Πλοήγηση κινούμενου ρομπότ σε άγνωστο περιβάλλον προς ένα προκαθορισμένο στόχο

90 σ.Η παρούσα διπλωματική εργασία περιγράφει μια υλοποίηση ενός συστήματος αλληλεπίδρασης ανθρώπου υπολογιστή για ευφυή ρομπότ. Αποσκοπεί στο να προσφέρει την ικανότητα σε ένα κινούμενο ρομπότ εσωτερικού χώρου να κατανοήσει και να εκτελέσει οδηγίες πλοήγησης δοσμένες σε μια ψευδο-ανθρώπινη γλώσσα. Το ρομπότ τοποθετείται σε άγνωστο περιβάλλον εσωτερικού χώρου και του δίνονται οδηγίες όπως "Πήγαινε στο τρίτο γραφείο δεξιά". Για να επιτύχει το σκοπό του, το ρομπότ πρέπει να έχει τη δυνατότητα να φτιάξει ένα χάρτη του περιβάλλοντος και να προσδιορίσει τη θέση του μέσα σε αυτό. Για το σκοπό αυτό χρησιμοποιούνται τεχνικές Simultaneous Localisation And Mapping (SLAM). Δύο σημαντικές καινοτόμες προκλήσεις αντιμετωπίζονται. Αρχικά, η πλοήγηση προς ένα στόχο διαμέσου ενός άγνωστου χάρτη, και κατά δεύτερον, το πόσο χρήσιμος και ενημερωτικός είναι ο χάρτης. Ο κύριος στόχος των υφιστάμενων τεχνικών πλοήγησης είναι να οδηγήσουν το ρομπότ προς την άγνωστη περιοχή του χάρτη ώστε να ελαχιστοποιήσουν το περιβάλλον που δεν έχει επισκευθεί ακόμα. Αυτό δεν είναι αρκετό αν το ρομπότ πρέπει να κινηθεί προς ένα προκαθορισμένο στόχο. Για να επιτευχθεί αυτού του είδους η συμπεριφορά, έχει επανασχεδιαστεί μια υφιστάμενη τεχνική πλοήγησης. Επιπρόσθετα, το ρομπότ θα πρέπει να αναγνωρίσει τις οντότητες που υποδηλώνονται από τις οδηγίες που δίνει ο άνθρωπος. Για να επιτευχθεί αυτό, δημιουργείται ένας χάρτης οντοτήτων όπως πόρτα, καρέκλα, κιβώτιο κλπ. και δίνεται στο ρομπότ. Για να αναγνωριστούν αυτές οι οντότητες, θα μπορούσαν να χρησιμοποιηθούν τεχνικές αναγνώρισης προτύπων. Το αποτέλεσμα είναι ένας χάρτης αντικειμένων που μπορεί να χρησιμοποιηθεί όχι μόνο για πλοήγηση, αλλά και για καλύτερη απεικόνιση του χάρτη.This thesis project describes an implementation of a Human Computer Interaction (HCI) system for intelligent mobile robots. It aims to provide the ability to indoor mobile robots to understand and execute direction orders described in a pseudo-human language. The robot is positioned in an unknown indoor environment and it is given directions like ”Go to the third office on your right”. To achieve that, the robot should be able to create a map of its environment and localise itself in the map. Thus, Simultaneous Localisation And Mapping (SLAM) techniques are used. Two key novel challenges are confronted. Firstly, the navigation towards a target in a yet unknown map, and secondly, how informative and useful the map is. The main objective of existing navigation techniques, is to drive the robot towards the unknown area of the map in order to minimise the yet unseen environment. That is not enough if the robot must move towards a predefined target. In order to achieve this kind of behaviour, an existing navigation technique is augmented. Secondly, the robot should be able to recognise entities that signify the way-points given by the human. To cope with that, a map of entities like door, chair, box, etc. is created and provided to to the robot. To identify these entities, pattern recognition techniques may be employed. The result is a map of objects that can be used not only for navigation and path planning, but also for a better illustration of the actual map.Χαράλαμπος Μ. Ρωσσίδη

The dynamics of interacting multi-pulses in the one-dimensional quintic complex Ginzburg-Landau equation

We formulate an effective numerical scheme that can readily, and accurately, calculate the dynamics of weakly interacting multi-pulse solutions of the quintic complex Ginzburg-Landau equation (QCGLE) in one space dimension. The scheme is based on a global centre-manifold reduction where one considers the solution of the QCGLE as the composition of individual pulses plus a remainder function, which is orthogonal to the adjoint eigenfunctions of the linearised operator about a single pulse. This centre-manifold projection overcomes the difficulties of other, more orthodox, numerical schemes, by yielding a fast-slow system describing 'slow' ordinary differential equations for the locations and phases of the individual pulses, and a 'fast' partial differential equation for the remainder function. With small parameter $\epsilon=e^{-\lambda_r d}$ where $\lambda_r$ is a constant and $d>0$ is the pulse separation distance, we write the fast-slow system in terms of first-order and second-order correction terms only, a formulation which is solved more efficiently than the full system. This fast-slow system is integrated numerically using adaptive time-stepping. Results are presented here for two- and three-pulse interactions. For the two-pulse problem, cells of periodic behaviour, separated by an infinite set of heteroclinic orbits, are shown to 'split' under perturbation creating complex spiral behaviour. For the case of three pulse interaction a range of dynamics, including chaotic pulse interaction, are found. While results are presented for pulse interaction in the QCGLE, the numerical scheme can also be applied to a wider class of parabolic PDEs.Comment: 33 page

Cost Optimization of Ice Distribution

Two questions regarding minimizing fuel costs while delivering ice along a pre-set route are tackled. The first question is when demand exceeds the load of a single truck, so that a second truck of ice has to be taken to some point of the route for the driver/salesman to continue with that for the rest of the route: Is it better: 1) for the first truck to deliver starting from the costumer nearest to the base, or 2) for the first truck to start the delivery from the last costumer (the most distant from the base)? We show that the second strategy was better for the particular data looked at, and we have the basis of an algorithm for deciding which strategy is the better for a given delivery schedule. The second question concerns how best to modify a regular sales route when an extra delivery has to be made. Again, the basis for an algorithm to decide how to minimize fuel costs is derived

Genetic Basis of Myocarditis: Myth or Reality?

