Image-Based Monte-Carlo Localisation without a Map

In this paper, we propose a way to fuse the image-based localisation approach with the Monte-Carlo localisation approach. The method we propose does not suffer of the major limitation of the two separated methods: the need of a metric map of the environment for the Monte-Carlo localisation and the failure of the image-based approach in environments with spatial periodicity (perceptual aliasing). The approach we developed exploits the properties of the Fourier Transform of the omnidirectional images and uses the similarity between the images to weights the beliefs about the robot position. Successful experiments in large indoor environment are presented in which we do not used a priory information on the metrical map of the environment

The effect of hot days on occupational heat stress in the manufacturing industry: implications for workers' well-being and productivity

Climate change is expected to exacerbate heat stress at the workplace in temperate regions, such as Slovenia. It is therefore of paramount importance to study present and future summer heat conditions and analyze the impact of heat on workers. A set of climate indices based on summer mean (Tmean) and maximum (Tmax) air temperatures, such as the number of hot days (HD: Tmax above 30 °C), and Wet Bulb Globe Temperature (WBGT) were used to account for heat conditions in Slovenia at six locations in the period 1981–2010. Observed trends (1961–2011) of Tmean and Tmax in July were positive, being larger in the eastern part of the country. Climate change projections showed an increase up to 4.5 °C for mean temperature and 35 days for HD by the end of the twenty-first century under the high emission scenario. The increase in WBGT was smaller, although sufficiently high to increase the frequency of days with a high risk of heat stress up to an average of a third of the summer days. A case study performed at a Slovenian automobile parts manufacturing plant revealed non-optimal working conditions during summer 2016 (WBGT mainly between 20 and 25 °C). A survey conducted on 400 workers revealed that 96% perceived the temperature conditions as unsuitable, and 56% experienced headaches and fatigue. Given these conditions and climate change projections, the escalating problem of heat is worrisome. The European Commission initiated a program of research within the Horizon 2020 program to develop a heat warning system for European workers and employers, which will incorporate case-specific solutions to mitigate heat stress.The work was supported by the European Union Horizon 2020 Research and Innovation Action (Project number 668786: HEATSHIELD)

Evaluation of residence time on nitrogen oxides removal in non-thermal plasma reactor

Non-thermal plasma (NTP) has been introduced over the last few years as a promising after- treatment system for nitrogen oxides and particulate matter removal from diesel exhaust. NTP technology has not been commercialised as yet, due to its high rate of energy consumption. Therefore, it is important to seek out new methods to improve NTP performance. Residence time is a crucial parameter in engine exhaust emissions treatment. In this paper, different electrode shapes are analysed and the corresponding residence time and NOx removal efficiency are studied. An axisymmetric laminar model is used for obtaining residence time distribution numerically using FLUENT software. If the mean residence time in a NTP plasma reactor increases, there will be a corresponding increase in the reaction time and consequently the pollutant removal efficiency increases. Three different screw thread electrodes and a rod electrode are examined. The results show the advantage of screw thread electrodes in comparison with the rod electrode. Furthermore,between the screw thread electrodes, the electrode with the thread width of 1 mm has the highest NOx removal due to higher residence time and a greater number of micro-discharges. The results show that the residence time of the screw thread electrode with a thread width of 1 mm is 21% more than for the rod electrode

Illumination Insensitive Robot Self-Localization Using Panoramic Eigenspaces

Abstract. We propose to use a robust method for appearance-based matching that has been shown to be insensitive to illumination and oc-clusion for robot self-localization. The drawback of this method is that it relies on panoramic images taken in one certain orientation, restricts the heading of the robot throughout navigation or needs additional sen-sors for orientation, e.g. a compass. To avoid these problems we propose a combination of the appearance-based method with odometry data. We demonstrate the robustness of the proposed self-localization against changes in illumination by experimental results obtained in the RoboCup Middle-Size scenario.

A Robust PCA Algorithm for Building Representations from Panoramic Images

Appearance-based modeling of objects and scenes using PCA has been successfully applied in many recognition tasks. Robust methods which have made the recognition stage less susceptible to outliers, occlusions, and varying illumination have further enlarged the domain of applicability. However, much less research has been done in achieving robustness in the learning stage. In this paper, we propose a novel robust PCA method for obtaining a consistent subspace representation in the presence of outlying pixels in the training images. The method is based on the EM algorithm for estimation of principal subspaces in the presence of missing data. By treating the outlying points as missing pixels, we arrive at a robust PCA representation. We demonstrate experimentally that the proposed method is efficient. In addition, we apply the method to a set of panoramic images to build a representation that enables surveillance and view-based mobile robot localization

A Robust PCA Algorithm for Building Representations from Panoramic Images

Appearance-based modeling of objects and scenes using PCA has been successfully applied in many recognition tasks. Robust methods which have made the recognition stage less susceptible to outliers, occlusions, and varying illumination have further enlarged the domain of applicability. However, much less research has been done in achieving robustness in the learning stage. In this paper, we propose a novel robust PCA method for obtaining a consistent subspace representation in the presence of outlying pixels in the training images. The method is based on the EM algorithm for estimation of principal subspaces in the presence of missing data. By treating the outlying points as missing pixels, we arrive at a robust PCA representation. We demonstrate experimentally that the proposed method is efficient. In addition, we apply the method to a set of panoramic images to build a representation that enables surveillance and view-based mobile robot localization

Break zones in the distributions of alleles and species in alpine plants

Aim  We test for the congruence between allele-based range boundaries (break zones) in silicicolous alpine plants and species-based break zones in the silicicolous flora of the European Alps. We also ask whether such break zones coincide with areas of large elevational variation. Location  The European Alps. Methods  On a regular grid laid across the entire Alps, we determined areas of allele- and species-based break zones using respective clustering algorithms, identifying discontinuities in cluster distributions (breaks), and quantifying integrated break densities (break zones). Discontinuities were identified based on the intra-specific genetic variation of 12 species and on the floristic distribution data from 239 species, respectively. Coincidence between the two types of break zones was tested using Spearman’s correlation. Break zone densities were also regressed on topographical complexity to test for the effect of elevational variation. Results  We found that two main break zones in the distribution of alleles and species were significantly correlated. Furthermore, we show that these break zones are in topographically complex regions, characterized by massive elevational ranges owing to high mountains and deep glacial valleys. We detected a third break zone in the distribution of species in the eastern Alps, which is not correlated with topographic complexity, and which is also not evident from allelic distribution patterns. Species with the potential for long-distance dispersal tended to show larger distribution ranges than short-distance dispersers. Main conclusions  We suggest that the history of Pleistocene glaciations is the main driver of the congruence between allele-based and species-based distribution patterns, because occurrences of both species and alleles were subject to the same processes (such as extinction, migration and drift) that shaped the distributions of species and genetic lineages. Large elevational ranges have had a profound effect as a dispersal barrier for alleles during post-glacial immigration. Because plant species, unlike alleles, cannot spread via pollen but only via seed, and thus disperse less effectively, we conclude that species break zones are maintained over longer time spans and reflect more ancient patterns than allele break zones