Within this Master’s thesis, design and construction of a strapdown inertial navigation system based on MEMS sensors is described. The thesis includes theoretic analysis of physics behind determining the position of an object based on the object’s aceleration and changes in the object’s orientation in space. Included is also an overview of mathematical methods related to the position calculation.

The modern attention economy incentivizes the use of persuasive designs in software development. Scrolling is an interaction technique commonly associated with persuasive designs because of its lack of natural stopping cues and potential for habit promotion. A scroll-like interaction is used in gesture navigation, which is a method of navigating mobile operating systems. This paper investigates gesture navigation in mobile operating systems in the context of persuasive designs. The aim of this paper is to answer whether gesture navigation affects mobile usage and if there is a systematic preference for gesture navigation over traditional button navigation. In order to answer these questions a pre-post study was conducted. The participants were instructed to change system navigation controls for ten days; whereafter data regarding their mobile usage was collected. The collected data was analyzed in order to determine if there was a difference in mobile usage after changing system navigation controls and whether there was a systematic preference for gesture navigation. The results did not suggest that gesture navigation has an effect on mobile usage. The results did however point towards a systematic preference for gesture navigation over button navigation. The idéa of a systematic preference for gesture navigation motivates further research about the mechanisms behind it. / Den moderna uppmärksamhets-ekonomin motiverar implementering av persuasive design-tekniker inom mjukvaruutveckling. Scrolling är en interaktionsteknik som ofta förknippas med persuasive design på grund av dess brist på naturliga stoppsignaler och förmåga att forma användarvanor. En scrolling-liknande interaktion används i gestnavigering, vilket är en navigeringsmetod i mobila operativsystem. Denna uppsats undersöker gestnavigering i mobila operativsystem i anknytning till persuasive design. Syftet med uppsatsen är att besvara om gestnavigering påverkar mobilanvändning och om det finns en systematisk preferens för gestnavigering framför traditionell knappnavigering. För att besvara dessa frågor genomfördes en inventionsstudie. Deltagarna instruerades att ändra systemnavigering i tio dagar; varefter data om deras mobilanvändning samlades in. De insamlade uppgifterna analyserades för att avgöra om det förekom någon skillnad på mobilanvändandet efter bytet av systemnavigering och om det fanns en systematisk preferens för gestnavigering. Resultaten tydde inte på att gestnavigering påverkar mobilanvändning. Resultaten pekade däremot på en systematisk preferens för gestnavigering framför knappnavigering. Idén om en systematisk preferens för gestnavigering motiverar vidare forskning om preferensens bakomliggande mekanismer.

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Диссертационная работа посвящена проблеме привлечения детей и подростков к занятиям спортом в школе олимпийского резерва, а также привлечению людей всех возрастов к активному образу жизни. Исследование включает анализ методов творческого мышления для их дальнейшего использования в проектной части работы. В диссертации рассмотрены различные существующие дизайнерские решения в сфере спорта и проведен анализ эффективности их воздействия на целевую аудиторию. Были подведены итоги и сделаны выводы о проделанном исследовании. / The dissertation work is dedicated to the problem of attracting children and adolescents to go in for sports at the School of the Olympic reserve as well as attracting people of all ages to maintain a healthy lifestyle. The study includes an analysis of creative thinking methods for their further use in the practical design part of the work. Various existing design solutions in the field of sports are reviewed, the effectiveness of their impact on the target audience is analyzed. The results of the study were summed up and conclusions were drawn.

