Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Completion problems for real matrices, II

Thirty years ago, G.N. de Oliveira has proposed the following completion problems: Describe the possible characteristic polynomials of [C-ij], i,j is an element of {1, 2}, where C-1,C-1 and C-2,C-2 are square submatrices, when some of the blocks C-ij are fixed and the others vary. Several of these problems remain unsolved. This paper gives the solution, over the field of real numbers, of Oliveira's problem where the blocks C-1,C-1, C-2,C-2 are fixed and the others vary.

Performance of microstrip antennas in the presence of EBG in an indoor localization system

Indoor localization systems in nowadays is a huge area of interest not only at academic but also at industry and commercial level. The correct location in these systems is strongly influenced by antennas performance which can provide several gains, bandwidths, polarizations and radiation patterns, due to large variety of antennas types and formats. This paper presents the design, manufacture and measurement of a compact microstrip antenna, for a 2.4 GHZ frequency band, enhanced with the use of Electromagnetic Band-Gap (EBG) structures, which improve the electromagnetic behavior of the conventional antennas. The microstrip antenna with an EBG structure integrated allows an improvement of the location system performance in about 25% to 30% relatively to a conventional microstrip antenna.

Positive solutions of fourth order problems with clamped beam boundary conditions

n this paper we make an exhaustive study of the fourth order linear operator u((4)) + M u coupled with the clamped beam conditions u(0) = u(1) = u'(0) = u'(1) = 0. We obtain the exact values on the real parameter M for which this operator satisfies an anti-maximum principle. Such a property is equivalent to the fact that the related Green's function is nonnegative in [0, 1] x [0, 1]. When M < 0 we obtain the best estimate by means of the spectral theory and for M > 0 we attain the optimal value by studying the oscillation properties of the solutions of the homogeneous equation u((4)) + M u = 0. By using the method of lower and upper solutions we deduce the existence of solutions for nonlinear problems coupled with this boundary conditions. (C) 2011 Elsevier Ltd. All rights reserved.

Water quality issues in rivers, lakes and reservoirs in Asian countries: an approach to the problems and the methodologies

Water covers over 70% of the Earth's surface, and is vital for all known forms of life. But only 3% of the Earth's water is fresh water, and less than 0.3% of all freshwater is in rivers, lakes, reservoirs and the atmosphere. However, rivers and lakes are an important part of fresh surface water, amounting to about 89%. In this Master Thesis dissertation, the focus is on three types of water bodies – rivers, lakes and reservoirs, and their water quality issues in Asian countries. The surface water quality in a region is largely determined both by the natural processes such as climate or geographic conditions, and the anthropogenic influences such as industrial and agricultural activities or land use conversion. The quality of the water can be affected by pollutants discharge from a specific point through a sewer pipe and also by extensive drainage from agriculture/urban areas and within basin. Hence, water pollutant sources can be divided into two categories: Point source pollution and Non-point source (NPS) pollution. Seasonal variations in precipitation and surface run-off have a strong effect on river discharge and the concentration of pollutants in water bodies. For example, in the rainy season, heavy and persistent rain wash off the ground, the runoff flow increases and may contain various kinds of pollutants and, eventually, enters the water bodies. In some cases, especially in confined water bodies, the quality may be positive related with rainfall in the wet season, because this confined type of fresh water systems allows high dilution of pollutants, decreasing their possible impacts. During the dry season, the quality of water is largely related to industrialization and urbanization pollution. The aim of this study is to identify the most common water quality problems in Asian countries and to enumerate and analyze the methodologies used for assessment of water quality conditions of both rivers and confined water bodies (lakes and reservoirs). Based on the evaluation of a sample of 57 papers, dated between 2000 and 2012, it was found that over the past decade, the water quality of rivers, lakes, and reservoirs in developing countries is being degraded. Water pollution and destruction of aquatic ecosystems have caused massive damage to the functions and integrity of water resources. The most widespread NPS in Asian countries and those which have the greatest spatial impacts are urban runoff and agriculture. Locally, mine waste runoff and rice paddy are serious NPS problems. The most relevant point pollution sources are the effluents from factories, sewage treatment plant, and public or household facilities. It was found that the most used methodology was unquestionably the monitoring activity, used in 49 of analyzed studies, accounting for 86%. Sometimes, data from historical databases were used as well. It can be seen that taking samples from the water body and then carry on laboratory work (chemical analyses) is important because it can give an understanding of the water quality. 6 papers (11%) used a method that combined monitoring data and modeling. 6 papers (11%) just applied a model to estimate the quality of water. Modeling is a useful resource when there is limited budget since some models are of free download and use. In particular, several of used models come from the U.S.A, but they have their own purposes and features, meaning that a careful application of the models to other countries and a critical discussion of the results are crucial. 5 papers (9%) focus on a method combining monitoring data and statistical analysis. When there is a huge data matrix, the researchers need an efficient way of interpretation of the information which is provided by statistics. 3 papers (5%) used a method combining monitoring data, statistical analysis and modeling. These different methods are all valuable to evaluate the water quality. It was also found that the evaluation of water quality was made as well by using other types of sampling different than water itself, and they also provide useful information to understand the condition of the water body. These additional monitoring activities are: Air sampling, sediment sampling, phytoplankton sampling and aquatic animal tissues sampling. Despite considerable progress in developing and applying control regulations to point and NPS pollution, the pollution status of rivers, lakes, and reservoirs in Asian countries is not improving. In fact, this reflects the slow pace of investment in new infrastructure for pollution control and growing population pressures. Water laws or regulations and public involvement in enforcement can play a constructive and indispensable role in environmental protection. In the near future, in order to protect water from further contamination, rapid action is highly needed to control the various kinds of effluents in one region. Environmental remediation and treatment of industrial effluent and municipal wastewaters is essential. It is also important to prevent the direct input of agricultural and mine site runoff. Finally, stricter environmental regulation for water quality is required to support protection and management strategies. It would have been possible to get further information based in the 57 sample of papers. For instance, it would have been interesting to compare the level of concentrations of some pollutants in the diferente Asian countries. However the limit of three months duration for this study prevented further work to take place. In spite of this, the study objectives were achieved: the work provided an overview of the most relevant water quality problems in rivers, lakes and reservoirs in Asian countries, and also listed and analyzed the most common methodologies.

