Along with the development of localization and navigation technologies, the Global Positioning System (GPS) plays an important role in our daily life, but it is confined in outdoor environments. The technology of human localization has been developed in recent years. This technology utilizes sensors to determine the movement of human and measure the distance of walking, which is not only used to solve the problem of GPS out-of-lock, but also used for the indoor localization. This thesis describes a human step-length recognition and real-time localization base on an embedded system. The goal of this system is to develop a gait pattern classification and pedestrian dead reckoning (PDR) method for human localization. Through the information of an Inertial Measurement Unit (IMU) and two force sensors mounted on a shoe, the wireless transmission module is used to send data of sensors to an embedded platform. Then the functions of step detection, step length estimation and gait pattern recognition can be achieved. According to coordinate transformation and the ZUPT algorithm, the accumulated error of velocity can be corrected. The dead reckoning method is used to obtain the information of location. Finally, the information of human location and gait patterns is sent to the Android system for remote monitoring.

<p>In order to detect movements and vibrations on different appliance, especially robots and self-going devices are used different sensors. One of the most used movement sensors are accelerometers. They are three different types of accelerometers one-axes, two-axes and three-axes. They can be analogue or digital. Husqvarna AB uses an accelerometer to detect movements of their self-going lawnmower Automower. Since it begins to turn up others sensors on the market and the sensor which today uses in Husqvarna’s lawnmower don’t fulfils all functions there is a need to find other solutions. What sensors can be found on a market and which new has come? How can they be used best and which difference is between them? How can they use to detect movements in x, y and z direction and how can they read different movements to detect collision, inclination and lift? Sensor analysis will be done to find out how they can be used in this matter and an big analysis will be done to find out how a sensor witch already is in a lawnmower can be use on the better ways?</p> / <p>För att kunna detektera rörelse och vibrationer på olika anordningar och framförallt robotar och självgående maskiner används olika sensorer. En av de mest använda rörelsesensorer är accelerometer. Det finns en uppsjö av olika utföringar som kan vara med en axel, två axlar eller tre axlar. Accelerometrar finns som digitala eller analoga. Husqvarna AB använder en sådan sensor för att detektera rörelse på sin självgående gräsklippare Automower. Eftersom det börjar dyka upp andra sensorer på marknaden och den sensor som används idag uppfyller inte alla funktioner finns det behov av att lägga tid på att se vad kan åstadkommas med en sådan sensor. Vilka sensorer kan hittas på marknaden och vilka nya har dykt upp? Hur kan de användas på bästa sätt och vad skiljer de åt? Hur kan de användas för att detektera rörelse i x, y, z-led och hur kan de läsa av olika rörelse för att detektera krock, lutning och lyft? Det skall göras analys för att se hur olika sensorer reagerar och hur kan de användas på bästa sätt. Det skall utforskas hur den sensor som redan sitter kan användas på ett bättre sätt.</p>

Methodologies are proposed for combining carrier-phase differential GPS (CDGPS), visual simultaneous localization and mapping (SLAM), and inertial measurements to obtain precise and globally-referenced position and attitude estimates of a rigid structure connecting a GPS receiver, a camera, and an inertial measurement unit (IMU). As part of developing these methodologies, observability of globally-referenced attitude based solely on GPS-based position estimates and visual feature measurements is proven. Determination of attitude in this manner eliminates the need for attitude estimates based on magnetometer and accelerometer measurements, which are notoriously susceptible to magnetic disturbances. This combination of navigation techniques, if coupled properly, is capable of attaining centimeter-level or better absolute positioning and degree-level or better absolute attitude accuracies in any space, both indoors and out. Such a navigation system is ideally suited for application to augmented reality (AR), which often employs a GPS receiver, a camera, and an IMU, and would result in tight registration of virtual elements to the real world. A prototype AR system is presented that represents a first step towards coupling CDGPS, visual SLAM, and inertial navigation. While this prototype AR system does not couple CDGPS and visual SLAM tightly enough to obtain some of the benefit of the proposed methodologies, the system is capable of demonstrating an upper bound on the precision that such a combination of navigation techniques could attain. Test results for the prototype AR system are presented for a dynamic scenario that demonstrate sub-centimeter-level positioning precision and sub-degree-level attitude precision. This level of precision would enable convincing augmented visuals. / text

