Thesis (M.A.) - Carleton University, 2007. / Includes bibliographical references (p. 160-168). Also available in electronic format on the Internet.

Thesis (M.A.)--Carleton University, 2001. / Includes bibliographical references. Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Idaho, 2005. / Also available online in PDF format. Abstract. "August 2005." Includes bibliographical references.

Thesis (M. G. I. S.)--University of Hong Kong, 2005. / Title proper from title frame. Also available in printed format.

Mobile phones are increasingly being equipped with a wide range of sensors which enable a variety of interaction techniques. Sensor-based interaction techniques are particularly promising for domains such as map-based applications, where the user is required to interact with a large information space on the small screen of a mobile phone. Traditional interaction techniques have several shortcomings for interacting with mobile map-based applications. Keypad interaction offers limited control over panning speed and direction. Touch-screen interaction is often a two-handed form of interaction and results in the display being occluded during interaction. Sensor-based interaction provides the potential to address many of these shortcomings, but currently suffers from several limitations. The aim of this research was to propose enhancements to address the shortcomings of sensor-based interaction, with a particular focus on tilt interaction. A comparative study between tilt and keypad interaction was conducted using a prototype mobile map-based application. This user study was conducted in order to identify shortcomings and opportunities for improving tilt interaction techniques in this domain. Several shortcomings, including controllability, mental demand and practicality concerns were highlighted. Several enhanced tilt interaction techniques were proposed to address these shortcomings. These techniques were the use of visual and vibrotactile feedback, attractors, gesture zooming, sensitivity adaptation and dwell-time selection. The results of a comparative user study showed that the proposed techniques achieved several improvements in terms of the problem areas identified earlier. The use of sensor fusion for tilt interaction was compared to an accelerometer-only approach which has been widely applied in existing research. This evaluation was motivated by advances in mobile sensor technology which have led to the widespread adoption of digital compass and gyroscope sensors. The results of a comparative user study between sensor fusion and accelerometer-only implementations of tilt interaction showed several advantages for the use of sensor fusion, particularly in a walking context of use. Modifications to sensitivity adaptation and the use of tilt to perform zooming were also investigated. These modifications were designed to address controllability shortcomings identified in earlier experimental work. The results of a comparison between tilt zooming and Summary gesture zooming indicated that tilt zooming offered better results, both in terms of performance and subjective user ratings. Modifications to the original sensitivity adaptation algorithm were only partly successful. Greater accuracy improvements were achieved for walking tasks, but the use of dynamic dampening factors was found to be confusing. The results of this research were used to propose a framework for mobile tilt interaction. This framework provides an overview of the tilt interaction process and highlights how the enhanced techniques proposed in this research can be integrated into the design of tilt interaction techniques. The framework also proposes an application architecture which was implemented as an Application Programming Interface (API). This API was successfully used in the development of two prototype mobile applications incorporating tilt interaction.

This thesis addresses the problem of computationally estimating the motion of pack ice in sequential digital satellite images. The problem is posed in terms of linear filter theory and is solved by minimizing the error variance. The intuitive use of cross correlation and edge detection are shown to flow naturally from this approach. The theoretical framework also allows a geometric intuition into the action of the filter which is not possible through ad hoc methods. The noise corrupting the filtering process is investigated and the filter is implemented through both a first order method common to image processing, and a more sophisticated second order approach from computational vision. The class of imagery for which the filtering system is appropriate is discussed and the images chosen for the experiments are shown to be representative of this class. The experimental results reveal the power of the system in estimating ice motion, and some analysis of the derived motion is performed by comparison to a simple theory of wind-driven ice motion. The failings of the system are discussed and improvements are suggested. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

Manual digitizing has been recognized by investigators as a significant source of map error in GIS, but the error characteristics have not been well defined. This thesis presents a methodology for simulating manual digitizing error. Stream mode digitizing error was modeled using autoregressive moving average (ARMA) procedures, and point mode digitizing was stochastically simulated using an uniform random model. These models were developed based on quantification of digitizing error collected from several operators. The resulting models were used to evaluate the effect digitizing error had upon polygon size and total line length at varying map accuracy standards. Digitizing error produced no bias in polygon area. The standard deviation of polygon area doubled as the accuracy standard bandwidth doubled, but the standard deviation was always less than 1.6 percent of total area for stream mode digitizing. Smaller polygons (less than 10 square map inches) had more bias and more variance relative to their size than larger polygons. A doubling of the accuracy standard bandwidth caused a quadrupling of line length bias and a doubling to tripling of the line length standard deviation. For stream mode digitizing, reasonable digitizing standards produced line length biases of less than 2 percent of total length and standard deviations of less than 1 percent of total length. Bias and standard deviation both increased with increasing line length (or number of points), but the bias and standard deviation as a percent of total line length remained constant as feature size changed. / Master of Science

Thesis (M.S.) -- Mississippi State University. Department of Geosciences. / Title from title screen. Includes bibliographical references.

