70 research outputs found
Motion-based remote control device for interaction with multimedia content
This dissertation describes the development and implementation of techniques to enhance
the accuracy of low-complexity lters, making them suitable for remote control devices
in consumer electronics. The evolution veri ed in the last years, on multimedia contents,
available for consumers in Smart TVs and set-top-boxes, is not raising the expected
interest from users, and one of the pointed reasons for this nding is the user interface.
Although most current pointing devices rely on relative rotation increments, absolute
orientation allows for a more intuitive use and interaction. This possibility is explored in
this work as well as the interaction with multimedia contents through gestures.
Classical accurate fusion algorithms are computationally intensive, therefore their implementation
in low-energy consumption devices is a challenging task. To tackle this
problem, a performance study was carried, comparing a relevant set of professional commercial
of-the-shelf units, with the developed low-complexity lters in state-of-the-art
Magnetic, Angular Rate, Gravity (MARG) sensors. Part of the performance evaluation
tests are carried out under harsh conditions to observe the algorithms response in a nontrivial
environment. The results demonstrate that the implementation of low-complexity
lters using low-cost sensors, can provide an acceptable accuracy in comparison with the
more complex units/ lters. These results pave the way for faster adoption of absolute
orientation-based pointing devices in interactive multimedia applications, which includes
hand-held, battery-operated devices
Development of MEMS - based IMU for position estimation: comparison of sensor fusion solutions
With the surge of inexpensive, widely accessible, and precise Micro-Electro Mechanical Systems (MEMS) in recent years, inertial systems tracking move ment have become ubiquitous nowadays. Contrary to Global Positioning Sys tem (GPS)-based positioning, Inertial Navigation System (INS) are intrinsically
unaffected by signal jamming, blockage susceptibilities, and spoofing. Measure ments from inertial sensors are also acquired at elevated sampling rates and may
be numerically integrated to estimate position and orientation knowledge. These
measurements are precise on a small-time scale but gradually accumulate errors
over extended periods. Combining multiple inertial sensors in a method known as
sensor fusion makes it possible to produce a more consistent and dependable un derstanding of the system, decreasing accumulative errors. Several sensor fusion
algorithms occur in literature aimed at estimating the Attitude and Heading
Reference System (AHRS) of a rigid body with respect to a reference frame.
This work describes the development and implementation of a low-cost, multi purpose INS for position and orientation estimation. Additionally, it presents an
experimental comparison of a series of sensor fusion solutions and benchmarking
their performance on estimating the position of a moving object. Results show
a correlation between what sensors are trusted by the algorithm and how well it
performed at estimating position. Mahony, SAAM and Tilt algorithms had best
general position estimate performance.Com o recente surgimento de sistemas micro-eletromecânico amplamente acessíveis
e precisos nos últimos anos, o rastreio de movimento através de sistemas de in erciais tornou-se omnipresente nos dias de hoje. Contrariamente à localização
baseada no Sistema de Posicionamento Global (GPS), os Sistemas de Naveg ação Inercial (SNI) não são afetados intrinsecamente pela interferência de sinal,
suscetibilidades de bloqueio e falsificação. As medições dos sensores inerciais
também são adquiridas a elevadas taxas de amostragem e podem ser integradas
numericamente para estimar os conhecimentos de posição e orientação. Estas
medições são precisas numa escala de pequena dimensão, mas acumulam grad ualmente erros durante longos períodos. Combinar múltiplos sensores inerci ais num método conhecido como fusão de sensores permite produzir uma mais
consistente e confiável compreensão do sistema, diminuindo erros acumulativos.