Robotar är en självklar del av modern automation och produktion. Användningsområdenaär många och innefattar bland annat repetitiva arbetsuppgifter ochuppgifter som kan vara hälsofarliga för oss människor, så som t.ex. målning,punktsvetsning och materialhantering. Ett problem inom robotik är att noggrant skatta position och orientering för robotensverktyg. Detta examensarbete syftar till att ta fram metoder för dennaskattning baserad på mätningar från en Inertial Measurement Unit (IMU) sommonteras vid robotens verktyg. En IMU är en kombinationsenhet som består av flera sensorer, vanligtvis accelerometeroch gyroskop. Enheten mäter då acceleration och rotationshastighetbaserat på kroppars tröghet. Examensarbetet presenterar tre metoder för att skatta position och orienteringav robotens verktyg. En skattningsmetod endast är baserad på mätningar frånIMU:n, död räkning, samt två filter där även robotkinematiken tillsammans meduppmätta motorvinklar används, extended Kalmanfilter (EKF) och komplementärfilter(CF). Resultat för skattningsmetoderna visas för experimentell data från en högpresterandeIMU tillsammans med en industrirobot med sex frihetsgrader. / Industrial robots have a well established part within modern automation and production.The uses for robots are many and include e.g. repetitive tasks, painting, spot welding and material handling. One problem in robotics is to sufficiently well estimate the position and orientation for the end effector of the robot. This thesis aims to present estimationmethods based on data from an Inertial Measurement Unit (IMU) mounted onthe end effector of the robot. An IMU is a combination unit typically containing accelerometers and gyroscopes.The unit measures acceleration and rotational speed based on the inertia of bodies. The thesis presents three methods for position and orientation estimation. One based exclusively on IMU data, dead reckoning, and two filters based on IMUdata in combination with robot kinematics and motor angles, extended Kalmanfilter (EKF) and complementary filter (CF). Results for the estimation methods are shown based on experimental data froma high-performance IMU and a industrial robot with six degrees of freedom.

In this thesis a quadrotor is studied and a linear model is derived using grey-box estimation, a discipline in system identification where a model structure based on physical relations is used and the parameters are estimated using input-output measurements. From IMU measurements and measured PWM signals to the four motors, a direct approach using the prediction-error method is applied. To investigate the impact of the unknown controller the two-stage method, a closed-loop approach in system identification,  is applied as well. The direct approach was enough for estimating the model parameters. The resulting model manages to simulate the major dynamics for the vertical acceleration and the angular rates well enough  for future control design.

Submitted by Thiago Rodrigues Pentiado (thpentiado@gmail.com) on 2018-04-17T14:29:02Z No. of bitstreams: 1 Dissertaçao_Thiago Rodrigues Pentiado.pdf: 2123868 bytes, checksum: 6aa66b3594aba591b49597bc4b262ba6 (MD5) / Approved for entry into archive by Cristina Alexandra de Godoy null (cristina@adm.feis.unesp.br) on 2018-04-17T16:54:17Z (GMT) No. of bitstreams: 1 pentiado_tr_me_ilha.pdf: 2123868 bytes, checksum: 6aa66b3594aba591b49597bc4b262ba6 (MD5) / Made available in DSpace on 2018-04-17T16:54:17Z (GMT). No. of bitstreams: 1 pentiado_tr_me_ilha.pdf: 2123868 bytes, checksum: 6aa66b3594aba591b49597bc4b262ba6 (MD5) Previous issue date: 2018-02-07 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Sistemas de rastreamento de movimento são amplamente utilizados em diversas áreas de conhecimento, como por exemplo, para aplicações de realidade aumentada, ciência do esporte e reabilitação de pacientes. Atualmente, diversas tecnologias existem no mercado para a captura e análise de movimento, entretanto, os altos custos envolvendo tais tecnologias são proibitivos. Isso impede que hospitais, clínicas e grupos de pesquisa tenham acesso a esse tipo de tecnologia. Nesse sentido, é apresentado neste trabalho um sistema de baixo custo de rastreamento do movimento de membros inferiores. O sistema proposto consiste de uma IMU (inertial measurement unit) com três giroscópios e três acelerômetros para as medições, e o algoritmo de filtro de Kalman para reduzir os erros de estimação. Os resultados obtidos mostram que o equipamento, além de dimensões reduzidas de peso e volume, apresenta alto desempenho, com valores de correlação maiores que 99% com o dispositivo de referência, sendo uma alternativa a sistemas comerciais utilizados. / Motion tracking systems are widely used in many areas of knowledge, such as augmented reality applications, sports science and patient rehabilitation. Currently, there are several technologies for motion capture and analysis available in the market, however, the high costs of such technologies prevents hospitals, clinics and research groups from having access to this type of system. In this sense, a low-cost tracking system for lower limb movement is presented in this work. The system consists of an IMU (inertial measurement unit) with three gyroscopes and three accelerometers for the measurements, and the Kalman filter algorithm to reduce estimation errors. The results show that the equipment, in addition to reduced dimensions of weight and volume, presents high performance, with correlation values higher than 99% with the reference device, being an alternative to the reference system used.

