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 field strength prediction chart is a set of statistical curves obtained through the analysis of huge amount of field strength measurement data of the specific radio band in some area. It reflects the natural or artificial effects such as geography, atmospheric condition and buildings, etc. that affect the radio wave propagation. One advantage is that we can predict the rough relationship between the field strength and distance easily. As a result, we don¡¦t have to perform simulation field measurement in every radio planning. With prediction chart and field strength interference /protection ratio standard, we can suggest a minimum distance separation criterion between co-channel and adjacent channel broadcasting stations. It also provides a reference to authority to examine the broadcasting service application. The FCC develops the F(50,50) charts and minimum separation between radio stations base on data collected in the U.S.. Presently, the regulations concerning the broadcasting applications in Taiwan still follow the FCC¡¦s suggestion. In general, the field strength distribution is affected by two main factors: geography and atmospheric condition, which can be different from those in the U.S.. With the acquisition of digital terrain data of Taiwan, the terrain profile for a given path can be generated. In this thesis, we¡¦ll use Deygout model and the database of existed broadcasting stations to generate field strength distribution database for each station and analyze the database to develop the prediction chart that is suitable for the propagation environment in Taiwan. When combine with the field strength interference /protection ratio standard, we¡¦ll provide a minimum distance separation criterion of co-channel and adjacent channel in the FM band broadcasting stations. Our study can help the authority to achieve the most effective spectrum management in FM band.

<p>Three-dimensional computer graphics enjoys a wide range of applications of which games and movies are only few examples. By incorporating three-dimensional computer graphics in to a simulator the simulator is able to provide the operator with visual feedback during a simulation. Simulators come in many different flavors where flight and radar simulators are two types in which three-dimensional rendering of large terrains constitutes a central component.</p><p>Ericsson Microwave Systems (EMW) in Skövde is searching for an algorithm that (a) can handle terrain data that is larger than physical memory and (b) has an adjustable error metric that can be used to reduce terrain detail level if an increase in load on other critical parts of the system is observed. The aim of this paper is to identify and evaluate existing algorithms for terrain rendering in order to find those that meet EMW: s requirements. The objectives are to (i) perform a literature survey over existing algorithms, (ii) implement these algorithms and (iii) develop a test environment in which these algorithms can be evaluated form a performance perspective.</p><p>The literature survey revealed that the algorithm developed by Lindstrom and Pascucci (2001) is the only algorithm of those examined that succeeded to fulfill the requirements without modifications or extra software. This algorithm uses memory-mapped files to be able to handle terrain data larger that physical memory and focuses on how terrain data should be laid out on disk in order to minimize the number of page faults. Testing of this algorithm on specified test architecture show that the error metric used could be adjusted to effectively control the terrains level of detail leading to a substantial increase in performance. The results also reveal the need for both view frustum culling as well a level of detail algorithm to achieve fast display rates of large terrains. Further the results also show the importance of how terrain data is laid out on disk especially when physical memory is limited.</p>

<p>Computer gamers demand more realistic effects for each release of a new game. This final year project is concerned with deforming the geometry in a terrain rendering environment. The intension is to increase the resolution where the original resolution of the terrain is not enough to cater for all the details associated with a deformation, such as an explosion.</p><p>An algorithm for extending the maximum available resolution was found, the DEXTER algorithm, but calculations have shown that it has a too high memory consumption to be feasible in a game environment. In this project, an algorithm has been implemented, based on the DEXTER algorithm, but with some structural changes. The algorithm which has been implemented increases the resolution, if needed, where a deformation occurs. The increased resolution is described by b-spline surfaces, whereas the original resolution is given by a height map. Further, graphics primitives are only allocated to a high resolution region, when needed by the refinement process.</p><p>It has been found that by using dynamic blocks of graphics primitives, the amount of RAM consumed can be lowered, without a severe decrease in rendering speed. However, the algorithm implemented has been found to suffer from frame rate drops, if too many high resolution cells need to be attached to the refinement process during a single frame.</p><p>Is has been concluded that the algorithm, which is the result of this final year project, is not suitable for a game environment, as the memory consumption is still too high. The amount of time spent on refining the terrain can also be considered too much, as no time is left for other aspects of a game environment.</p><p>The algorithm is however considered a good choice concerning deformations, as the updates needed in association with a deformation, can be kept small and localized, according to the DEXTER structure. Also, the b-spline surfaces offer more freedom over the deformation, compared to using a height map.</p>

Thèse de doctorat : Géographie physique : Paris Est : 2008. / Titre provenant de l'écran-titre.

