982 resultados para Inertial Measurement Unit


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The use of computational fluid dynamics simulations for calibrating a flush air data system is described, In particular, the flush air data system of the HYFLEX hypersonic vehicle is used as a case study. The HYFLEX air data system consists of nine pressure ports located flush with the vehicle nose surface, connected to onboard pressure transducers, After appropriate processing, surface pressure measurements can he converted into useful air data parameters. The processing algorithm requires an accurate pressure model, which relates air data parameters to the measured pressures. In the past, such pressure models have been calibrated using combinations of flight data, ground-based experimental results, and numerical simulation. We perform a calibration of the HYFLEX flush air data system using computational fluid dynamics simulations exclusively, The simulations are used to build an empirical pressure model that accurately describes the HYFLEX nose pressure distribution ol cr a range of flight conditions. We believe that computational fluid dynamics provides a quick and inexpensive way to calibrate the air data system and is applicable to a broad range of flight conditions, When tested with HYFLEX flight data, the calibrated system is found to work well. It predicts vehicle angle of attack and angle of sideslip to accuracy levels that generally satisfy flight control requirements. Dynamic pressure is predicted to within the resolution of the onboard inertial measurement unit. We find that wind-tunnel experiments and flight data are not necessary to accurately calibrate the HYFLEX flush air data system for hypersonic flight.

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Hand and finger tracking has a major importance in healthcare, for rehabilitation of hand function required due to a neurological disorder, and in virtual environment applications, like characters animation for on-line games or movies. Current solutions consist mostly of motion tracking gloves with embedded resistive bend sensors that most often suffer from signal drift, sensor saturation, sensor displacement and complex calibration procedures. More advanced solutions provide better tracking stability, but at the expense of a higher cost. The proposed solution aims to provide the required precision, stability and feasibility through the combination of eleven inertial measurements units (IMUs). Each unit captures the spatial orientation of the attached body. To fully capture the hand movement, each finger encompasses two units (at the proximal and distal phalanges), plus one unit at the back of the hand. The proposed glove was validated in two distinct steps: a) evaluation of the sensors’ accuracy and stability over time; b) evaluation of the bending trajectories during usual finger flexion tasks based on the intra-class correlation coefficient (ICC). Results revealed that the glove was sensitive mainly to magnetic field distortions and sensors tuning. The inclusion of a hard and soft iron correction algorithm and accelerometer and gyro drift and temperature compensation methods provided increased stability and precision. Finger trajectories evaluation yielded high ICC values with an overall reliability within application’s satisfying limits. The developed low cost system provides a straightforward calibration and usability, qualifying the device for hand and finger tracking in healthcare and animation industries.

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This paper reports on the creation of an interface for 3D virtual environments, computer-aided design applications or computer games. Standard computer interfaces are bound to 2D surfaces, e.g., computer mouses, keyboards, touch pads or touch screens. The Smart Object is intended to provide the user with a 3D interface by using sensors that register movement (inertial measurement unit), touch (touch screen) and voice (microphone). The design and development process as well as the tests and results are presented in this paper. The Smart Object was developed by a team of four third-year engineering students from diverse scientific backgrounds and nationalities during one semester.