Orientador: Aparecido Augusto de Carvalho / Resumo: Sistemas de rastreamento de movimento são amplamente utilizados em diversas áreas de conhecimento, como por exemplo, para aplicações de realidade aumentada, ciência do esporte e reabilitação de pacientes. Atualmente, diversas tecnologias existem no mercado para a captura e análise de movimento, entretanto, os altos custos envolvendo tais tecnologias são proibitivos. Isso impede que hospitais, clínicas e grupos de pesquisa tenham acesso a esse tipo de tecnologia. Nesse sentido, é apresentado neste trabalho um sistema de baixo custo de rastreamento do movimento de membros inferiores. O sistema proposto consiste de uma IMU (inertial measurement unit) com três giroscópios e três acelerômetros para as medições, e o algoritmo de filtro de Kalman para reduzir os erros de estimação. Os resultados obtidos mostram que o equipamento, além de dimensões reduzidas de peso e volume, apresenta alto desempenho, com valores de correlação maiores que 99% com o dispositivo de referência, sendo uma alternativa a sistemas comerciais utilizados. / Abstract: Motion tracking systems are widely used in many areas of knowledge, such as augmented reality applications, sports science and patient rehabilitation. Currently, there are several technologies for motion capture and analysis available in the market, however, the high costs of such technologies prevents hospitals, clinics and research groups from having access to this type of system. In this sense, a low-cost tracking system for lower limb movement is presented in this work. The system consists of an IMU (inertial measurement unit) with three gyroscopes and three accelerometers for the measurements, and the Kalman filter algorithm to reduce estimation errors. The results show that the equipment, in addition to reduced dimensions of weight and volume, presents high performance, with correlation values higher than 99% with the reference device, being an alternative to the reference system used. / Mestre