Vários algoritmos de fusão de sensores ocorrem na literatura com o objetivo de
estimar os Sistemas de Referência de Atitude e Rumo (SRAR) de um corpo
rígido no que diz respeito a uma estrutura de referência. Este trabalho descreve
o desenvolvimento e implementação de um sistema multiusos de baixo custo
para estimativa de posição e orientação. Além disso, apresenta uma comparação
experimental de uma série de soluções de fusão de sensores e compara o seu de sempenho na estimativa da posição de um objeto em movimento. Os resultados
mostram uma correlação entre os sensores que são confiados pelo algoritmo e o
quão bem ele desempenhou na posição estimada. Os algoritmos Mahony, SAAM
e Tilt tiveram o melhor desempenho da estimativa da posição geral
Indoor positioning system for wireless sensor networks
Tese de Doutoramento - Programa Doutoral em Engenharia Electrónica e ComputadoresPositioning technologies are ubiquitous nowadays. From the implementation of the
global positioning system (GPS) until now, its evolution, acceptance and spread has been
unanimous, due to the underlying advantages the system brings. Currently, these systems are
present in many different scenarios, from the home to the movie theatre, at work, during a
walk in the park. Many applications provide useful information, based on the current position
of the user, in order to provide results of interest.
Positioning systems can be implemented in a wide range of contexts: in hospitals to
locate equipment and guide patients to the necessary resources, or in public spaces like
museums, to guide tourists during visits. They can also be used in a gymnasium to point the
user to his next workout machine and, simultaneously, gather information regarding his
fitness plan. In a congress or conference, the positioning system can be used to provide
information to its participants about the on-going presentations. Devices can also be
monitored to prevent thefts.
Privacy and security issues are also important in positioning systems. A user might not
want to be localized or its location to be known, permanently or during a time interval, in
different locations. This information is therefore sensitive to the user and influences directly
the acceptance of the system itself.
Concerning outdoor systems, GPS is in fact the system of reference. However, this
system cannot be used in indoor environment, due to the high attenuation of the satellite
signals from non-line-of-sight conditions. Another issue related to GPS is the power
consumption. The integration of these devices with wireless sensor networks becomes
prohibitive, due to the low power consumption profile associated with devices in this type of
networks. As such, this work proposes an indoor positioning system for wireless sensor
networks, having in consideration the low energy consumption and low computational
capacity profile.
The proposed indoor positioning system is composed of two modules: the received
signal strength positioning module and the stride and heading positioning module. For the
first module, an experimental performance comparison between several received signal
strength based algorithms was conducted in order to assess its performance in a predefined indoor environment. Modifications to the algorithm with higher performance were
implemented and evaluated, by introducing a model of the effect of the human body in the
received signal strength.
In the case of the second module, a stride and heading system was proposed, which
comprises two subsystems: the stride detection and stride length estimation system to detect
strides and infer the travelled distance, and an attitude and heading reference system to
provide the full three-dimensional orientation stride-by-stride.
The stride detection enabled the identification of the gait cycle and detected strides
with an error percentage between 0% and 0.9%. For the stride length estimation two methods
were proposed, a simplified method, and an improved method with higher computational
requirements than the former. The simplified method estimated the total distance with an error
between 6.7% and 7.7% of total travelled distance. The improved method achieved an error
between 1.2% and 3.7%. Both the stride detection and the improved stride length estimation
methods were compared to other methods in the literature with favourable results.
For the second subsystem, this work proposed a quaternion-based complementary
filter. A generic formulation allows a simple parameterization of the filter, according to the
amount of external influences (accelerations and magnetic interferences) that are expected,
depending on the location that the device is to be attached on the human body. The generic
formulation enables the inclusion/exclusion of components, thus allowing design choices
according to the needs of applications in wireless sensor networks. The proposed method was
compared to two other existing solutions in terms of robustness to interferences and execution
time, also presenting a favourable outcome.Os sistemas de posicionamento fazem parte do quotidiano. Desde a implementação do
sistema GPS (Global Positioning System) até aos dias que correm, a evolução, aceitação e
disseminação destes sistemas foi unânime, derivada das vantagens subjacentes da sua
utilização. Hoje em dia, eles estão presentes nos mais variados cenários, desde o lar até́ à sala
de cinema, no trabalho, num passeio ao ar livre. São várias as aplicações que nos fornecem
informação útil, usando como base a descrição da posição atual, de modo a produzir
resultados de maior interesse para os utilizadores.
