Adaptive spatio-temporal filter for low-cost camera depth maps

In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters to different levels of estimated noise. Kalman filters are used to reduce the temporal random fluctuations of the measurements. Finally an interpolation algorithm is used to obtain consistent depth maps in the regions where the depth information is not available. Results show that this approach allows to considerably improve the depth maps quality by considering spatio-temporal information and by adapting its parameters to different levels of noise.

Wireless communication enhancement methods for mobile robots in radiation environments

En entornos hostiles tales como aquellas instalaciones científicas donde la radiación ionizante es el principal peligro, el hecho de reducir las intervenciones humanas mediante el incremento de las operaciones robotizadas está siendo cada vez más de especial interés. CERN, la Organización Europea para la Investigación Nuclear, tiene alrededor de unos 50 km de superficie subterránea donde robots móviles controlador de forma remota podrían ayudar en su funcionamiento, por ejemplo, a la hora de llevar a cabo inspecciones remotas sobre radiación en los diferentes áreas destinados al efecto. No solo es preciso considerar que los robots deben ser capaces de recorrer largas distancias y operar durante largos periodos de tiempo, sino que deben saber desenvolverse en los correspondientes túneles subterráneos, tener en cuenta la presencia de campos electromagnéticos, radiación ionizante, etc. y finalmente, el hecho de que los robots no deben interrumpir el funcionamiento de los aceleradores. El hecho de disponer de un sistema de comunicaciones inalámbrico fiable y robusto es esencial para la correcta ejecución de las misiones que los robots deben afrontar y por supuesto, para evitar tales situaciones en las que es necesario la recuperación manual de los robots al agotarse su energía o al perder el enlace de comunicaciones. El objetivo de esta Tesis es proveer de las directrices y los medios necesarios para reducir el riesgo de fallo en la misión y maximizar las capacidades de los robots móviles inalámbricos los cuales disponen de almacenamiento finito de energía al trabajar en entornos peligrosos donde no se dispone de línea de vista directa. Para ello se proponen y muestran diferentes estrategias y métodos de comunicación inalámbrica. Teniendo esto en cuenta, se presentan a continuación los objetivos de investigación a seguir a lo largo de la Tesis: predecir la cobertura de comunicaciones antes y durante las misiones robotizadas; optimizar la capacidad de red inalámbrica de los robots móviles con respecto a su posición; y mejorar el rango operacional de esta clase de robots. Por su parte, las contribuciones a la Tesis se citan más abajo. El primer conjunto de contribuciones son métodos novedosos para predecir el consumo de energía y la autonomía en la comunicación antes y después de disponer de los robots en el entorno seleccionado. Esto es importante para proporcionar conciencia de la situación del robot y evitar fallos en la misión. El consumo de energía se predice usando una estrategia propuesta la cual usa modelos de consumo provenientes de diferentes componentes en un robot. La predicción para la cobertura de comunicaciones se desarrolla usando un nuevo filtro de RSS (Radio Signal Strength) y técnicas de estimación con la ayuda de Filtros de Kalman. El segundo conjunto de contribuciones son métodos para optimizar el rango de comunicaciones usando novedosas técnicas basadas en muestreo espacial que son robustas frente a ruidos de campos de detección y radio y que proporcionan redundancia. Se emplean métodos de diferencia central finitos para determinar los gradientes 2D RSS y se usa la movilidad del robot para optimizar el rango de comunicaciones y la capacidad de red. Este método también se valida con un caso de estudio centrado en la teleoperación háptica de robots móviles inalámbricos. La tercera contribución es un algoritmo robusto y estocástico descentralizado para la optimización de la posición al considerar múltiples robots autónomos usados principalmente para extender el rango de comunicaciones desde la estación de control al robot que está desarrollando la tarea. Todos los métodos y algoritmos propuestos se verifican y validan usando simulaciones y experimentos de campo con variedad de robots móviles disponibles en CERN. En resumen, esta Tesis ofrece métodos novedosos y demuestra su uso para: predecir RSS; optimizar la posición del robot; extender el rango de las comunicaciones inalámbricas; y mejorar las capacidades de red de los robots móviles inalámbricos para su uso en aplicaciones dentro de entornos peligrosos, que como ya se mencionó anteriormente, se destacan las instalaciones científicas con emisión de radiación ionizante. En otros términos, se ha desarrollado un conjunto de herramientas para mejorar, facilitar y hacer más seguras las misiones de los robots en entornos hostiles. Esta Tesis demuestra tanto en teoría como en práctica que los robots móviles pueden mejorar la calidad de las comunicaciones inalámbricas mediante la profundización en el estudio de su movilidad para optimizar dinámicamente sus posiciones y mantener conectividad incluso cuando no existe línea de vista. Los métodos desarrollados en la Tesis son especialmente adecuados para su fácil integración en robots móviles y pueden ser aplicados directamente en la capa de aplicación de la red inalámbrica. ABSTRACT In hostile environments such as in scientific facilities where