A*(A-Star)演算法透過啟發函式，以減少路徑搜尋過程中所需要計算的網路數量，SMA*(Simplified Memory Bounded A-Star)為A*之變形，目前最廣泛被應用於GPS導航系統之路徑規劃的演算法。尋找路徑的計算過程中，A*與SMA*演算法利用中間節點與目的地的方向(直線距離)作為啟發函式，以預估中間節點到目的地之路徑長度挑選優先搜尋的路段，而SMA*則因記憶體的限制會排除預估長度較長的路段，以減少搜尋的路段數量與記憶體之使用量。當起點與終點中存在障礙地形時或路段較崎嶇時，以方向導引路徑搜尋之準確度便大幅降低，導致A*與SMA*之搜尋數量增加，SMA*甚至會得到較差的路徑。 主幹導引式最短路徑搜尋演算法(Backbone Orientation)以骨幹路徑導引路徑之搜尋，在障礙地形或道路崎嶇的情況下，可有效避免SMA*之缺點，效能較佳。主幹導引式最短路徑搜尋演算法分為二階段，先由原始路網中提取骨幹路網，並計算出最佳骨幹路徑，再利用骨幹路徑引導路徑的搜尋，在骨幹路徑的一定範圍內搜尋最短路徑。 本研究以台灣地區2007年之平面路網圖進行實驗，以三種不同的實驗方式進行實驗，以驗證主幹導引式最短路徑搜尋演算法之效能，證明在SMA*演算法之啟發函式效能低落時，使用主幹導引式最短路徑搜尋演算法可以有效的改善SMA*在障礙地形之效能不彰的問題。

Neste trabalho, é abordado o problema da navegação de um veículo submarino autônomo. São propostos estimadores de estado que realizam fusão sensorial baseada em Filtro Estendido de Kalman. Esses estimadores de estado empregam as medidas dos seguintes sensores: uma unidade de medição inercial, um sensor de velocidade por efeito Doppler, um profundímetro e uma bússola. Primeiramente foi projetado um estimador de estados para o AUV Pirajuba, onde a estimação da orientação do veículo é realizada de forma desacoplada à estimação da velocidade e posição do veículo. Em seguida, foram desenvolvidos dois estimadores de estado que estimam orientação, velocidade e profundidade do veículo de forma acoplada. Para o projeto e testes dos estimadores mencionados anteriormente, foi empregada uma base de dados contendo um registro de medições reais dos sensores do veículo submarino autônomo Pirajuba, durante testes de campo no lago de uma represa. Os resultados dos testes validaram os estimadores de estado propostos nesse trabalho. Por último, foi realizada uma análise comparativa dos estimadores de estado mencionados. / This work concerns the navigation problem of an autonomous underwater vehicle. Some state estimators using sensorial fusion were proposed, the sensorial fusion is based in an Extended Kalman Filter. The state estimators are fed by measurements of the following sensors: an inertial measurements unit, a velocity sensor by Doppler effect, a depthmeter and a compass. In the first version of the EKF algorithm, the vehicles attitude estimation was decoupled from the vehicle velocity estimation. The second version considers the coupling between linear velocity and the attitude in the vehicle reference frame, taking the velocity reading for correction of the filter estimates. Finally, in the third version, the coupling between position and attitude is also considered, but the correction of the filters estimates is based on the depth readings. Experiments for supporting the design and validation of the navigation algorithms were based on a database constructed with motion measurements during the AUV maneuvers in the north coast of Sao Paulo, and the Guarapiranga lake in the São Paulo city. This work presents a comparative analysis of those algorithms.

This thesis deals with the new unconventional way of agricultural land management. Currently, high precision of work machines in the field is required. The development and accessibility of modern agricultural equipment linked to the information technology has led this branch to the unnecessary and high precise field ecosystem management. This new approach is called as precision agriculture. In the theoretical part of work is made the literature research and overview of the available data about the precision farming methods and the possibilities of field observation and data collection, including their processing with the available high information technology. The practical part evaluates the current possibilities of precision farming in the Czech Republic and in the world and looks for a solution to its implementation in the specific business environment of the agricultural laboratory.