Call number: LD2668 .T4 1985 H33 / Master of Landscape Architecture

Thesis (MSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: In this thesis we consider the problem of building a dense and consistent map of a mobile robot’s environment that is updated as the robot moves. Such maps are vital for safe and collision-free navigation. Measurements obtained from a range sensor mounted on the robot provide information on the structure of the environment, but are typically corrupted by noise. These measurements are also relative to the robot’s unknown pose (location and orientation) and, in order to combine them into a world-centric map, pose estimation is necessary at every time step. A SLAM system can be used for this task. However, since landmark measurements and robot motion are inherently noisy, the pose estimates are typically characterized by uncertainty. When building a map it is essential to deal with the uncertainties in range measurements and pose estimates in a principled manner to avoid overconfidence in the map. A literature review of robotic mapping algorithms reveals that the occupancy grid mapping algorithm is well suited for our goal. This algorithm divides the area to be mapped into a regular lattice of cells (squares for 2D maps or cubes for 3D maps) and maintains an occupancy probability for each cell. Although an inverse sensor model is often employed to incorporate measurement uncertainty into such a map, many authors merely state or depict their sensor models. We derive our model analytically and discuss ways to tailor it for sensor-specific uncertainty. One of the shortcomings of the original occupancy grid algorithm is its inability to convey uncertainty in the robot’s pose to the map. We address this problem by altering the occupancy grid update equation to include weighted samples from the pose uncertainty distribution (provided by the SLAM system). The occupancy grid algorithm has been criticized for its high memory requirements. Techniques have been proposed to represent the map as a region tree, allowing cells to have different sizes depending on the information received for them. Such an approach necessitates a set of rules for determining when a cell should be split (for higher resolution in a local region) and when groups of cells should be merged (for lower resolution). We identify some inconsistencies that can arise from existing rules, and adapt those rules so that such errors are avoided. We test our proposed adaptive occupancy grid algorithm, that incorporates both measurement and pose uncertainty, on simulated and real-world data. The results indicate that these uncertainties are included effectively, to provide a more informative map, without a loss in accuracy. Furthermore, our adaptive maps need far fewer cells than their regular counterparts, and our new set of rules for deciding when to split or merge cells significantly improves the ability of the adaptive grid map to mimic its regular counterpart. / AFRIKAANSE OPSOMMING: In hierdie tesis beskou ons die probleem om ’n digte en konsekwente kaart van ’n mobiele robot se omgewing te bou, wat opgedateer word soos die robot beweeg. Sulke kaarte is van kardinale belang vir veilige, botsingvrye navigasie. Metings verkry vanaf ’n sensor wat op die robot gemonteer is, verskaf inligting rakende die struktuur van die omgewing, maar word tipies deur ruis vervorm. Hierdie metings is ook relatief tot die robot se onbekende postuur (posisie en oriëntasie) en, om hulle saam te voeg in ’n wêreldsentriese kaart, is postuurafskatting nodig op elke tydstap. ’n SLAM stelsel kan vir hierdie doeleinde gebruik word. Aangesien landmerkmetings en die beweging van die robot inherent ruiserig is, word die postuurskattings gekarakteriseer deur onsekerheid. Met die bou van ’n kaart moet hierdie onsekerhede in afstandmetings en postuurskattings op ’n beginselvaste manier hanteer word om te verhoed dat te veel vertroue in die kaart geplaas word. ’n Literatuurstudie van karteringsalgoritmes openbaar die besettingsroosteralgoritme as geskik vir ons doel. Die algoritme verdeel die gebied wat gekarteer moet word in ’n reëlmatige rooster van selle (vierkante vir 2D kaarte of kubusse vir 3D kaarte) en onderhou ’n besettingswaarskynlikheid vir elke sel. Alhoewel ’n inverse sensormodel tipies gebruik word om metingsonsekerheid in so ’n kaart te inkorporeer, noem of wys baie outeurs slegs hulle model. Ons herlei ons model analities en beskryf maniere om sensorspesifieke metingsonsekerheid daarby in te sluit. Een van die tekortkominge van die besettingsroosteralgoritme is sy onvermoë om onsekerheid in die postuur van die robot na die kaart oor te dra. Ons spreek hierdie probleem aan deur die opdateringsvergelyking van die oorspronklike besettingsroosteralgoritme aan te pas, om geweegde monsters van die postuuronsekerheidsverdeling (verskaf deur die SLAM stelsel) in te sluit. Die besettingsroosteralgoritme word soms gekritiseer vir sy hoë verbruik van geheue. Tegnieke is voorgestel om die kaart as ’n gebiedsboom voor te stel, wat selle toelaat om verskillende groottes te hê, afhangende van die inligting wat vir hulle verkry is. So ’n benadering noodsaak ’n stel reëls wat spesifiseer wanneer ’n sel verdeel (vir ’n hoër resolusie in ’n plaaslike gebied) en wanneer ’n groep selle saamgevoeg (vir ’n laer resolusie) word. Ons identifiseer teenstrydighede wat kan voorkom as die huidige reëls gevolg word, en pas hierdie reëls aan sodat sulke foute vermy word. Ons toets ons voorgestelde aanpasbare besettingsroosteralgoritme, wat beide metings- en postuuronsekerheid insluit, op gesimuleerde en werklike data. Die resultate dui daarop dat hierdie onsekerhede op ’n effektiewe wyse na die kaart oorgedra word sonder om akkuraatheid prys te gee. Wat meer is, ons aanpasbare kaarte benodig heelwat minder selle as hul reëlmatige eweknieë. Ons nuwe stel reëls om te besluit wanneer selle verdeel of saamgevoeg word, veroorsaak ook ’n merkwaardige verbetering in die vermoë van die aanpasbare roosterkaart om sy reëlmatige eweknie na te boots.