ionising radiation is a dominant hazard, reducing human interventions by increasing robotic operations are desirable. CERN, the European Organization for Nuclear Research, has around 50 km of underground scientific facilities, where wireless mobile robots could help in the operation of the accelerator complex, e.g. in conducting remote inspections and radiation surveys in different areas. The main challenges to be considered here are not only that the robots should be able to go over long distances and operate for relatively long periods, but also the underground tunnel environment, the possible presence of electromagnetic fields, radiation effects, and the fact that the robots shall in no way interrupt the operation of the accelerators. Having a reliable and robust wireless communication system is essential for successful execution of such robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy or when the robot loses its communication link. The goal of this thesis is to provide means to reduce risk of mission failure and maximise mission capabilities of wireless mobile robots with finite energy storage capacity working in a radiation environment with non-line-of-sight (NLOS) communications by employing enhanced wireless communication methods. Towards this goal, the following research objectives are addressed in this thesis: predict the communication range before and during robotic missions; optimise and enhance wireless communication qualities of mobile robots by using robot mobility and employing multi-robot network. This thesis provides introductory information on the infrastructures where mobile robots will need to operate, the tasks to be carried out by mobile robots and the problems encountered in these environments. The reporting of research work carried out to improve wireless communication comprises an introduction to the relevant radio signal propagation theory and technology followed by explanation of the research in the following stages: An analysis of the wireless communication requirements for mobile robot for different tasks in a selection of CERN facilities; predictions of energy and communication autonomies (in terms of distance and time) to reduce risk of energy and communication related failures during missions; autonomous navigation of a mobile robot to find zone(s) of maximum radio signal strength to improve communication coverage area; and autonomous navigation of one or more mobile robots acting as mobile wireless relay (repeater) points in order to provide a tethered wireless connection to a teleoperated mobile robot carrying out inspection or radiation monitoring activities in a challenging radio environment. The specific contributions of this thesis are outlined below. The first sets of contributions are novel methods for predicting the energy autonomy and communication range(s) before and after deployment of the mobile robots in the intended environments. This is important in order to provide situational awareness and avoid mission failures. The energy consumption is predicted by using power consumption models of different components in a mobile robot. This energy prediction model will pave the way for choosing energy-efficient wireless communication strategies. The communication range prediction is performed using radio signal propagation models and applies radio signal strength (RSS) filtering and estimation techniques with the help of Kalman filters and Gaussian process models. The second set of contributions are methods to optimise the wireless communication qualities by using novel spatial sampling based techniques that are robust to sensing and radio field noises and provide redundancy features. Central finite difference (CFD) methods are employed to determine the 2-D RSS gradients and use robot mobility to optimise the communication quality and the network throughput. This method is also validated with a case study application involving superior haptic teleoperation of wireless mobile robots where an operator from a remote location can smoothly navigate a mobile robot in an environment with low-wireless signals. The third contribution is a robust stochastic position optimisation algorithm for multiple autonomous relay robots which are used for wireless tethering of radio signals and thereby to enhance the wireless communication qualities. All the proposed methods and algorithms are verified and validated using simulations and field experiments with a variety of mobile robots available at CERN. In summary, this thesis offers novel methods and demonstrates their use to predict energy autonomy and wireless communication range, optimise robots position to improve communication quality and enhance communication range and wireless network qualities of mobile robots for use in applications in hostile environmental characteristics such as scientific facilities emitting ionising radiations. In simpler terms, a set of tools are developed in this thesis for improving, easing and making safer robotic missions in hostile environments. This thesis validates both in theory and experiments that mobile robots can improve wireless communication quality by exploiting robots mobility to dynamically optimise their positions and maintain connectivity even when the (radio signal) environment possess non-line-of-sight characteristics. The methods developed in this thesis are well-suited for easier integration in mobile robots and can be applied directly at the application layer of the wireless network. The results of the proposed methods have outperformed other comparable state-of-the-art methods.

