The goal of this work is to navigate through an office environmentsusing only visual information gathered from four cameras placed onboard a mobile robot. The method is insensitive to physical changes within the room it is inspecting, such as moving objects. Forward and rotational motion vision are used to find doors and rooms, and these can be used to build topological maps. The map is built without the use of odometry or trajectory integration. The long term goal of the project described here is for the robot to build simple maps of its environment and to localize itself within this framework.

In this paper we examine the need of navigational aids when designing interfaces for e-newspapers – newspapers presented on a digital paper built on E-Ink technology. By reviewing literature on navigation, and by handling input from both newspaper designers and potential e-newspaper adopters, we have suggested a number of navigational aids for the future e-newspaper. Our suggestions have been tested through a prototype using a modification of the Cooperative Usability Testing model (CUT) on a total of fifteen potential users. The results show that most users prefer a linear organization of the e-newspaper. To render a sense of depth in this flat medium, page-numbering is essential. Several different interaction possibilities will also be needed to ease the navigation and our suggestions include a blend of page-turning and hyper linking, combined with an index to give the user a better overview of the content.

Background: In Sri Lanka, motherhood within marriage is highly valued. Sex out of wedlock is socially unacceptable and can create serious public health problems such as illegal abortions, suicide and infanticide, and single motherhood as a result of premarital sex is considered shameful. The way unmarried women facing single motherhood reflect on and make use of their agency in their social environments characterised by limited social and financial support has consequences for the health and well-being of both themselves and their children. The aim of this study was to explore and describe how unmarried women facing single motherhood in Sri Lanka handle their situation. Methods: This qualitative study comprised semi-structured interviews with 28 unmarried pregnant women or single mothers. The data were analysed by qualitative content analysis and the results related to the conceptual framework of social navigation. Results: The women facing single motherhood expressed awareness of having trespassed norms of sexuality through self-blame, victimhood and obedience, and by considering or attempting suicide. They demonstrated willingness to take responsibility for becoming pregnant before marriage by giving the child up for adoption, bringing up the child themselves, claiming a father for their child, refraining from marriage in the future, permanently leave their home environment, and taking up employment. Throughout the interviews, the women expressed fear of shame, and striving for familial and societal acceptance and financial survival. Conclusions: A social environment highly condemning of unmarried motherhood hindered these women from making strategic choices on how to handle their situation. However, to achieve acceptance and survival, the women tactically navigated norms of femininity, strong family dependence, a limited work market, and different sources of support. Limited access to resources restricted the women's sexual and reproductive health and rights, including their ability to make acceptable and healthy choices for themselves and their children.

The ability to navigate with limited vision is a skill that is often employed in our daily lives. Navigating without vision to a remembered target has previously been studied. However, not much is known about the attention required to perform blind navigation. We examined the effect of aging and presence of obstacles on the attentional demands of blind navigation. We evaluated reaction time, navigation errors and average walking speed in an 8 meter walking path, with or without obstacles, in the absence of vision. Results showed that older participants had increased reaction time and increased linear distance travelled as opposed to young participants, that obstacles increased reaction time and decreased average walking speed in all participants, and that emitting the reaction time stimulus early in the trial increased the linear distance travelled. Interpretation of the results suggests that aging and presence of obstacles augments the attentional demands of blind navigation.

Understanding human spatial cognition and behaviour is not something easily studied. Many factors are involved that contribute in different ways for different individuals. Navigation and wayfinding have been used as an approach, or starting point, for such studies. Spatial abilities tests have long been used as reference points to generalize to overt navigational behaviour. Care needs to be taken in generalizing from paper to behaviour to make certain that it is a valid relationship exists.<p>The purpose of this study was to examine the extent to which certain psychometric spatial abilities tests are indicators of actual navigational decision making. The study was conducted in two phases. The navigational decision tasks were made up of four paths with two variables: length and number of turns. The participants were required to make a decision on which direction to go after being lead part of the way around a hallway. The choices were to either go back the way they were led or take a novel route along a previously un-travelled path (shortcut). Spatial abilities tests (MRT, PFT, and OLMT), a self-rating of SOD, and learning preference for novel environments were administered in phase two. <p>While efficient navigation was not explicitly required in the navigation tasks those participants making the most efficient decisions shared similar characteristics. Efficient navigators have a higher aptitude for mental manipulation (as measured by the MRT), express a preference for a more exploratory environmental learning style, are disproportionately male, and have a slightly higher self-rating of SOD. In addition to the collective set of four navigation decisions (one for each experimental path), path 2 demonstrated the efficient vs. non-efficient distinction quite well: in order to make the most efficient decision the individual must maintain the correct metric distance from the origin point and not be deterred by the passage of only half of the turns in the rectangular experimental environment.