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O uso da tecnologia tem crescido nas últimas décadas nas mais diversas áreas, seja na indústria ou no dia-a-dia, e é cada vez mais evidente os benefícios que traz. No desporto não é diferente. Cada dia surgem novos desenvolvimentos objetivando a melhoria do desempenho dos praticantes de atividades físicas, possibilitando atingir resultados nunca antes pensados. Além disto, a utilização da tecnologia no desporto permite a obtenção de dados biomecânicos que podem ser utilizados tanto no treinamento quando na melhoria da qualidade de vida dos atletas auxiliando na prevenção de lesões, por exemplo. Deste modo, o presente projeto se aplica na área do desporto, nomeadamente, na modalidade do surfe, onde a ausência de trabalhos científicos ainda é elevada, aliando a tecnologia eletrônica ao desporto para quantificar informações até então desconhecidas. Três fatores básicos de desempenho foram levantados, sendo eles: equilíbrio, posicionamento dos pés e movimentação da prancha de surfe. Estes fatores levaram ao desenvolvimento de um sistema capaz de medi-los dinamicamente através da medição das forças plantares e da rotação da prancha de surfe. Além da medição dos fatores, o sistema é capaz de armazenar os dados adquiridos localmente através de um cartão de memória, para posterior análise; e também enviá-los através de uma comunicação sem fio, permitindo a visualização do centro de pressões plantares; dos ângulos de rotação da prancha de surfe; e da ativação dos sensores; em tempo real. O dispositivo consiste em um sistema eletrônico embarcado composto por um microcontrolador ATMEGA1280; um circuito de aquisição e condicionamento de sinal analógico; uma central inercial; um módulo de comunicação sem fio RN131; e um conjunto de sensores de força Flexiforce. O firmware embarcado foi desenvolvido em linguagem C. O software Matlab foi utilizado para receção de dados e visualização em tempo real. Os testes realizados demostraram que o funcionamento do sistema atende aos requisitos propostos, fornecendo informação acerca do equilíbrio, através do centro de pressões; do posicionamento dos pés, através da distribuição das pressões plantares; e do movimento da prancha nos eixos pitch e roll, através da central inercial. O erro médio de medição de força verificado foi de -0.0012 ± 0.0064 N, enquanto a mínima distância alcançada na transmissão sem fios foi de 100 m. A potência medida do sistema foi de 330 mW.

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13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

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A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.

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Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.

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Near ground maneuvers, such as hover, approach and landing, are key elements of autonomy in unmanned aerial vehicles. Such maneuvers have been tackled conventionally by measuring or estimating the velocity and the height above the ground often using ultrasonic or laser range finders. Near ground maneuvers are naturally mastered by flying birds and insects as objects below may be of interest for food or shelter. These animals perform such maneuvers efficiently using only the available vision and vestibular sensory information. In this paper, the time-to-contact (Tau) theory, which conceptualizes the visual strategy with which many species are believed to approach objects, is presented as a solution for Unmanned Aerial Vehicles (UAV) relative ground distance control. The paper shows how such an approach can be visually guided without knowledge of height and velocity relative to the ground. A control scheme that implements the Tau strategy is developed employing only visual information from a monocular camera and an inertial measurement unit. To achieve reliable visual information at a high rate, a novel filtering system is proposed to complement the control system. The proposed system is implemented on-board an experimental quadrotor UAV and shown not only to successfully land and approach ground, but also to enable the user to choose the dynamic characteristics of the approach. The methods presented in this paper are applicable to both aerial and space autonomous vehicles.

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Near-ground maneuvers, such as hover, approach, and landing, are key elements of autonomy in unmanned aerial vehicles. Such maneuvers have been tackled conventionally by measuring or estimating the velocity and the height above the ground, often using ultrasonic or laser range finders. Near-ground maneuvers are naturally mastered by flying birds and insects because objects below may be of interest for food or shelter. These animals perform such maneuvers efficiently using only the available vision and vestibular sensory information. In this paper, the time-tocontact (tau) theory, which conceptualizes the visual strategy with which many species are believed to approach objects, is presented as a solution for relative ground distance control for unmanned aerial vehicles. The paper shows how such an approach can be visually guided without knowledge of height and velocity relative to the ground. A control scheme that implements the tau strategy is developed employing only visual information from a monocular camera and an inertial measurement unit. To achieve reliable visual information at a high rate, a novel filtering system is proposed to complement the control system. The proposed system is implemented onboard an experimental quadrotor unmannedaerial vehicle and is shown to not only successfully land and approach ground, but also to enable the user to choose the dynamic characteristics of the approach. The methods presented in this paper are applicable to both aerial and space autonomous vehicles.