The aim of this thesis is to write a multisensor navigation algorithm and to design a test setup. After doing these, test the algorithm by using the test setup. In navigation, dead reckoning is a procedure to calculate the position from initial position with some measured inputs. These measurements do not include absolute position data. Using only an inertial measurement unit is an example for dead reckoning navigation. Calculating position and velocity with the inertial measurement unit is highly erroneous because, this calculation requires integration of acceleration data. Integration means accumulation of errors as time goes. For example, a constant acceleration error of 0.1 m/s^2 on 1 m/s^2 of acceleration will lead to 10% of position error in only 5 seconds. In addition to this, wrong calculation of attitude is going to blow the accumulated position errors. However, solving the navigation equations while knowing the initial position and the IMU readings is possible, the IMU is not used solely in practice. In literature, there are studies about this topic and in these studies / some other sensors aid the navigation calculations. The aiding or fusion of sensors is accomplished via Kalman filter. In this thesis, a navigation algorithm and a sensor fusion algorithm were written. The sensor fusion algorithm is based on estimation of IMU errors by use of a Kalman filter. The design of Kalman filter is possible after deriving the mathematical model of error propagation of mechanization equations. For the sensor fusion, an IMU, two incremental encoders and a digital compass were utilized. The digital compass outputs the orientation data directly (without integration). In order to find the position, encoder data is calculated in dead reckoning sense. The sensor triplet aids the IMU which calculates position data by integrations. In order to mount these four sensors, an unmanned tracked vehicle prototype was manufactured. For data acquisition, an xPC&ndash / Target system was set. After planning the test procedure, the tests were performed. In the tests, different paths for different sensor fusion algorithms were experimented. The results were recorded in a computer and a number of figures were plotted in order to analyze the results. The results illustrate the benefit of sensor fusion and how much feedback sensor fusion is better than feed forward sensor fusion.

Inertial navigation systems (INSs) have the well-known advantages of being self-contained, weatherproof, jam-proof, and non-self-revealing while providing stable navigation information with little high-frequency noise. However, their single most important drawback is the growth of their error cumulatively with time in an unbounded manner. Navigation systems based on position fixing, in contrast, offer bounded errors in the long term, but their output is usually contaminated with strong high-frequency noise. To harness the advantages of both types of systems, INSs have been traditionally aided or augmented by one or more fixing system(s). Such an arrangement preserves the excellent short-term stability and damping (i.e. high-frequency rejection) capability of INSs while limiting its long-term drift. In recent years, the availability of navigation information from the Global Positioning System (GPS) reliably and accurately over the entire globe has made it a natural choice as the means of augmentation of INSs. An integrated navigation system combining data from two or more ‘pure’systems is called a hybrid navigation system (HNS). There is no unique way of combining navigation information from the INS and GPS. Depending on the goals and specifications of the overall navigation system, the instrument and equipment available, cost constraints, and technology options, the scheme for integrating INS and GPS may take one of many forms. In generic terms integration of diverse ‘pure’ navigation systems can be performed at various levels. At the simplest and most basic level, each system may be allowed to run independently, generating its own navigation data separately which may then be combined periodically to reset any accumulated error. At the other extreme, the two (or more) systems may be intimately coupled right at their raw data levels in a quasi-continuous manner with the intention of maximising their mutually beneficial effect and deriving the ‘best’ possible navigation information. Hybrid navigation architectures have been a subject of much research and development, and a significant body of information is available on the subject. However, there are clear gaps in open literature on many practical issues that arise in the context of implementing specific HNSs. In this thesis we investigate the architecture, implementation and performance issues of HNSs that combine stand-alone INS and GPS units. The thesis consists of eight chapters. The first chapter offers an introduction to the navigation problem and discusses the basic types of navigation including inertial and satellite navigation. Inertial sensors such as gyroscopes and accelerometers and the GPS are discussed in some detail. The types and principle of gyroscopes and accelerometers and the error sources in inertial navigation are briefly covered, as also the advantages and disadvantages of INS and the trends in inertial system development.The chapter also touches upon GPS segments (space, control and user), the theory and determination of position fix, and