Mobile robotics research is currently interested on exporting autonomous navigation results achieved in indoor environments, to more challenging environments, such as, for instance, urban pedestrian areas. Developing mobile robots with autonomous navigation capabilities in such urban environments supposes a basic requirement for a upperlevel service set that could be provided to an users community. However, exporting indoor techniques to outdoor urban pedestrian scenarios is not evident due to the larger size of the environment, the dynamism of the scene due to pedestrians and other moving obstacles, the sunlight conditions, and the high presence of three dimensional elements such as ramps, steps, curbs or holes. Moreover, GPS-based mobile robot localization has demonstrated insufficient performance for robust long-term navigation in urban environments. One of the key modules within autonomous navigation is localization. If localization supposes an a priori map, even if it is not a complete model of the environment, localization is called map-based. This assumption is realistic since current trends of city councils are on building precise maps of their cities, specially of the most interesting places such as city downtowns. Having robots localized within a map allows for a high-level planning and monitoring, so that robots can achieve goal points expressed on the map, by following in a deliberative way a previously planned route. This thesis deals with the mobile robot map-based localization issue in urban pedestrian areas. The thesis approach uses the particle filter algorithm, a well-known and widely used probabilistic and recursive method for data fusion and state estimation. The main contributions of the thesis are divided on four aspects: (1) long-term experiments of mobile robot 2D and 3D position tracking in real urban pedestrian scenarios within a full autonomous navigation framework, (2) developing a fast and accurate technique to compute on-line range observation models in 3D environments, a basic step required by the real-time performance of the developed particle filter, (3) formulation of a particle filter that integrates asynchronous data streams and (4) a theoretical proposal to solve the global localization problem in an active and cooperative way, defining cooperation as either information sharing among the robots or planning joint actions to solve a common goal. / Actualment, la recerca en robòtica mòbil té un interés creixent en exportar els resultats de navegació autònoma aconseguits en entorns interiors cap a d'altres tipus d'entorns més exigents, com, per exemple, les àrees urbanes peatonals. Desenvolupar capacitats de navegació autònoma en aquests entorns urbans és un requisit bàsic per poder proporcionar un conjunt de serveis de més alt nivell a una comunitat d'usuaris. Malgrat tot, exportar les tècniques d'interiors cap a entorns exteriors peatonals no és evident, a causa de la major dimensió de l'entorn, del dinamisme de l'escena provocada pels peatons i per altres obstacles en moviment, de la resposta de certs sensors a la il.luminació natural, i de la constant presència d'elements tridimensionals tals com rampes, escales, voreres o forats. D'altra banda, la localització de robots mòbils basada en GPS ha demostrat uns resultats insuficients de cara a una navegació robusta i de llarga durada en entorns urbans. Una de les peces clau en la navegació autònoma és la localització. En el cas que la localització consideri un mapa conegut a priori, encara que no sigui un model complet de l'entorn, parlem d'una localització basada en un mapa. Aquesta assumpció és realista ja que la tendència actual de les administracions locals és de construir mapes precisos de les ciutats, especialment dels llocs d'interés tals com les zones més cèntriques. El fet de tenir els robots localitzats en un mapa permet una planificació i una monitorització d'alt nivell, i així els robots poden arribar a destinacions indicades sobre el mapa, tot seguint de forma deliberativa una ruta prèviament planificada. Aquesta tesi tracta el tema de la localització de robots mòbils, basada en un mapa i per entorns urbans peatonals. La proposta de la tesi utilitza el filtre de partícules, un mètode probabilístic i recursiu, ben conegut i àmpliament utilitzat per la fusió de dades i l'estimació d'estats. Les principals contribucions de la tesi queden dividides en quatre aspectes: (1) experimentació de llarga durada del seguiment de la posició, tant en 2D com en 3D, d'un robot mòbil en entorns urbans reals, en el context de la navegació autònoma, (2) desenvolupament d'una tècnica ràpida i precisa per calcular en temps d'execució els models d'observació de distàncies en entorns 3D, un requisit bàsic pel rendiment del filtre de partícules a temps real, (3) formulació d'un filtre de partícules que integra conjunts de dades asíncrones i (4) proposta teòrica per solucionar la localització global d'una manera activa i cooperativa, entenent la cooperació com el fet de compartir informació, o bé com el de planificar accions conjuntes per solucionar un objectiu comú.