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In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

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Pós-graduação em Ciências Cartográficas - FCT

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Healthcare, Human Computer Interfaces (HCI), Security and Biometry are the most promising application scenario directly involved in the Body Area Networks (BANs) evolution. Both wearable devices and sensors directly integrated in garments envision a word in which each of us is supervised by an invisible assistant monitoring our health and daily-life activities. New opportunities are enabled because improvements in sensors miniaturization and transmission efficiency of the wireless protocols, that achieved the integration of high computational power aboard independent, energy-autonomous, small form factor devices. Application’s purposes are various: (I) data collection to achieve off-line knowledge discovery; (II) user notification of his/her activities or in case a danger occurs; (III) biofeedback rehabilitation; (IV) remote alarm activation in case the subject need assistance; (V) introduction of a more natural interaction with the surrounding computerized environment; (VI) users identification by physiological or behavioral characteristics. Telemedicine and mHealth [1] are two of the leading concepts directly related to healthcare. The capability to borne unobtrusiveness objects supports users’ autonomy. A new sense of freedom is shown to the user, not only supported by a psychological help but a real safety improvement. Furthermore, medical community aims the introduction of new devices to innovate patient treatments. In particular, the extension of the ambulatory analysis in the real life scenario by proving continuous acquisition. The wide diffusion of emerging wellness portable equipment extended the usability of wearable devices also for fitness and training by monitoring user performance on the working task. The learning of the right execution techniques related to work, sport, music can be supported by an electronic trainer furnishing the adequate aid. HCIs made real the concept of Ubiquitous, Pervasive Computing and Calm Technology introduced in the 1988 by Marc Weiser and John Seeley Brown. They promotes the creation of pervasive environments, enhancing the human experience. Context aware, adaptive and proactive environments serve and help people by becoming sensitive and reactive to their presence, since electronics is ubiquitous and deployed everywhere. In this thesis we pay attention to the integration of all the aspects involved in a BAN development. Starting from the choice of sensors we design the node, configure the radio network, implement real-time data analysis and provide a feedback to the user. We present algorithms to be implemented in wearable assistant for posture and gait analysis and to provide assistance on different walking conditions, preventing falls. Our aim, expressed by the idea to contribute at the development of a non proprietary solutions, driven us to integrate commercial and standard solutions in our devices. We use sensors available on the market and avoided to design specialized sensors in ASIC technologies. We employ standard radio protocol and open source projects when it was achieved. The specific contributions of the PhD research activities are presented and discussed in the following. • We have designed and build several wireless sensor node providing both sensing and actuator capability making the focus on the flexibility, small form factor and low power consumption. The key idea was to develop a simple and general purpose architecture for rapid analysis, prototyping and deployment of BAN solutions. Two different sensing units are integrated: kinematic (3D accelerometer and 3D gyroscopes) and kinetic (foot-floor contact pressure forces). Two kind of feedbacks were implemented: audio and vibrotactile. • Since the system built is a suitable platform for testing and measuring the features and the constraints of a sensor network (radio communication, network protocols, power consumption and autonomy), we made a comparison between Bluetooth and ZigBee performance in terms of throughput and energy efficiency. Test in the field evaluate the usability in the fall detection scenario. • To prove the flexibility of the architecture designed, we have implemented a wearable system for human posture rehabilitation. The application was developed in conjunction with biomedical engineers who provided the audio-algorithms to furnish a biofeedback to the user about his/her stability. • We explored off-line gait analysis of collected data, developing an algorithm to detect foot inclination in the sagittal plane, during walk. • In collaboration with the Wearable Lab – ETH, Zurich, we developed an algorithm to monitor the user during several walking condition where the user carry a load. The remainder of the thesis is organized as follows. Chapter I gives an overview about Body Area Networks (BANs), illustrating the relevant features of this technology and the key challenges still open. It concludes with a short list of the real solutions and prototypes proposed by academic research and manufacturers. The domain of the posture and gait analysis, the methodologies, and the technologies used to provide real-time feedback on detected events, are illustrated in Chapter II. The Chapter III and IV, respectively, shown BANs developed with the purpose to detect fall and monitor the gait taking advantage by two inertial measurement unit and baropodometric insoles. Chapter V reports an audio-biofeedback system to improve balance on the information provided by the use centre of mass. A walking assistant based on the KNN classifier to detect walking alteration on load carriage, is described in Chapter VI.