the GPS error sources. Mention is also made of the types of GPS receiver available and the trends in GPS technologies. Integration of INS and GPS and its benefits are discussed and a set of specifications for an integrated system is laid out to serve as the basis for the configurations proposed later. The second chapter, in its three sections, provides a summary of the significant literature relevant to INS and GPS in the context of their integration. Chapter three discusses mechanisation aspects of the INS-GPS hybrid navigation system. This chapter is divided into three sections. In the first section the frames of reference, INS mechanisation and the error equations are discussed. The definitions for the various frames such as body, platform, local level, geodetic, Earth-centred-Earth-fixed (ECEF), and the computer frame are mentioned along with the direction cosine matrices for the transformation of frames. In the second section various types of mechanisation of INS and the summary of tilt, velocity and position equations are described. The INS can be mechanised in two ways: the stable platform and the strap-down. In this chapter the general error equations for platform tilt, velocity and position are listed. Platform-based systems can be mechanized as one of the following types, viz. unipolar, Focualt, north pointing and wander azimuth. The definitions and summary of the tilt, velocity and position, and the error equations are given for all these types of mechanization. The accelerometer and gyro error models are discussed. It is pointed out that inclusion of all the possible INS states in the model would lead to a 45-state system which would be too complex to handle on board. The scope for reduction of model order and the effect of such reduction are brought out. The section ends with a summary of the INS error equations considered for implementation. In the third section the GPS principle and derivation of navigation solutions based on GPS measurements are dealt with. GPS error modelling, computation of DOP (dilution of precision), and clock modelling are also discussed. In this section the navigation solution for various classes of users – stationary, low-dynamics, medium-dynamics and high-dynamics – are discussed. The INS model and the clock model defined in this chapter are used in configuring the integrated system model later. Chapter four discusses the various HNS configurations and their implementation to mitigate the INS error. Three levels of integration are considered: a. Output coupled: The INS needs initial alignment during which the INS position and velocity are initialised with the precisely known co-ordinates and components at the starting location. Starting with these initial conditions, the INS-sensed accelerations are continuously integrated to yield the current velocity and position. As mentioned earlier, the INS error is dependent on this initial value and further increases with time. If the initial position and velocity inputs are precise, the short-term INS accuracy (typically for the first 10-15 minutes in case of aircraft) is usually within acceptable limits. Further error built up during longer flights can be reduced by periodic updation of INS with the precise position and/or velocity values. To achieve this the pilot may, for example, fly over waypoints whose co-ordinates are precisely known. This would constitute a physical or manual method of INS re-initialisation. A better and more modern method is to use precise GPS-derived information to reinitialise the INS periodically and automatically. b. Medium coupled: Another way of mitigating the INS error build-up is by using medium-coupled HNS wherein the INS errors are estimated using the GPS measurements as reference. The INS outputs are corrected by applying these error estimates. The important point to note here is that in medium coupling, the errors in the INS states are considered instead of the states themselves. The final geodetic outputs from the two systems are used as measurements. A twelve-state indirect feed-forward Kalman filter is used to estimate the INS position error. c. Tightly coupled: The basic measurements from the GPS are pseudoranges which are the distances from the user to the GPS satellites. By making a minimum of four such measurements the GPS receiver computes the user location in the geodetic coordinates. Conversely, knowing the user position from INS, it is possible to calculate the expected pseudoranges to known GPS satellite locations. Comparing the measured and the computed pseudoranges, the filter estimates the errors in the INS position. In this work a seventeen-state, feed-forward, indirect Kalman filter is configured to estimate the INS-derived pseudorange errors. These errors are then translated into positional errors which are used to correct the indicated INS positions. In configuring the filter it is assumed that the INS and GPS are physically separated and data transfer is through the interface buses. In this chapter the simulators used for validation and performance estimation of the configurations are also described. Two simulators are used to validate the hybrid system, namely, software-and hardware-based simulators. The simulators simulate the six-degree-of-freedom of trajectory generator, and error models of INS and GPS. The truth data from the trajectory generator are combined with the INS error and GPS error to get the INS and GPS outputs