Local map update for large scale SLAM

A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Problems with large groups

A list of considerations on the problems with large groups. This material was sent to Debra Morris in 2007, by David Jaques, an educationist with many years' experience of working with groups.

Large Scale Structure of Metric Spaces

How the mathematical concept of Coarse Geometries is useful to analysing the Web

Online Discussions Replacing Tutorials for Large Cohorts - Melanie Ashleigh

This is one of a series of short case studies describing how academic tutors at the University of Southampton have made use of learning technologies to support their students.

Online Discussions for Large Cohorts - Ian Harwood

This is one of a series of short case studies describing how academic tutors at the University of Southampton have made use of learning technologies to support their students.

Large heterogeneous classes. 'Clases heterog??neas'

El art??culo es un resumen de la propia autora sobre la conferencia realizada en la sede del CDL. Contiene una presentaci??n en catal??n, realizada por Aina Carreras

Modelling for Problem Solving in the Large

This a short presentation which introduces how models and modelling help us to solve large scale problems in the real world. It introduces the idea that dynamic behaviour is caused by interacting components in the system. Feedback in the system makes behaviour prediction difficult unless we use modelling to support understanding

Dynamic programming for stochastic target problems, Viscosity solutions and hedging in markets with Portfolio constraints and large investors

The purpose of this expository arti le is to present a self- ontained overview of some results on the hara terization of the optimal value fun tion of a sto hasti target problem as (dis ontinuous) vis osity solution of a ertain dynami programming PDE and its appli ation to the problem of hedging ontingent laims in the presen e of portfolio onstraints and large investors

Bees.

La obra, aprobada por expertos en educación, trata temas reales de la vida. El lenguaje sencillo que se utiliza ayuda al niño a desarrollar su interés por la lectura y la curiosidad por el mundo en que vive. Tiene glosario alfabético.

Teaching large multilevel classes.

Este es un manual diseñado para profesores de clases de niveles múltiples de gran tamaño. Contiene una serie de actividades especialmente creadas para hacer frente a todas las dificultades que surgen en este contexto. Muchas actividades pueden ser utilizadas con éxito también en clases más pequeñas y más homogéneas. Las actividades están seleccionadas según un criterio diferente: cómo despertar el interés de los estudiantes; cómo personalizar e individualizar su trabajo; cómo promover la colaboración; cómo hacer que los estudiantes tomen conciencia de su aprendizaje; cómo lograr una gestión positiva de clase. El autor señala cómo la variedad también puede conducir al desorden y lo importante que es crear y respetar las normas y rutinas, cruciales para la buena gestión de la clase. No se olvida de crear un sentido de pertenencia a un grupo, que es extremadamente importante en las clases grandes, donde los estudiantes tímidos o más débiles podrían sentirse excluidos. El trabajo en grupo se mezcla con el trabajo individual y una vez más el autor demuestra ser comprensivo hacia los sentimientos de los estudiantes, fomenta la individualización y la personalización, junto con actividades de grupo. Las actividades siempre están diseñadas para mantener un equilibrio entre individuo y grupo. El profesor dirige el grupo, mantiene todo bajo control y es el punto de referencia para todos los estudiantes, y al mismo tiempo interactúa con el grupo. De hecho los estudiantes de nivel superior pueden llegar a ser de gran ayuda para los más débiles, creando así una especie de cadena de aprendizaje. Muchas actividades están destinadas a que los estudiantes tomen conciencia de sus estilos de aprendizaje y sean responsables de su propio aprendizaje, y para evaluar su propio progreso.

Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants

Treatment of nonlinear optical properties due to large amplitude anharmonic vibrational motions: umbrella motion in NH3

A general reduced dimensionality finite field nuclear relaxation method for calculating vibrational nonlinear optical properties of molecules with large contributions due to anharmonic motions is introduced. In an initial application to the umbrella (inversion) motion of NH3 it is found that difficulties associated with a conventional single well treatment are overcome and that the particular definition of the inversion coordinate is not important. Future applications are described

Efficient topology estimation for large scale optical mapping

Large scale image mosaicing methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that lowcost Remotely operated vehicles (ROVs) usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predetermined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This thesis presents a set of consistent methods aimed at creating large area image mosaics from optical data obtained during surveys with low-cost underwater vehicles. First, a global alignment method developed within a Feature-based image mosaicing (FIM) framework, where nonlinear minimisation is substituted by two linear steps, is discussed. Then, a simple four-point mosaic rectifying method is proposed to reduce distortions that might occur due to lens distortions, error accumulation and the difficulties of optical imaging in an underwater medium. The topology estimation problem is addressed by means of an augmented state and extended Kalman filter combined framework, aimed at minimising the total number of matching attempts and simultaneously obtaining the best possible trajectory. Potential image pairs are predicted by taking into account the uncertainty in the trajectory. The contribution of matching an image pair is investigated using information theory principles. Lastly, a different solution to the topology estimation problem is proposed in a bundle adjustment framework. Innovative aspects include the use of fast image similarity criterion combined with a Minimum spanning tree (MST) solution, to obtain a tentative topology. This topology is improved by attempting image matching with the pairs for which there is the most overlap evidence. Unlike previous approaches for large-area mosaicing, our framework is able to deal naturally with cases where time-consecutive images cannot be matched successfully, such as completely unordered sets. Finally, the efficiency of the proposed methods is discussed and a comparison made with other state-of-the-art approaches, using a series of challenging datasets in underwater scenarios