Les drones ou systèmes de drones aériens jouent un rôle de plus en plus important danstous les domaines, spécialement les drones à décollage et atterrissage verticaux. L’un desplus connus est le Quadrotor et, sans doute, il est la plateforme de recherche la plus utilisée.Cette thèse traite le problème de l’estimation et de la commande d’attitude appliqué àun corps rigide se déplaçant dans l’espace 3D tel que le Quadrotor. La première contributionde cette thèse est la conception et l’implémentation d’une solution d’estimation d’attitude.Celle-ci est basée sur un ensemble de filtres complémentaires combinés avec un algorithmealgébrique tel que TRIAD, QUEST, etc. avec la possibilité de choisir deux formes différentesdes filtres: la première dénommée forme Directe, et la seconde dénommée forme Passive.Les filtres proposés ont une flexibilité dans le choix de l’ordre qui peut être pris grand afinde bien réduire l’effet du bruit de mesure et permettent d’aboutir à un estimateur qui peutprendre en compte le biais éventuel des gyromètres. L’analyse par la théorie de Lyapunovprouve que les erreurs d’estimation tendent globalement et asymptotiquement vers zéro. Unesuite logique de cette première contribution est la proposition d’une solution pour la commanded’attitude qui constitue la deuxième contribution de cette thèse. Elle se traduit par ledéveloppement d’une nouvelle loi de commande d’attitude d’un corps rigide dans l’espace3D, dans laquelle seulement les vecteurs de mesures inertiels avec les mesures des gyromètressont utilisés. Elle utilise le principe de fusion des données à travers un filtre complémentairepermettant l’élimination des bruits des mesures tout en assurant une stabilité presque globalede l’équilibre désiré. La troisième contribution est une loi de commande pour la stabilisationd’attitude sans mesure de vitesse angulaire, ni mesure d’attitude. Pour cela, un systèmelinéaire auxiliaire basé sur les mesures des vecteurs inertiels a été introduit. Ce dernier sesubstitue au manque de l’information de la vitesse angulaire. L’analyse de stabilité du contrôleurproposé est basée sur la théorie de Lyapunov couplée avec le théorème de LaSalle. Ellepermet de conclure sur la stabilité presque globale de l’équilibre désiré. Les performances dessolutions proposées ont été validées par un ensemble de tests expérimentaux / Nowadays, we see a growing popularity of the use of Unmanned Aerial Vehicles (UAV) ofespecially Vertical Take-Off and Landing (VTOL) type. One of the most known VTOL is thequadrotor or Quadcopter which is probably the most used one as a research platform. Thisthesis deal with attitude control and estimation techniques applied to a rigid body movingin 3D space such as Quadcopter VTOL. The first contribution of this thesis is the design ofa new class of complementary linear-like filters allowing the fusion of inertial vector measurementswith angular velocity measurements and combined with algebraic algorithms asTRIAD, QUEST etc. to give an efficient attitude estimation solution. This class of filtersallows several possibilities of implementation such as the order of the filters which can bechosen high in order to reduce more the measurement noise and the form of the filters thatcan be direct or passive and the ability to take into account the possible gyro bias. Lyapunovanalysis shows the global asymptotic convergence of the estimation errors to zero. The sameprinciple of data fusion is used for the proposed new attitude control law in which the complementaryfilters were included to reduce the effect of measurement noise. The obtainedcontroller ensures almost global stability of the desired equilibrium point; it represents thesecond contribution of this thesis. The third contribution takes into consideration an interestingspecial case, where instantaneous measurements of attitude and angular velocity areunavailable. A first order linear auxiliary system based directly on vector measurements isused in an observer-like system to handle the luck of angular velocity. The proposed controllerensures almost global asymptotic stability of the trajectories to the desired equilibriumpoint. Detailed sets of experiments were done to validate the obtained results

This thesis describes the work done to implement and develop position and trajectory control of a quadcopter. The quadcopter was originally equipped with sensors and software to estimate and control the quadcopter's orientation, but did not estimate the current position. A GPS module, GPS antenna and a LIDAR have been added to measure the position in three dimensions. Filters have been implemented and developed to estimate the position, velocity and acceleration. Four controllers have been designed that use these estimates: one PID controller and one LQ controller for vertical movement, and a position controller and a trajectory controller for horizontal movement. The position controller maintains a constant position, while the trajectory controller maintains a constant velocity while travelling along a straight line. These position and trajectory controllers calculate the reference angles required to direct the thrust necessary to control the quadcopter's movement. Additionally, an algorithm has been developed to decrease overshoot by predicting future trajectories. These controllers have proven to be successful at controlling the quadcopter's position in all three dimensions, both in practice during outdoor flight and in simulations.

This thesis presents the design of an inertial measurement data acquisition system intended for use in sailboats. The variables of interest are 3-axis acceleration, 3-axis rotation, GPS position/velocity, magnetic compass bearing and wind speed/direction. The design focus is on low-cost micro-electromechanical systems (MEMS) based technology and demonstrating the validity of these technologies in a scientific application. A prototype is constructed and submitted to a series of tests to demonstrate functionality and soundness of the design. These tests range from bench tests to full scale application. Contributions of this thesis include the novel application of inertial measurement unit (IMU) technology to a sailboat racing application, the integration of all instrumentation, creative ruggedised packaging and emphasising the use of low-cost commercial off-the-shelf (COTS) technology.