Os sistemas de posicionamento podem ser implementados nos mais variados
contextos, como por exemplo: nos hospitais, para localizar equipamento e guiar os pacientes
aos recursos necessários, ou nas grandes superfícies públicas, como por exemplo museus, para
guiar os turistas durante as visitas. Podem ser igualmente utilizados num ginásio para indicar
ao utilizador qual a máquina para onde se deve dirigir durante o seu treino e,
simultaneamente, obter informação acerca desta mesma máquina. Num congresso ou
conferência, o sistema de localização pode ser utilizado para fornecer informação aos seus
participantes sobre as apresentações que estão a decorrer no momento. Os dispositivos
também podem ser monitorizados para prevenir roubos.
Existem também questões de privacidade e segurança associados aos sistemas de
posicionamento. Um utilizador poderá não desejar ser localizado ou que a sua localização seja
conhecida, permanentemente ou num determinado intervalo de tempo, num ou em vários
locais. Esta informação é por isso sensível ao utilizador e influencia diretamente a aceitação
do próprio sistema.
No que diz respeito aos sistemas utilizados no exterior, o GPS (ou posicionamento por
satélite) é de facto o sistema mais utilizado. No entanto, em ambiente interior este sistema não
pode ser usado, por causa da grande atenuação dos sinais provenientes dos satélites devido à
falta de linha de vista. Um outro problema associado ao recetor GPS está relacionado com as
suas características elétricas, nomeadamente os consumos energéticos. A integração destes
dispositivos nas redes de sensores sem fios torna-se proibitiva, devido ao perfil de baixo
consumo associado a estas redes. Este trabalho propõe um sistema de posicionamento para redes de sensores sem fio em
ambiente interior, tendo em conta o perfil de baixo consumo de potência e baixa capacidade
de processamento.
O sistema proposto é constituído por dois módulos: o modulo de posicionamento por
potência de sinal recebido e o módulo de navegação inercial pedestre. Para o primeiro módulo
foi feita uma comparação experimental entre vários algoritmos que utilizam a potência do
sinal recebido, de modo a avaliar a sua utilização num ambiente interior pré-definido. Ao
algoritmo com melhor prestação foram implementadas e testadas modificações, utilizando um
modelo do efeito do corpo na potência do sinal recebido.
Para o segundo módulo foi proposto um sistema de navegação inercial pedestre. Este
sistema é composto por dois subsistemas: o subsistema de deteção de passos e estimação de
distância percorrida; e o subsistema de orientação que fornece a direção do movimento do
utilizador, passo a passo.
O sistema de deteção de passos proposto permite a identificação das fases da marcha,
detetando passos com um erro entre 0% e 0.9%. Para o sistema de estimação da distância
foram propostos dois métodos: um método simplificado de baixa complexidade e um método
melhorado, mas com maiores requisitos computacionais quando comparado com o primeiro.
O método simplificado estima a distância total com erros entre 6.7% e 7.7% da distância
percorrida. O método melhorado por sua vez alcança erros entre 1.2% e 3.7%. Ambos os
sistemas foram comparados com outros sistemas da literatura apresentando resultados
favoráveis.
Para o sistema de orientação, este trabalho propõe um filtro complementar baseado em
quaterniões. É utilizada uma formulação genérica que permite uma parametrização simples do
filtro, de acordo com as influências externas (acelerações e interferências magnéticas) que são
expectáveis, dependendo da localização onde se pretende colocar o dispositivo no corpo
humano. O algoritmo desenvolvido permite a inclusão/exclusão de componentes, permitindo
por isso liberdade de escolha para melhor satisfazer as necessidades das aplicações em redes
de sensores sem fios. O método proposto foi comparado com outras soluções em termos de
robustez a interferências e tempo de execução, apresentando também resultados positivos
Design and implementation of resilient attitude estimation algorithms for aerospace applications
Satellite attitude estimation is a critical component of satellite attitude determination and control systems, relying on highly accurate sensors such as IMUs, star trackers, and sun sensors. However, the complex space environment can cause sensor performance degradation or even failure. To address this issue, FDIR systems are necessary. This thesis presents a novel approach to satellite attitude estimation that utilizes an InertialNavigation System (INS) to achieve high accuracy with the low computational load. The algorithm is based on a two-layer Kalman filter, which incorporates the quaternion estimator(QUEST) algorithm, FQA, Linear interpolation (LERP)algorithms, and KF. Moreover, the thesis proposes an FDIR system for the INS that can detect and isolate faults and recover the system safely. This system includes two-layer fault detection with isolation and two-layered recovery, which utilizes an Adaptive Unscented Kalman Filter (AUKF), QUEST algorithm, residual generators, Radial Basis Function (RBF) neural
