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.

The NASA Airborne Topographic Mapper (ATM) is a laser scanning instrument which is used mainly to collect dense topographic data over much of the conterminous US coastline. The inclusion of two digital cameras in consonance with the ATM instrument now gives 3-band (RGB) imagery apart from a very rich topographic data. This imagery, in its crude form, has limited applications due to it being not georeferenced and having a heavy camera lens distortions. As thesis, a processing system - Park-View - is developed to bring this imagery into a more suitable format for the scientists for analytical and interpretational purposes. Park-View utilizes the well gridded elevation data from layer four of another processing system called LaserMap for georeferencing the digital camera images. Camera lens behavior is modeled using a 2D grid image and all of its intrinsic parameters ascertained. These parameters are then incorporated into correcting the lens distortions of georeferenced images. Errors in time-stamping of images and in the mounting angles of the camera are calculated using well known tie-points. Georeferenced images can be stored either in GeoTiff format or jpeg format. Individual images can be georeferenced or put in a mosaic form with the mosaic color equalized for adjoining images. Park-View also provides the main GUI displaying the entire surveyed area, mapper GUI for a batch processing of all the images and a display window for displaying georeferenced images or mosaics. Additional capabilities could be added to the processing system for performing some specific image processing operations on the images such as edge detection and image enhancement.

This thesis describes how a pipeline was obtained to reconstruct an urban environment from terrestrial laser scanning and photogrammetric 3D maps of Norrköping, visualized in first prison and real-time. Together with LIU University and the city planning office of Norrköping the project was carried out as a preliminary study to get an idea of how much work is needed and in what accuracy we can recreate a few buildings. The visualization is intended to demonstrate a new way of exploring the city in virtual reality as well as visualize the geometrical and textural details in a higher quality comparing to the 3D map that Municipality of Norrköping uses today. Before, the map has only been intended to be displayed from a bird’s eye view and has poor resolution from closer ranges. In order to improve the resolution, HDR photos were used to texture the laser scanned model and cover a particular area of the low res 3D map. This thesis will explain which method was used to process a point based environment for texturing and setting up an environment in Unreal using both the 3d map and the laser scanned model.

This thesis derives an vision based feedback control strategy for a class of uncertain projector-camera systems that are used to animate two dimensional projected images on complex, three dimensional, articulated target objects. The target object of the robotic system is articulated using an open loop control strategy that generates a desired sequence of target poses that are designed using commercially available geometric modeling software. The ideal or desired image sequences are subsequently rendered in the geometric modeling software using an ideal camera/projector pose and ideal intrinsic parameter camera model. The rendered imagery from the ideal camera and projector pose are subsequently used to define tracking performance for the feedback control of the camera and projector. Uncertainty in actuator models of the camera and projector actuator subsystems in this paper includes contributions due to imprecision in camera pose and in intrinsic camera parameters. A feedback control strategy is derived that employs pixel coordinates of multiple tracked feature points in the target image sequence for pose estimation and tracking control problems. We establish sufficient conditions that guarantee the convergence and asymptotic stability of the pose estimation and tracking control problems for the class of uncertain, nonlinear systems studied in this thesis. Several numerical studies are summarized in the thesis that provide confidence in the derived theoretical results and further suggest robustness of the control strategy for the considered uncertainty class. / Master of Science