Thesis (M.S.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains xi, 76 p. Vita. Includes abstract. Includes bibliographical references (p. 55-56).

Terrain attributes computed from Digital Elevation Models (DEMs) are widely used in hydrology and hydrologic modeling. It is important to consider that the values of the attributes can be different depending on the resolution of the DEM from which they are derived. The question arises as to how much exactly the high-resolution DEMs created through LIDAR remote sensing techniques change the values of the terrain attributes when compared to lower resolution DEMs.In this thesis a LIDAR-derived DEM of 20 feet resolution was resampled using a nearest-neighbour algorithm to various coarser resolutions to examine and quantify the effect of DEM resolution upon a series of hydrologically significant terrain attributes including slope, surface curvature, topographic wetness index, stream power index and stream networks. Values for slope and surface curvature are found to be smaller when computed from lower resolution DEMs; values for the topographic wetness index and stream power index are found to increase as DEM cell size increases.The derived stream networks for each resolution were compared in terms of length per stream order, drainage density, bifurcation ratio, and overall accuracy indicating a loss of small detail, but only a modest change in the overall stream network morphometry. This research suggests that it is possible to establish relationships that quantify the effects of DEM resolution upon hydrologically significant terrain attributes, which can then be considered when processing DEMs from various resolutions for the purpose of parameterizing hydrologic models.

Terrestrial robots must be capable of negotiating rough terrain if they are to become autonomous outside of the lab. Although the control mechanism offered by wheels is attractive in its simplicity, any wheeled system is confined to relatively flat terrain. Wheels will also only ever be useful for rolling, while limbs observed in nature are highly multimodal. The robust locomotive utility of legs is evidenced by the many animals that walk, run, jump, swim, and climb in a world full of challenging terrain. On the other hand, legs with multiple degrees of freedom (DoF) require much more complex control and precise sensing than wheels. Legged robotic systems are easily hampered by sensor noise and bulky control loops that prohibit the high-speed adaptation to external perturbations necessary for dynamic stability in real time. Low sensor bandwidth can limit the system’s reaction time to external perturbations. It is also often necessary to filter sensor data, which introduces significant delays in the control loop. In addition, state estimation is often relied upon in order to compute active stabilizing responses. State estimation requires accurate sensor data, often involving filtering, and can involve additional nontrivial computation such as the pseudo-inversion of fullbody Jacobians. This perception portion of the control burden is all incurred before a response can be planned and executed. These delays can prevent a system from executing a corrective response before instability leads to failure. The present work presents an approach to legged system design and control that reduces both the perception and planning aspects of the online control burden. A commonly accepted design goal in robotics is to accomplish a task with the fewest possible DoF in order to tighten the control loop and avoid the curse of dimensionality. However, animals control many DoF in a manner that adapts to external perturbations faster than can be explained by efferent neural control. The passive mechanics of segmented animal limbs are capable of rejecting unexpected disturbances without the supervision of an active controller. By simulating biomimetic limbs, we can learn more about this preflexive response, how the properties of segmented biological limbs foster self-stable passive mechanics, and how the control burden can be mitigated in robotic legged systems. The contribution of this body of work is to reduce the control burden of legged locomotion for robots by drawing on self-stabilizing mechanical design and control principles observed in animal locomotion. To that end, minimal templates such as Sensory-Coupled Action Switching Modules (SCASM), Central Pattern Generators (CPGs), and the Spring-Loaded Inverted Pendulum (SLIP) model are used to learn more about the essential components of legged locomotion. The motivation behind this work lies largely in the study of how internal, predictive models and the intrinsic mechanical properties of biological limbs help animals self-stabilize in real time. Robotic systems have already begun to demonstrate the benefits of these biological design primitives in an engineering context, such as reduced cost of transportation and an immediate mechanical response that does not need to wait for sensor feedback or planning. The original research presented here explores the extent to which these principles can be utilized in order to encourage stable legged locomotion over uneven terrain with as little sensory information as possible. A method for generating feedforward, terrain-adaptive control primitives based on a compliant limb architecture is developed. Offline analysis of system dynamics is used to develop clock-driven patterns of leg stiffness and attack angle control during late swing with which passive stance phase dynamics will produce the desired apex height and stride period to within 0.1 mm and 50 μs, respectively. A feedforward method of energy modulation is incorporated that regulates velocity to within 10−5 m/s. Preservation of a constant stride period eliminates the need for detection of the apex event. Precise predictive controls based on thorough offline dynamic modeling reduce the system’s reliance on state and environmental data, even in rough terrain. These offline models of system dynamics are used to generate a controller that predicts the dynamics of running over uneven terrain using an internal clock signal. Real-time state estimation is a non-trivial bottleneck in the control of mobile systems, legged and wheeled alike. The present work significantly reduces this burden by generating predictive models that eliminate the need for state estimation within the control loop, even in the presence of damping. The resulting system achieves not only self-stable legged running, but direct control of height, speed, and stride period without inertial sensing or force feedback. Through this work, the controller dependency on accurate and rapid sensing of the body height and velocity, apex event, and ground variation was eliminated. This was done by harnessing physics-based models of leg dynamics, used to generate predictive controls that exploit the passive mechanics of the compliant limb to their full potential. While no real world system is entirely deterministic, such a predictive model may serve as the base layer for a lightweight control architecture capable of stable robotic limb control, as in animal locomotion.

ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / The paper describes the development of a robotic platform which can autonomously map terrain using a COTS infrared imaging and ranging system. The robotic system is based on an omnidirectional platform, and can navigate typical commercial indoor environments. An on-board processor performs surface reconstruction, and condenses the point clouds generated by the ranging system to mesh models which can be more easily stored and transmitted. The processor then correlates new frames with the existing world model by using sensor odomerty. The robot will autonomously determine the best areas of the environment to map, and gather complete three dimensional color models of arbitrary environments.

Thunderstorms that occur in areas of complex terrain are a major severe weather hazard in the intermountain western U.S. Short-term quantitative estimation (QPE) of precipitation in complex terrain is a pressing need to better forecast flash flooding. Currently available techniques for QPE, that utilize a combination of rain gauge and weather radar information, may underestimate precipitation in areas where gauges do not exist or there is radar beam blockage. These are typically very mountainous and remote areas, that are quite vulnerable to flash flooding because of the steep topography. Lightning has been one of the novel ways suggested by the scientific community as an alternative to estimate precipitation over regions that experience convective precipitation, especially those continental areas with complex topography where the precipitation sensor measurements are scarce. This dissertation investigates the relationship between cloud-to-ground lightning and precipitation associated with convection with the purpose of estimating precipitation- mainly over areas of complex terrain which have precipitation sensor coverage problems (e.g. Southern Arizona).The results of this research are presented in two papers. The first, entitled Toward Development of Improved QPE in Complex Terrain Using Cloud-to-Ground Lighting Data: A case Study for the 2005 Monsoon in Southern Arizona, was published in the Journal of Hydrometeorology in December 2012. This initial study explores the relationship between cloud-to-ground lightning occurrences and multi-sensor gridded precipitation over southern Arizona. QPE is performed using a least squares approach for several time resolutions (seasonal -June, July and August-, 24 hourly and hourly) and for a 8 km grid size. The paper also presents problems that arise when the time resolution is increased, such as the spatial misplacing of discrete lightning events with gridded precipitation and the need to define a "diurnal day" that is synchronized with the diurnal cycle of convection. The second manuscript (unpublished), entitled An Improved QPE Over Complex Terrain by Using Cloud-to-Ground Lightning Occurrences, provides a new method to retrieve lightning-derived precipitation at 5 minutes and 5 Km time and space resolutions. A stationary model that employs spatio-temporal neighboring (Space and Time Invariant model -STI) improves upon the least squares method in the first paper. By applying a Kalman filter to the STI model, lightning-precipitation is retrieved by a dynamic model that changes in time. The results for seasonal and 5 minutes time resolution show that the dynamic model improves the retrievals derived by the STI model.