768 research outputs found
Decentralized Riemannian Particle Filtering with Applications to Multi-Agent Localization
The primary focus of this research is to develop consistent nonlinear decentralized particle filtering approaches to the problem of multiple agent localization. A key aspect in our development is the use of Riemannian geometry to exploit the inherently non-Euclidean characteristics that are typical when considering multiple agent localization scenarios. A decentralized formulation is considered due to the practical advantages it provides over centralized fusion architectures. Inspiration is taken from the relatively new field of information geometry and the more established research field of computer vision. Differential geometric tools such as manifolds, geodesics, tangent spaces, exponential, and logarithmic mappings are used extensively to describe probabilistic quantities. Numerous probabilistic parameterizations were identified, settling on the efficient square-root probability density function parameterization. The square-root parameterization has the benefit of allowing filter calculations to be carried out on the well studied Riemannian unit hypersphere. A key advantage for selecting the unit hypersphere is that it permits closed-form calculations, a characteristic that is not shared by current solution approaches. Through the use of the Riemannian geometry of the unit hypersphere, we are able to demonstrate the ability to produce estimates that are not overly optimistic. Results are presented that clearly show the ability of the proposed approaches to outperform current state-of-the-art decentralized particle filtering methods. In particular, results are presented that emphasize the achievable improvement in estimation error, estimator consistency, and required computational burden
Applications in Electronics Pervading Industry, Environment and Society
This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs
Advanced Strategies for Robot Manipulators
Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored
Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using Sequential Monte Carlo Methods with Hyper-Dimensional Spherical Distributions
This dissertation examined the inertial tracking technology for robotics and human tracking applications. This is a multi-discipline research that builds on the embedded system engineering, Bayesian estimation theory, software engineering, directional statistics, and biomedical engineering.
A discussion of the orientation tracking representations and fundamentals of attitude estimation are presented briefly to outline the some of the issues in each approach. In addition, a discussion regarding to inertial tracking sensors gives an insight to the basic science and limitations in each of the sensing components.
An initial experiment was conducted with existing inertial tracker to study the feasibility of using this technology in human motion tracking. Several areas of improvement were made based on the results and analyses from the experiment. As the performance of the system relies on multiple factors from different disciplines, the only viable solution is to optimize the performance in each area. Hence, a top-down approach was used in developing this system.
The implementations of the new generation of hardware system design and firmware structure are presented in this dissertation. The calibration of the system, which is one of the most important factors to minimize the estimation error to the system, is also discussed in details. A practical approach using sequential Monte Carlo method with hyper-dimensional statistical geometry is taken to develop the algorithm for recursive estimation with quaternions.
An analysis conducted from a simulation study provides insights to the capability of the new algorithms. An extensive testing and experiments was conducted with robotic manipulator and free hand human motion to demonstrate the improvements with the new generation of inertial tracker and the accuracy and stability of the algorithm. In addition, the tracking unit is used to demonstrate the potential in multiple biomedical applications including kinematics tracking and diagnosis instrumentation.
The inertial tracking technologies presented in this dissertation is aimed to use specifically for human motion tracking. The goal is to integrate this technology into the next generation of medical diagnostic system
Workshop on Advanced Technologies for Planetary Instruments, part 1
This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. This volume contains papers presented at the Workshop on Advanced Technologies for Planetary Instruments on 28-30 Apr. 1993. This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. Over the past several years, SDIO has sponsored a significant technology development program aimed, in part, at the production of instruments with these characteristics. This workshop provided an opportunity for specialists from the planetary science and DoD communities to establish contacts, to explore common technical ground in an open forum, and more specifically, to discuss the applicability of SDIO's technology base to planetary science instruments
Efficient algorithms for arbitrary sample rate conversion with application to wave field synthesis
Arbitrary sample rate conversion (ASRC) is used in many fields of digital signal processing to alter the sampling rate of discrete-time signals by arbitrary, potentially time-varying ratios.
This thesis investigates efficient algorithms for ASRC and proposes several improvements. First, closed-form descriptions for the modified Farrow structure and Lagrange interpolators are derived that are directly applicable to algorithm design and analysis. Second, efficient implementation structures for ASRC algorithms are investigated. Third, this thesis considers coefficient design methods that are optimal for a selectable error norm and optional design constraints.
Finally, the performance of different algorithms is compared for several performance metrics. This enables the selection of ASRC algorithms that meet the requirements of an application with minimal complexity.