Improved Animal Tracking Algorithm using Distributed Kalman Filter-based Algortihms

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

Multiple Frequency Solidly Mounted BAW Filters

This paper reports the simultaneous fabrication of Receive and Transmit Bulk Acoustic Wave filters for the WCDMA standard on the same die. Both filters are based on Solidly Mounted Resonators using a common Bragg mirror, but with each having a specific piezoelectric film thickness. Electrical measurements reveal that the process steps required to provide the two different piezoelectric film thicknesses on the same die does not impact the electrical performances of resonators and filters and that this approach could thus be generalised to more than two filters.

Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter

When we try to analyze and to control a system whose model was obtained only based on input/output data, accuracy is essential in the model. On the other hand, to make the procedure practical, the modeling stage must be computationally efficient. In this regard, this paper presents the application of extended Kalman filter for the parametric adaptation of a fuzzy model

Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation

Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation in-line with the process

Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling

Adaptive embedded systems are required in various applications. This work addresses these needs in the area of adaptive image compression in FPGA devices. A simplified version of an evolution strategy is utilized to optimize wavelet filters of a Discrete Wavelet Transform algorithm. We propose an adaptive image compression system in FPGA where optimized memory architecture, parallel processing and optimized task scheduling allow reducing the time of evolution. The proposed solution has been extensively evaluated in terms of the quality of compression as well as the processing time. The proposed architecture reduces the time of evolution by 44% compared to our previous reports while maintaining the quality of compression unchanged with respect to existing implementations. The system is able to find an optimized set of wavelet filters in less than 2 min whenever the input type of data changes.

On the penetration of particles through filters and masks.

El principal objetivo de este trabajo es la evaluación de la eficiencia de filtros y máscaras destinados a la protección de los trabajadores contra partículas sólidas respirables. Se ha diseñado un dispositivo que simula los ciclos respiratorios del ser humano de forma automática. Filtros y máscaras se ensayan en el interior de una cámara, en una atmósfera controlada, y se introducen partículas de polvo en suspensión en su interior. Las partículas de polvo pasan a través de los filtros y se toma una muestra en vía húmeda. Se toma una muestra de polvo después de pasar por los filtros y se compara con la inicial, en una forma cualitativa y cuantitativa, mediante gravimetría y difracción laser. Analizados los resultados, se ha observado una variabilidad significativa en la eficiencia de máscaras y filtros pertenecientes a una misma categoría, por lo que se han sugerido recomendaciones a la normativa actual.

Optimal design of AC EMI filters with damping networks and effect on the systems power factor

The cutoff frequencies of an EMI filter are normally given by the noise attenuation requirements the filter has to fulfill. In order to select the component values of the filter elements, i.e. inductances and capacitances, an additional design criterium is needed. In this paper the effect of the EMI filter input and output impedances are considered. The input impedance influences the filters effect on the system displacement power factor and the output impedance plays a key role in the system stability. The effect of filter element values, the number of filter stages as well as additional damping networks are considered and a design procedure is provided. For this analysis a two-port description of the input filters employing ABCD-parameters is used.

Design and Multi-Objective Optimization of EMI Input Filters

An EMI filter design procedure for power converters is proposed. Based on a given noise spectrum, information about the converter noise source impedance and design constraints, the design space of the input filter is defined. The design is based on component databases and detailed models of the filter components, including high frequency parasitics, losses, weight, volume, etc.. The design space is mapped onto a performance space in which different filter implementations are evaluated and compared. A multi-objective optimization approach is used to obtain optimal designs w.r.t. a given performance function.