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L’analisi del cammino è uno strumento in grado di fornire importanti informazioni sul ciclo del passo; in particolare è fondamentale per migliorare le conoscenze biomeccaniche del cammino, sia normale che patologico, e su come questo viene eseguito dai singoli soggetti. I parametri spazio temporali del passo rappresentano alcuni degli indici più interessanti per caratterizzare il cammino ed il passo nelle sue diverse fasi. Essi permettono infatti il confronto e il riconoscimento di patologie e disturbi dell’andatura. Negli ultimi anni è notevolmente aumentato l’impiego di sensori inerziali (Inertial Measurement Unit, IMU), che comprendono accelerometri, giroscopi e magnetometri. Questi dispositivi, utilizzati singolarmente o insieme, possono essere posizionati direttamente sul corpo dei pazienti e sono in grado fornire, rispettivamente, il segnale di accelerazione, di velocità angolare e del campo magnetico terrestre. A partire da questi segnali, ottenuti direttamente dal sensore, si è quindi cercato di ricavare i parametri caratteristici dell’andatura, per valutare il cammino anche al di fuori dell’ambiente di laboratorio. Vista la loro promettente utilità e la potenziale vasta applicabilità nell’analisi del ciclo del cammino; negli ultimi anni un vasto settore della ricerca scientifica si è dedicata allo sviluppo di algoritmi e metodi per l’estrazione dei parametri spazio temporali a partire da dati misurati mediante sensori inerziali. Data la grande quantità di lavori pubblicati e di studi proposti è emersa la necessità di fare chiarezza, riassumendo e confrontando i metodi conosciuti, valutando le prestazioni degli algoritmi, l’accuratezza dei parametri ricavati, anche in base alla tipologia del sensore e al suo collocamento sull’individuo, e gli eventuali limiti. Lo scopo della presente tesi è quindi l’esecuzione di una revisione sistematica della letteratura riguardante la stima dei parametri spazio temporali mediante sensori inerziali. L’intento è di analizzare le varie tecniche di estrazione dei parametri spazio temporali a partire da dati misurati con sensori inerziali, utilizzate fino ad oggi ed indagate nella letteratura più recente; verrà utilizzato un approccio prettamente metodologico, tralasciando l’aspetto clinico dei risultati.

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L’analisi della postura e del movimento umano costituiscono un settore biomedico in forte espansione e di grande interesse dal punto di vista clinico. La valutazione delle caratteristiche della postura e del movimento, nonché delle loro variazioni rispetto ad una situazione di normalità, possono essere di enorme utilità in campo clinico per la diagnosi di particolari patologie, così come per la pianificazione ed il controllo di specifici trattamenti riabilitativi. In particolare è utile una valutazione quantitativa della postura e del movimento che può essere effettuata solo utilizzando metodologie e tecnologie ‘ad hoc’. Negli ultimi anni la diffusione di sensori MEMS e lo sviluppo di algoritmi di sensor fusion hanno portato questi dispositivi ad entrare nel mondo della Motion Capture. Queste piattaforme multi-sensore, comunemente chiamate IMU (Inertial Measurement Unit), possono rappresentare l’elemento base di una rete sensoriale per il monitoraggio del movimento umano.

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Lo studio dello sviluppo delle attività motorie fondamentali (FMS) nei bambini sta acquisendo in questi anni grande importanza, poiché la padronanza di queste ultime sembra essere correlata positivamente sia con la condizione di benessere fisico, sia con il mantenimento di alti livelli di autostima; si ritiene inoltre che possano contribuire al mantenimento di uno stile di vita sano in età adulta. In questo elaborato di tesi viene preso in considerazione un test di riferimento per la valutazione delle FMS, il TMGD – 2. Lo scopo è quello di fornire una valutazione quantitativa delle performance delle FMS, sulla base degli standard proposti dal protocollo TGMD-2, mediante una versione strumentata del test, utilizzando delle Inertial Measurement Unit (IMU). Questi sensori consentono di superare il limite posto dalla soggettività nella valutazione dell’operatore e permettono di esprimere un giudizio in maniera rapida e automatica. Il TGMD-2 è stato somministrato, in versione strumentata, a 91 soggetti di età compresa tra i 6 e i 10 anni. Sono stati ideati degli algoritmi che, a partire dai segnali di accelerazione e velocità angolare acquisiti mediante le IMU, consentono di conferire una valutazione a ciascuno dei task impartito dal TGMD – 2. Gli algoritmi sono stati validati mediante il confronto fra i risultati ottenuti e i giudizi di un valutatore esperto del TGMD-2, mostrando un alto grado di affinità, in genere tra l’80% e il 90%.