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Objective and repeatable image quality assessment with Gaussian mixture models

Quantifying image quality enables objective optimisation of imaging protocols. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measure visibility of features in relation to the image noise. Conventional SNR and CNR measurement is performed by user selection of regions in the image representing each material, which is not repeatable and impractical for large numbers of 3D datasets. Here, a semi-automated, objective and repeatable method of calculating SNR and CNR is presented which does not require user definition of regions-of-interest. This method utilises Gaussian mixture models to separate materials in the specimen based on the grey value distribution of the image. This tool is available as a graphical user interface for Fiji/ImageJ users, and as importable libraries for Python users under the GNU General Public License v3.0

Objective and repeatable image quality assessment with Gaussian mixture models

Quantifying image quality enables objective optimisation of imaging protocols. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measure visibility of features in relation to the image noise. Conventional SNR and CNR measurement is performed by user selection of regions in the image representing each material, which is not repeatable and impractical for large numbers of 3D datasets. Here, a semi-automated, objective and repeatable method of calculating SNR and CNR is presented which does not require user definition of regions-of-interest. This method utilises Gaussian mixture models to separate materials in the specimen based on the grey value distribution of the image. This tool is available as a graphical user interface for Fiji/ImageJ users, and as importable libraries for Python users under the GNU General Public License v3.0. </span

Effects of fast x-ray cone-beam tomographic measurement on dimensional metrology

Abstract X-ray computed tomography (XCT) is increasingly used for dimensional metrology, where it can offer accurate measurements of internal features that are not accessible with other techniques. However, XCT scanning can be relatively slow, which often prevents routine uptake for many applications. This paper explores the feasibility of improving the speed of XCT measurements while maintaining the quality of the dimensional measurements derived from reconstructed volumes. In particular, we compare two approaches to fast XCT acquisition, the use of fewer XCT projections as well as the use of shortened x-ray exposure times for each projection. The study shows that the additional Poisson noise produced by reducing the exposure for each projection has significantly less impact on dimensional measurements compared to the artefacts associated with strategies that take fewer projection images, leading to about half the measurement error variability. Advanced reconstruction algorithms such as the conjugate gradient least squares method or total variation constrained approaches, are shown to allow further improvements in measurement speed, though this can come at the cost of increased measurement bias (e.g. 2.8% increase in relative error in one example) and variance (e.g. 25% in the same example).</jats:p

747P Real-world experience of rucaparib in patients with ovarian cancer: A multicentre United Kingdom study

Background Epithelial Ovarian Cancer (EOC) is the 5th leading cause of female cancer deaths. Despite high responses to first-line therapy, 5-year survival remains poor at 29%. Rucaparib is a small molecule PARP inhibitor (PARPi) approved as monotherapy for maintenance treatment of recurrent EOC with prior complete/partial response to platinum-based chemotherapy, on the basis of the ARIEL3 trial. Despite the validity of clinical trial evidence, applicability to routine practice is limited and real-world evidence (RWE) is mandated. Methods We performed a multi-center retrospective study of patients with advanced EOC receiving rucaparib in the UK from June 2018, via an early access program. Results 119 patients were included, with a median age of 66 years (range 26-89). Median ECOG at commencement was 1 (0-3). 91% (n=108) had high grade serous carcinoma and 24% (n=29) germline/somatic BRCA1/2mutation (BRCAm). Prior to rucaparib, patients had a median of 3 therapies (range 1-9) with 8% (n=10) receiving an alternate PARPi. Overall progression free survival (PFS) was 7.5 months (1.1-37.4), with a higher PFS of 9.1 months (1.1-35.5) in BRCAm patients. This is lower than observed in ARIEL3. However, if similar inclusion/exclusion criteria are applied to our RWE population, findings are analogous, with PFS of 10.2 and 16.6 months in the overall and BRCAm groups respectively. Treatment-related toxicity (any grade) was reported in 88% (n=105) of patients, most prevalent being nausea, fatigue, anaemia and other blood dyscrasias. 26% (n=32) of patients experienced a CTCAE grade 3/4 toxicity and 58% (n=69) required dose interruption/reduction. 13% (n=16) of patients discontinued therapy due to a treatment related adverse effect: most frequently fatigue, nausea or thrombocytopenia. No haematological malignancies were observed. Conclusions Overall we found a lower incidence of any grade and grade 3/4 toxicity, and furthermore equivalent discontinuation rates to ARIEL3. A lower overall PFS and BRCAm PFS was observed. This is likely due to the inclusion of patients with higher ECOG, median age, prior therapy lines and previous PARPi use. However, applying similar inclusion/exclusion criteria to the RWE population, recapitulates similar PFS findings to ARIEL3. Legal entity responsible for the study The authors. Funding Has not received any funding