve the overall robustness of the navigation. This thesis studies the possibility of instead using Simultaneous Localisation and Mapping (SLAM) in order to estimate the position of a UAV using an Inertial Measurement Unit (IMU) and the direction towards ground based radio transmitters without prior knowledge of their position. Simulations using appropriately generated data provides a feasibility analysis which shows promising results for position errors for outdoor trajectories over large areas, however with some issues regarding overall offset. The method seems to have potential but further studies are required using the measurements from a live flight, in order to determine the true performance.

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / The University of Arizona's Aerial Robotics Club (ARC) sponsors the development of an unmanned aerial vehicle (UAV) able to compete in the annual Association for Unmanned Vehicle Systems International (AUVSI) Seafarer Chapter Student Unmanned Aerial Systems competition. Modern programming frameworks are utilized to develop a robust distributed imagery and telemetry pipeline as a backend for a mission operator user interface. This paper discusses the design changes made for the 2013 AUVSI competition including integrating low-latency first-person view, updates to the distributed task backend, and incremental and asynchronous updates the operator's user interface for real-time data analysis.