respectively. The fifth and sixth chapters covers the validation of the above-mentioned three configurations. Since analysis of output coupled systems is rather straightforward, simulation and validation of the configuration are carried out for the medium and tightly coupled systems Covariance analysis and Error analysis modes of simulation are carried out to study and validate the behaviour of the configurations. In covariance analysis one obtains the root mean square (rms) value of the errors obtained from several Monte Carlo runs. It gives an estimate of the lower bound of the system errors. Covariance simulation provides a degree of confidence in the error model but is generally not sufficient to expose the complete behaviour of the system. For detailed investigation, error simulation needs to be carried out for the entire navigation system. In the thesis, covariance simulation is carried out for both the configurations to check the sensitivity of the system to measurement update rates, process noise, update times for the transition matrix, and also for the validity of the truncation of the Taylor series expansion. The details of the simulation processes and their results are discussed in these chapter. The seventh chapter makes a performance comparison of the configurations and draws inferences for practical hybrid system implementation. From the comparisons it is seen that the loosely coupled configuration is the simplest. In this configuration there is no requirement of the Kalman filter. The accuracy depends on the update rate. If the position update is made, for example, once every 600 s then the error in the combined system will be limited to the sum of the error due to the GPS and that accumulated in the INS alone over the of 600 s interval. There is no coordinate transformation required. In the case of medium coupled filter the addition of process noise to the GPS clock model is not critical. The position accuracy achieved is around 2 m (rms). The coordinate transformations are only from the body to platform, and platform to geodetic axes. The observation matrix is very simple in this case and the computation burden is low. Dynamic tuning of the measurement matrix is not required in real time.In the case of tightly coupled configuration the addition of a certain amount of process noise deliberately to the GPS clock model is critical. The position accuracy achieved with tight coupling is around found to be 34 m (rms) without the addition of process noise. On addition of a controlled amount of noise to the GPS clock bias and clock drift states and inclusion of measurement noise as a function of GPS signal strength, the position accuracy improves significantly, to about 7m (rms). Figures 2a and 2b below depict the behaviour before and after inclusion of the noise. The coordinate transformations are from body to platform, platform to geodetic, and geodetic to ECEF coordinates, and vice versa. The observation matrix (H) for this integration model is very complicated, and the computational burden is very high. In this configuration H transfers the measurements from metres to radians. Dynamic tuning of measurement matrix is required in this case. Chapter eight of the thesis summarises the results and lists out the conclusions arrived at from the study. It also includes a section with suggestions for future work in this direction.

Autonomous land vehicles (ALVs) have received considerable attention after their introduction into military and commercial applications. ALVs still stand as a challenging research topic. One of the main problems arising in ALV operations is the navigation accuracy while the other is the dynamic effects of road irregularities which may prevent the vehicle and its cargo to function properly. In this thesis, we propose intelligent solutions to these two basic problems of ALV. First, an intelligent method is proposed to enhance the performance of a coupled global positioning/inertial navigation system (GPS/INS) for land navigation applications during the GPS signal loss. Our method is based on using an artificial neural network (ANN) to intelligently aid the GPS/INS coupled navigation system in the absence of GPS signals. The proposed enhanced GPS/INS is used in the dynamic environment of a tour of an autonomous van and we provide the results here. GPS/INS+ANN system performance is thus demonstrated with the land trials. Secondly, our work focuses on the identification and enlargement of the stability region of the ALV. In this thesis, the domain of attraction of the ALV is found to be patched by chaotic and regular regions with chaotic boundaries which are extracted using novel technique of cell mapping equipped with measures of fractal dimension and rough sets. All image cells in the cellular state space, with their individual fractal dimension are classified as being members of lower approximation (surely stable), upper approximation (possibly stable) or boundary region using rough set theory. The obtained rough set with fractal dimension as its attribute is used to model the uncertainty of the regular regions. This uncertainty is then smoothed by a reinforcement learning algorithm in order to enlarge regular regions that are used for chassis control, critical in ALV in preventing vibration damages that can harm the payload. Hence, we will make ALV work in the largest safe area in dynamical sense and prevent the vehicle and its cargo.