Fractal analysis of laplacian pyramidal filters applied to segmentation of soil images

The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. The required properties to the pyramidal filter produce a family of filters, which is unipara metrical in the case of the classical problem, when the length of the filter is 5. We pay attention to gaussian and fractal behaviour of these basis functions (or filters), and we determine the gaussian and fractal ranges in the case of single parameter ?. These fractal filters loose less energy in every step of the laplacian pyramid, and we apply this property to get threshold values for segmenting soil images, and then evaluate their porosity. Also, we evaluate our results by comparing them with the Otsu algorithm threshold values, and conclude that our algorithm produce reliable test results.

Optical signal impairment study of cascaded optical filters in 40 Gbps DQPSK and 100 Gbps PM-DQPSK systems

Optical filters are crucial elements in optical communications. The influence of cascaded filters in the optical signal will affect the communications quality seriously. In this paper we will study and simulate the optical signal impairment caused by different kinds of filters which include Butterworth, Bessel, Fiber Bragg Grating (FBG) and Fabry-Perot (FP). Optical signal impairment is analyzed from an Eye Opening Penalty (EOP) and optical spectrum point of view. The simulation results show that when the center frequency of all filters aligns with the laser’s frequency, the Butterworth has the smallest influence to the signal while the F-P has the biggest. With a -1dB EOP, the amount of cascaded Butterworth optical filters with a bandwidth of 50 GHz is 18 in 40 Gbps NRZ-DQPSK systems and 12 in 100 Gbps PMNRZ- DQPSK systems. The value is reduced to 9 and 6 respectively for Febry-Perot optical filters. In the situation of frequency misalignment, the impairment caused by filters is more serious. Our research shows that with a frequency deviation of 5 GHz, only 12 and 9 Butterworth optical filters can be cascaded in 40 Gbps NRZ-DQPSK and 100 Gbps PM-NRZ-DQPSK systems respectively. We also study the signal impairment caused by different orders of the Butterworth filter model. Our study shows that although the higher-order has a smaller clipping effect in the transmission spectrum, it will introduce a more serious phase ripple which seriously affects the signal. Simulation result shows that the 2nd order Butterworth filter has the best performance.

Analysis of signal impairment and crosstalk penalty induced by different types of optical filters in 100 Gbps PM-DQPSK based systems

Optical filters are crucial elements in optical communication networks. Their influence toward the optical signal will affect the communication quality seriously. In this paper we will study and simulate the optical signal impairment and crosstalk penalty caused by different kinds of filters, which include Butterworth, Bessel, Fiber Bragg Grating (FBG) and Fabry-Perot (F-P). Signal impairment from filter concatenation effect and crosstalk penalty from out-band and in-band are analyzed from Q-penalty, eye opening penalty (EOP) and optical spectrum. The simulation results show that signal impairment and crosstalk penalty induced by the Butterworth filter is the minimum among these four types of filters. Signal impairment caused by filter concatenation effect shows that when center frequency of all filters is aligned perfectly with the laser's frequency, 12 50-GHz Butterworth filters can be cascaded, with 1-dB EOP. This value is reduced to 9 when the center frequency is misaligned with 5 GHz. In the 50-GHz channel spacing DWDM networks, total Q-penalty induced by a pair of Butterworth filters based demultiplexer and multiplexer is lower than 0.5 dB when the filter bandwidth is in the range of 42-46 GHz.

Improving the pass-band return loss in liquid crystal dual-mode bandpass filters by microstrip patch reshaping

In this paper, the design and experimental characterization of a tunable microstrip bandpass filter based on liquid crystal technology are presented. A reshaped microstrip dual-mode filter structure has been used in order to improve the device performance. Specifically, the aim is to increase the pass-band return loss of the filter by narrowing the filter bandwidth. Simulations confirm the improvement of using this new structure, achieving a pass-band return loss increase of 1.5 dB at least. Because of the anisotropic properties of LC molecules, a filter central frequency shift from 4.688 GHz to 5.045 GHz, which means a relative tuning range of 7.3%, is measured when an external AC voltage from 0 Vrms to 15 Vrms is applied to the device.