An Evaluation of Local Feature Combiners for Robot Visual Localization

In the last decade, local image features have been widely used in robot visual localization. To assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image to those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, we compare several candidate combiners with respect to their performance in the visual localization task. A deeper insight into the potential of the sum and product combiners is provided by testing two extensions of these algebraic rules: threshold and weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance. The voting method, whilst competitive to the algebraic rules in their standard form, is shown to be outperformed by both their modified versions.

Phex: a computational tool for plate heat exchanges design problems

This paper presents a computational tool (PHEx) developed in Excel VBA for solving sizing and rating design problems involving Chevron type plate heat exchangers (PHE) with 1-pass-1-pass configuration. The rating methodology procedure used in the program is outlined, and a case study is presented with the purpose to show how the program can be used to develop sensitivity analysis to several dimensional parameters of PHE and to observe their effect on transferred heat and pressure drop.

2D PCA-Based localization for mobile robots in unstructured environments

In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Pentagonal parch-excited sectorized antenna for localization systems

A pentagonal patch-excited sectorized antenna (SA) suitable for 2.4-2.5 GHz localization systems was studied and developed. The integration of six patch-excited structures converges into a sectorized antenna called Hive5 that provides gain improvement compared to a patch antenna, maximum variation of 3 dB beam width over the radiation pattern and circular polarization (CP). This antenna is presented and analyzed taking into account the tap length and the flare angle. The proposed antenna in combination with a RF-Switch provides a cost effective solution for localization based on Wireless Sensor Networks (WSN) and will be used for implementing angle of arrival (AoA) techniques combined with RF fingerprinting techniques.

Enhanced PCA-based localization using depth maps with missing data

In this paper a new method for self-localization of mobile robots, based on a PCA positioning sensor to operate in unstructured environments, is proposed and experimentally validated. The proposed PCA extension is able to perform the eigenvectors computation from a set of signals corrupted by missing data. The sensor package considered in this work contains a 2D depth sensor pointed upwards to the ceiling, providing depth images with missing data. The positioning sensor obtained is then integrated in a Linear Parameter Varying mobile robot model to obtain a self-localization system, based on linear Kalman filters, with globally stable position error estimates. A study consisting in adding synthetic random corrupted data to the captured depth images revealed that this extended PCA technique is able to reconstruct the signals, with improved accuracy. The self-localization system obtained is assessed in unstructured environments and the methodologies are validated even in the case of varying illumination conditions.