Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

Laser shock peening treatment to control and moderate fatigue crack growth in aircraft structure based on residual stress engineering approach

Laser Shock Peening (LSP) is a surface enhancement treatment which induces a significant layer of beneficial compressive residual stresses of up to several mm underneath the surface of metal components in order to improve the detrimental effects of the crack growth behavior rate in it. The aim of this thesis is to predict the crack growth behavior in metallic specimens with one or more stripes which define the compressive residual stress area induced by the Laser Shock Peening treatment. The process was applied as crack retardation stripes perpendicular to the crack propagation direction with the object of slowing down the crack when approaching the peened stripes. The finite element method has been applied to simulate the redistribution of stresses in a cracked model when it is subjected to a tension load and to a compressive residual stress field, and to evaluate the Stress Intensity Factor (SIF) in this condition. Finally, the Afgrow software is used to predict the crack growth behavior of the component following the Laser Shock Peening treatment and to detect the improvement in the fatigue life comparing it to the baseline specimen. An educational internship at the “Research & Technologies Germany – Hamburg” department of AIRBUS helped to achieve knowledge and experience to write this thesis. The main tasks of the thesis are the following: •To up to date Literature Survey related to “Laser Shock Peening in Metallic Structures” •To validate the FE model developed against experimental measurements at coupon level •To develop design of crack growth slowdown in Centered Cracked Tension specimens based on residual stress engineering approach using laser peened strip transversal to the crack path •To evaluate the Stress Intensity Factor values for Centered Cracked Tension specimens after the Laser Shock Peening treatment via Finite Element Analysis •To predict the crack growth behavior in Centered Cracked Tension specimens using as input the SIF values evaluated with the FE simulations •To validate the results by means of experimental tests

Prokaryotic community structure in ultra-slow spreading Southwest Indian Ridge.

The Southwest Indian Ridge segment that extends between 10° and 16° E has the slowest spreading rate of any other oceanic ridge (about 8.4 mm/year). In 2013 during the expedition ANTXXIX/8 seismology, geology, microbiology, heat flow analyses were carried out. Here, no hydrothermal plumes or black smoker systems were found but the results of the survey allowed to identify areas with peculiar characteristics: Area 1 with higher heat flux bsf; Area 2 where in 2002 the presence of hydrothermal emissions was hypothesized (Bach et al., 2002); Area 3 with anomalies of methane, ammonium, sulphide and dissolved inorganic carbon in pore water sediment profiles, and recovery of fauna vents. All these aspects suggest the presence of a hydrothermal circulation. Using Illumina 16S gene tag, statistical tools and phylogenetic trees, I provided a biological proof of the presence of hydrothermal circulation in this ridge segment. At Area 3, alpha and beta diversity indexes showed similarities with those described for venting microbial communities and about 40-70% of the dominant microbial community was found phylogenetically related to clones isolated hydrothermal-driven environments. Although the majority of chemosynthetic environment related taxa were not classified like autotrophic prokaryotes, some of them are key taxa in support of the presence of hydrothermal circulation, since they are partners of consortia or mediate specific reaction typically described for hydrothermal and seep environments, or are specialized organisms in exploiting labile organic substrates. Concluding, these results are remarkable because support the importance of ultra slow spreading ridge systems in contributing to global geochemical cycles and larval dispersion of vent fauna.

Inference of Raja miraletus population structure using mitochondrial and nuclear DNA: comparing the resolution power of molecular markers in exploring species and population boundaries

This study focused on the role of oceanographic discontinuities and the presence of transitional areas in shaping the population structure and the phylogeography of the Raja miraletus species complex, coupled with the test of the effective occurrence of past speciation events. The comparisons between the Atlantic African and the North-Eastern Atlantic-Mediterranean geographic populations were unravelled using both Cytochrome Oxidase I and eight microsatellite loci. This approach guaranteed a robust dataset for the identification of a speciation event between the Atlantic African clade, corresponding to the ex Raja ocellifera nominal species, and the NE Atlantic-Mediterranean R. miraletus clade. As a matter of fact, the origin of the Atlantic Africa and the NE Atlantic-Mediterranean deep split dated about 11.74MYA and was likely due to the synergic influence currents and two upwelling areas crossing the Western African Waters. Within the Mediterranean Sea, particular attention was also paid to the transitional area represented by Adventura and Maltese Bank, that might have contributed in sustaining the connectivity of the Western and the Eastern Mediterranean geographical populations. Furthermore, the geology of the easternmost part of Sicily and the geo-morphological depression of the Calabrian Arc could have driven the differentiation of the Eastern Mediterranean Sea. Although bathymetric and oceanographic discontinuity could represent barriers to dispersal and migration between Eastern and Western Mediterranean samples, a clear and complete genetic separation among them was not detected. Results produced by this work identified a speciation event defining Raja ocellifera and R. miraletus as two different species, and describing the R. miraletus species complex as the most ancient cryptic speciation event in the family Rajidae, representing another example of how strictly connected the environment, the behavioural habits and the evolutionary and ecologic drivers are.