Finding ones way in unknown and unfamiliar environments is a common task. A number of tools ranging from paper maps to location-based services have been introduced to assist human navigation. Undoubtedly, car navigation systems can be considered the most successful example of location based services that widely gained user acceptance. However the concept of car navigation is not always (perhaps rarely) suitable for pedestrian navigation. Moreover, precise localization of moving objects indoors is not possible due to the absence of an absolute positioning method such as GPS. These make accurate indoor tracking and navigation an interesting problem to explore. Many of the methods of spatial analysis popular in outdoor applications can be used indoors. In particular, generation of the indoor navigation network can be an effective solution for a) improving the navigation experience inside complex indoor structures and b) enhancing the analysis of the indoor tracking data collected with existing positioning solutions. Such building models should be based on a graph representation and consist of the number of ‘nodes’ and ‘edges’, where ‘nodes’ correspond to the central position of the room and ‘edge’ represents the medial axis of the hallway polygons, which physically connects these rooms. Similar node-links should be applied stairs and elevators to connect building floors. To generate this model, I selected the campus of University of Saskatchewan as the study area and presented a method that creates an indoor navigation network using ESRI ArcGIS products. First, the proposed method automatically extracts geometry and topology of campus buildings and computes the distances among all entities to calculate the shortest path between them. The system navigates through the University campus and it helps locating classrooms, offices, or facilities. The calculation of the route is based on the Dijkstra algorithm, but could employ any network navigation algorithm. To show the advantage of the generated network, I present results of a study conducted in conjunction with the department of Computer Science. An experiment that included 37 participants was designed to collect the tracking data on a university campus to demonstrate how the incorporation of the indoor navigation model can improve the analysis of the indoor movement data. Based on the results of the study, it can be concluded that the generated indoor network can be applied to raw positioning data in order to improve accuracy, as well as be employed as a stand-alone tool for enhancing of the route guidance on a university campus, and by extension any large indoor space consisting of individual or multiple buildings.

Simultaneous Localization and Mapping (SLAM) is a technique used by robots and autonomous vehicles to build up a map while operating in an unknown environment, while at the same time keeping track of a current position estimate. This process is not as straightforward as it may sound. Due to inherent uncertainties in tracking the robot's motion and observing the world around it, errors accumulate. Incorporating External Localization (EL) sensors, such as Global Positioning System (GPS) receivers, which are not subject to the same type of drift over time, can allow a system to eliminate errors from the SLAM process. This, however, requires the system to work with measurements from both the SLAM and EL coordinate frames. Since the SLAM coordinate origin is dependent upon the vehicle's starting location, which is unknown, the relationship between it and the EL frame is unknown and must be estimated. The main contributions of this thesis arise from a novel approach to integrating EL with SLAM, by estimating a transformation between the SLAM and external reference frames. The Constrained Relative Submap Filter (CRSF) SLAM is a computationally efficient SLAM lter operates on a series of local submaps, instead of one large map, as with Extended Kalman Filter (EKF) SLAM. By integrating the transformation estimation process with CRSF SLAM, a method to correct submap locations with EL is presented. This eliminates long term estimation drift, aids in loop closing and allows for accurate map generation with a reference to an external frame.

This master thesis investigates the performance of a car navigation system using lateral accelerometers, yaw rate and bearings relative three known radio beacons. Accelerometer, gyroscope and position data has been collected by an IMU combined with a GPS receiver, where the IMU was installed in the approximate motion center of a car. The bearing measurements are simulated using GPS data and the measurement noise model is derived from an experiment where the direction of arrival to one transmitter was estimated by an antenna array and the signal processing algorithm MUSIC. The measurements are fused in a multi-rate extended Kalman filter which assumes that all measurement noise is Gaussian distributed. This is not the case for the bearing measurement noise which contains outliers and therefore is modelled as a Gaussian uniform noise mixture. Different methods to deal with this have been investigated where the main focus is on the principle to use the Kalman filter’s innovation for each bearing measurement as an indication of its quality and discarding measurements with a quality above a certain threshold.

A general automotive navigation system is a satellite navigation system designed for use inautomobiles. It typically uses GPS to acquire position data to locate the user on a road in the unit's map database. However, due to recent improvements in the performance of small and lightweight micro-machined electromechanical systems (MEMS) inertial sensors have made the application of inertial techniques to such problems, possible. This has resulted in an increased interest in the topic of inertial navigation. In location tracking system, sensors are used either individually or in conjunction like in data fusion. However, still they remain noisy, and so there is a need to measure maximum data and then make an efficient system that can remove the noise from data and provide a better estimate. The task of this thesis work was to take data from two sensors, and use an estimation technique toprovide an accurate estimate of the true location. The proposed sensors were an accelerometer and a GPS device. This thesis however deals with using accelerometer sensor and using estimation scheme, Kalman filter. The thesis report presents an insight to both the proposed sensors and different estimation techniques. Within the scope of the work, the task was performed using simulation software Matlab. Kalman filter’s efficiency was examined using different noise levels.