Wave field synthesis (WFS), a high-quality spatial sound reproduction technique, is the main application considered in this work. For WFS, sophisticated ASRC algorithms improve the quality of moving sound sources. However, the improvements proposed in this thesis are not limited to WFS, but applicable to general-purpose ASRC problems.Verfahren zur unbeschränkten Abtastratenwandlung (arbitrary sample rate
conversion,ASRC) ermöglichen die Änderung der Abtastrate zeitdiskreter
Signale um beliebige, zeitvarianteVerhältnisse. ASRC wird in vielen
Anwendungen digitaler Signalverarbeitung eingesetzt.In dieser Arbeit wird
die Verwendung von ASRC-Verfahren in der Wellenfeldsynthese(WFS), einem
Verfahren zur hochqualitativen, räumlich korrekten Audio-Wiedergabe,
untersucht.Durch ASRC-Algorithmen kann die Wiedergabequalität bewegter
Schallquellenin WFS deutlich verbessert werden. Durch die hohe Zahl der in
einem WFS-Wiedergabesystembenötigten simultanen ASRC-Operationen ist eine
direkte Anwendung hochwertigerAlgorithmen jedoch meist nicht möglich.Zur
Lösung dieses Problems werden verschiedene Beiträge vorgestellt. Die
Komplexitätder WFS-Signalverarbeitung wird durch eine geeignete
Partitionierung der ASRC-Algorithmensignifikant reduziert, welche eine
effiziente Wiederverwendung von Zwischenergebnissenermöglicht. Dies
erlaubt den Einsatz hochqualitativer Algorithmen zur Abtastratenwandlungmit
einer Komplexität, die mit der Anwendung einfacher konventioneller
ASRCAlgorithmenvergleichbar ist. Dieses Partitionierungsschema stellt
jedoch auch zusätzlicheAnforderungen an ASRC-Algorithmen und erfordert
Abwägungen zwischen Performance-Maßen wie der algorithmischen
Komplexität, Speicherbedarf oder -bandbreite.Zur Verbesserung von
Algorithmen und Implementierungsstrukturen fĂĽr ASRC werdenverschiedene
MaĂźnahmen vorgeschlagen. Zum Einen werden geschlossene,
analytischeBeschreibungen fĂĽr den kontinuierlichen Frequenzgang
verschiedener Klassen von ASRCStruktureneingefĂĽhrt. Insbesondere fĂĽr
Lagrange-Interpolatoren, die modifizierte Farrow-Struktur sowie
Kombinationen aus Ăśberabtastung und zeitkontinuierlichen
Resampling-Funktionen werden kompakte Darstellungen hergeleitet, die sowohl
Aufschluss ĂĽber dasVerhalten dieser Filter geben als auch eine direkte
Verwendung in Design-Methoden ermöglichen.Einen zweiten Schwerpunkt bildet
das Koeffizientendesign fĂĽr diese Strukturen, insbesonderezum optimalen
Entwurf bezüglich einer gewählten Fehlernorm und optionaler
Entwurfsbedingungenund -restriktionen. Im Gegensatz zu bisherigen Ansätzen
werden solcheoptimalen Entwurfsmethoden auch fĂĽr mehrstufige
ASRC-Strukturen, welche ganzzahligeĂśberabtastung mit zeitkontinuierlichen
Resampling-Funktionen verbinden, vorgestellt.FĂĽr diese Klasse von
Strukturen wird eine Reihe angepasster Resampling-Funktionen
vorgeschlagen,welche in Verbindung mit den entwickelten optimalen
Entwurfsmethoden signifikanteQualitätssteigerungen ermöglichen.Die
Vielzahl von ASRC-Strukturen sowie deren Design-Parameter bildet eine
Hauptschwierigkeitbei der Auswahl eines fĂĽr eine gegebene Anwendung
geeigneten Verfahrens.Evaluation und Performance-Vergleiche bilden daher
einen dritten Schwerpunkt. Dazu wirdzum Einen der Einfluss verschiedener
Entwurfsparameter auf die erzielbare Qualität vonASRC-Algorithmen
untersucht. Zum Anderen wird der benötigte Aufwand bezüglich
verschiedenerPerformance-Metriken in Abhängigkeit von Design-Qualität
dargestellt.Auf diese Weise sind die Ergebnisse dieser Arbeit nicht auf WFS
beschränkt, sondernsind in einer Vielzahl von Anwendungen unbeschränkter
Abtastratenwandlung nutzbar
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