towards intelligent autonomous sorting of unclassified nuclear wastes

Sorting of old and mixed nuclear waste is an essential process in nuclear decommissioning operations. The main bottleneck is manual picking and separation of the materials using remotely operated arms, which is slow and error prone especially with small items. Automation of the process is therefore desirable. In the framework of the newly funded European project ECHORD++, experiment RadioRoSo, a pilot robotic cell is being developed and validated against industrial requirements on a range of sorting tasks. Industrial robots, custom gripper, vision feedback and new manipulation skills will be developed. This paper presents application context, cell layout and sorting approach

The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas

Tuberous sclerosis complex (TSC) is an autosomal dominantly inherited neurocutaneous disorder caused by inactivating mutations in TSC1 or TSC2, key regulators of the mechanistic target of rapamycin complex 1 (mTORC1) pathway. In the CNS, TSC is characterized by cortical tubers, subependymal nodules and subependymal giant cell astrocytomas (SEGAs). SEGAs may lead to impaired circulation of CSF resulting in hydrocephalus and raised intracranial pressure in patients with TSC. Currently, surgical resection and mTORC1 inhibitors are the recommended treatment options for patients with SEGA. In the present study, high-throughput RNA-sequencing (SEGAs n = 19, periventricular control n = 8) was used in combination with computational approaches to unravel the complexity of SEGA development. We identified 9400 mRNAs and 94 microRNAs differentially expressed in SEGAs compared to control tissue. The SEGA transcriptome profile was enriched for the mitogen-activated protein kinase (MAPK) pathway, a major regulator of cell proliferation and survival. Analysis at the protein level confirmed that extracellular signal-regulated kinase (ERK) is activated in SEGAs. Subsequently, the inhibition of ERK independently of mTORC1 blockade decreased efficiently the proliferation of primary patient-derived SEGA cultures. Furthermore, we found that LAMTOR1, LAMTOR2, LAMTOR3, LAMTOR4 and LAMTOR5 were overexpressed at both gene and protein levels in SEGA compared to control tissue. Taken together LAMTOR1-5 can form a complex, known as the 'Ragulator' complex, which is known to activate both mTORC1 and MAPK/ERK pathways. Overall, this study shows that the MAPK/ERK pathway could be used as a target for treatment independent of, or in combination with mTORC1 inhibitors for TSC patients. Moreover, our study provides initial evidence of a possible link between the constitutive activated mTORC1 pathway and a secondary driver pathway of tumour growth

Geometric and photometric image stabilization for detection of significant events in video from a low flying Unmanned Aerial Vehicles

Analysis and interpretation of the information present in a video stream from aerial surveys is demanding and time-consuming even for experts. On-line video sequences acquired by cameras on board of a small surveillance plane are very unstable. The brightness and contrast of the images are rapidly changing due to fast changes in illumination and the content of the scene. The movement of the small plane is non-uniform and it depends on the wind and other weather conditions

Estimation of Differential Structures on Triangulated Surfaces

This paper presents a method for extracting differential structures on 3D surfaces and describes an algorithm for estimation of principal curvatures and principal directions from 3D scanned data. The method serves as a base for the extracting intrinsic curves on the surface. The differential structures are intended for matching partially overlapping range images. The search for a deferential structure which is represented by the curves of inflection points is based on estimation of differential parameters of the surface. Therefore, the reliable estimation of differential parameters is necessary. The estimation of differential parameters consists of two steps. First, the measured points are locally approximated by an osculating paraboloid. The differential parameters of the paraboloid are considered as an initial estimate of the parameters of the original surface. Then, the initial estimate is further refined using estimated parameters from the neighbourhood of each point

Range Image Registration Driven By A Hierarchy Of Surface Differential Features

This work proposes a way how to register overlapping range images automatically. We explore the fact that the Euclidean transformation is determined by three pairs of corresponding points only. The main idea of the proposed approach is to reduce the number of points by finding intrinsic (significant) ones first. For that, differential structures of the surface as curves of zero-mean curvature which are invariant to Euclidean transformation are used. The differential structures on a surface provide us with a hierarchy of intrinsic features, i.e. in a top down manner: surface ! curves ! points. The first estimate of the Euclidean transform is done using points then it is refined on curves and finally improved on surfaces. The performance of the approach is satisfactory for complicated surfaces which have rich differential structure

Range Image Registration Driven by a Hierarchy of Surfaces

One of the 3-D vision tasks is to create a full 3-D model of an object. Only the partial range images from different view points can be obtained by real range finders. it is possible to get partially overlapped rang images. The views differ by Euclidean motion. This motions have to be known for combining the views. This article describes a method for registration of range images. Our algorithm is based on matching of differential structures of the surface. Results of this algorithm are used as first estimate in the distance minimization algorithm -- Iterative Closest Reciprocal Points (ICRP). Such approach produces more accurate results and solves some problems of ICRP algorithm

Registrace hloubkovych map na zaklade diferencialnich invariantnich struktur.

The thesis deals with the problem of registering two range images of the same 3D scene captured from two different points. Such a task is of practical importance, e.g. in reverse engineering in the automotive industry or elsewhere. A 3D CAD model is created from a 3D specimen of an object by capturing a set of overlapping range images that are later transformed into one coordinate system. The 3D model is then created by fusing all range images covering the object's surface. Our work addresses the problem of 3D model reconstruction from overlapping triangulated range images. A technique for automatic matching of curved free form surfaces exploiting curvilinear differential structures of the surfaces is presented. We propose a novel hybrid registration algorithm for automatic matching of curved free form surfaces. A pair of range images is registered based on significant curvilinear characteristics of the surface. It is assumed that all information needed to find the cccEuclidian transformation is to be found in the data. The algorithm combines advantages of working with small amount of interest points, it estimates the Euclidean transform matching both surfaces and uses all available points and the Iterative Reciprocal Point algorithm is used to refine the estimate and finally it matches surfaces. The method works in a bottom up and reversely manner utilizing the hierarchy surfaces -differential structures - significant points. The registration is automatic.Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi

Single arm robotic garment folding path generation

<p>We address the accurate single arm robotic garment folding. The folding capability is influenced mostly by the folding path which is performed by the robotic arm. This paper presents a new method for the folding path generation based on the static equilibrium of forces. The existing approach based on a similar principle confirmed to be accurate for one-dimensional strips only. We generalize the method to two-dimensional shapes by modeling the garment as an elastic shell. The path generated by our method prevents the garment from slipping while folding on a low friction surface. We demonstrate the accuracy of this approach by comparing our paths (a) with the existing method when one-dimensional strips of different materials were modeled, and (b) experimentally with real robotic folding.</p> <p>The paper proposes a robotic garment folding path generation procedure. It uses the garment model represented by a thin shell. The path computation seeks states satisfying a static equilibrium condition.</p