networks, and an adaptive complementary filter (ACF). These two fault detection layers aim
to isolate and identify faults while decreasing the rate of false alarms. An FPGA-based FDIR
system is also designed and implemented to reduce latency while maintaining normal resource
consumption in this thesis. Finally, a Fault Tolerance Federated Kalman Filter (FTFKF) is proposed to fuse the output from INS and the CNS to achieve high precision and robust attitude estimation.The findings of this study provide a solid foundation for the development of FDIR systems for various applications such as robotics, autonomous vehicles, and unmanned aerial vehicles, particularly for satellite attitude estimation. The proposed INS-based approach with the FDIR system has demonstrated high accuracy, fault tolerance, and low computational load, making
it a promising solution for satellite attitude estimation in harsh space environment
A wearable hybrid IEEE 802.15.4-2011 ultra-wideband/inertial sensor platform for ambulatory tracking
Ultra-Wideband (UWB) transceivers and low-cost micro electro mechanical systems (MEMS) based inertial sensors are proving a promising hybrid combination for location specific wearable applications. While several hybrid systems have been proposed to date, current approaches consider inertial sensors and UWB as ad-hoc components working in isolation. As a result issues surrounding extensive infrastructure requirements, synchronization, and limitations associated with the mutual sharing of inertial data have arisen. In an attempt to address such limitations, this paper presents a fully-coupled architecture whereby standardised IEEE 802.15.4-2011 UWB is employed for both ranging and as a mechanism for exchanging inertial data between the nodes of a network. A proof-of-concept system is implemented and tested for a single ambulatory use case scenario. Basic fusion algorithms are employed and the preliminary results show the benefits of a fully-coupled approach when compared with traditional standalone inertial navigation
Filtering and Tracking for Pedestrian Dead-Reckoning System.
This thesis proposes a leader-follower system in which a robot, equipped with relatively sophisticated sensors, tracks and follows a human whose equipped with a low-fidelity odometry sensor called a Pedestrian Dead-Reckoning (PDR) device. Such a system is useful for "pack mule" applications, where the robot carries heavy loads for the humans. The proposed system is not dependent upon GPS, which can be jammed or obstructed.
This human-following capability is made possible due to several novel contributions. First, we perform an in-depth analysis of our Pedestrian Dead-Reckoning (PDR) system with the Unscented Kalman Filter (UKF) and models of varying complexity. We propose an extension that limits elevation errors, and show that our proposed method reduces errors by 63% compared to a baseline method. We also propose a method for integrating magnetometers into the PDR framework, which automatically and opportunistically calibrates for hard/soft-iron effects and sensor misalignments. In a series of large-scale experiments, we show that this system achieves positional errors of less than 1.9% of the distance traveled.
Finally, we propose methods that allow a robot to use LIDAR data to improve the accuracy of the robot's estimate of the human’s trajectory. These methods include: 1) a particle filter method and 2) two multi-hypothesis maximum-likelihood approaches based on stochastic gradient descent optimization. We show that the proposed approaches are able to track human trajectories in several synthetic and real-world datasets.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113500/1/suratkw_1.pd
Down-Conditioning of Soleus Reflex Activity using Mechanical Stimuli and EMG Biofeedback
Spasticity is a common syndrome caused by various brain and neural injuries, which can severely impair walking ability and functional independence. To improve functional independence, conditioning protocols are available aimed at reducing spasticity by facilitating spinal neuroplasticity. This down-conditioning can be performed using different types of stimuli, electrical or mechanical, and reflex activity measures, EMG or impedance, used as biofeedback variable. Still, current results on effectiveness of these conditioning protocols are incomplete, making comparisons difficult. We aimed to show the within-session task- dependent and across-session long-term adaptation of a conditioning protocol based on mechanical stimuli and EMG biofeedback. However, in contrast to literature, preliminary results show that subjects were unable to successfully obtain task-dependent modulation of their soleus short-latency stretch reflex magnitude
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