Techniques and potential capabilities of multi-resolutional information (knowledge) processing

A concept of nested hierarchical (multi-resolutional, pyramidal) information (knowledge) processing is introduced for a variety of systems including data and/or knowledge bases, vision, control, and manufacturing systems, industrial automated robots, and (self-programmed) autonomous intelligent machines. A set of practical recommendations is presented using a case study of a multiresolutional object representation. It is demonstrated here that any intelligent module transforms (sometimes, irreversibly) the knowledge it deals with, and this tranformation affects the subsequent computation processes, e.g., those of decision and control. Several types of knowledge transformation are reviewed. Definite conditions are analyzed, satisfaction of which is required for organization and processing of redundant information (knowledge) in the multi-resolutional systems. Providing a definite degree of redundancy is one of these conditions

Probabilistic Surfel Fusion for Dense LiDAR Mapping

With the recent development of high-end LiDARs, more and more systems are able to continuously map the environment while moving and producing spatially redundant information. However, none of the previous approaches were able to effectively exploit this redundancy in a dense LiDAR mapping problem. In this paper, we present a new approach for dense LiDAR mapping using probabilistic surfel fusion. The proposed system is capable of reconstructing a high-quality dense surface element (surfel) map from spatially redundant multiple views. This is achieved by a proposed probabilistic surfel fusion along with a geometry considered data association. The proposed surfel data association method considers surface resolution as well as high measurement uncertainty along its beam direction which enables the mapping system to be able to control surface resolution without introducing spatial digitization. The proposed fusion method successfully suppresses the map noise level by considering measurement noise caused by laser beam incident angle and depth distance in a Bayesian filtering framework. Experimental results with simulated and real data for the dense surfel mapping prove the ability of the proposed method to accurately find the canonical form of the environment without further post-processing.Comment: Accepted in Multiview Relationships in 3D Data 2017 (IEEE International Conference on Computer Vision Workshops

Three-Dimensional Subdivision Parameterisation for Aerodynamic Shape Optimisation

A novel hierarchical wing parameterisation method based on subdivision surfaces is presented and its performance tested on a range of geometric and aerodynamic optimisation test cases. Subdivision surfaces form a limit surface based on the recursive refinement of an initial network of points. This intrinsically creates a hierarchy of control points that can be used to deform the surface at varying degrees of fidelity. This principle is used to create a multi-resolutional surface parameterisation that can make fine and gross surface changes without losing underlying surface detail. This is then extended to allow multi-resolutional control of arbitrary meshes such as computational surface grids. This parameterisation method is then applied to a range of optimisation problems in a ‘multi-level’ procedure that starts with a low fidelity parametrisation and which is then increased sequentially. These cases are compared against a range of ‘single-level’ schemes that use each level in isolation. It was found that by using the multi-level method significant improvements to both convergence rates and robustness were achieved. In some cases this increased robustness lead to improved final results by successfully exploiting high dimensional design spaces that could not be explored using a fixed number of design variables

Paradigm Shift in Materials Processing - The Intelligent Processing Revolution

During the last several decades, the importance of materials processing in the control of microstructure and materials properties has been recognized and, accordingly, the materials engineering community has dedicated much effort to studying the physics of the process. These endeavors have provided an understanding of the phenomena which are relevant. However, a paradigm shift is taking place in that the physics oriented approach to materials processing is being replaced by a control oriented approach. What is needed today is the ability to control the process and, thus, the trajectory of the controllable variables in a temporal space. Such a knowledge based approach to materials processing which requires understanding, sensors, and controls is the revolution taking place in the materials engineering field. The essence is a process which can learn and develop \u27\u27intelligence\u27\u27 as it progresses. This address will present and discuss the basis and the need for a knowledge based approach to materials processing. Furthermore, specific industrial examples will be given to illustrate implementation of intelligent processing. Finally, the challenges ahead and the impediments we face as a community will also be addressed

Discrete Symmetries in Heterotic/F-theory Duality and Mirror Symmetry

We study aspects of Heterotic/F-theory duality for compactifications with Abelian discrete gauge symmetries. We consider F-theory compactifications on genus-one fibered Calabi-Yau manifolds with n-sections, associated with the Tate-Shafarevich group Z_n. Such models are obtained by studying first a specific toric set-up whose associated Heterotic vector bundle has structure group Z_n. By employing a conjectured Heterotic/F-theory mirror symmetry we construct dual geometries of these original toric models, where in the stable degeneration limit we obtain a discrete gauge symmetry of order two and three, for compactifications to six dimensions. We provide explicit constructions of mirror-pairs for symmetric examples with Z_2 and Z_3, in six dimensions. The Heterotic models with symmetric discrete symmetries are related in field theory to a Higgsing of Heterotic models with two symmetric abelian U(1) gauge factors, where due to the Stuckelberg mechanism only a diagonal U(1) factor remains massless, and thus after Higgsing only a diagonal discrete symmetry of order n is present in the Heterotic models and detected via Heterotic/F-theory duality. These constructions also provide further evidence for the conjectured mirror symmetry in Heterotic/F-theory at the level of fibrations with torsional sections and those with multi-sections.Comment: 25 pages, 4 figure

Corners-based composite descriptor for shapes

In this paper, a composite descriptor for shape retrieval is proposed. The composite descriptor is obtained based upon corner-points and shape region. In an earlier paper, we proposed a composite descriptor based on shape region and shape contour, however, the descriptor was not effective for all perspective and geometric transformations. Hence, we modify the composite descriptor by replacing contour features with corner-points features. The proposed descriptor is obtained from Generic FourierDescriptors (GFD) of the shape region and the GFD ofthe corner-points. We study the performance of the proposed composite descriptor. The proposed method is evaluated using Item S8 within the MPEG-7 Still Images Content Set. Experimental results show that the proposed descriptor is effective.<br /

Coordination in a hierarchical multi-actuator controller

A hierarchical multi-actuator controller is represented as a multi-resolutional information (knowledge) system utilizing a number of intelligent modules with decision making capabilities. The laws of multi-resolutional information (knowledge) organization and processing are presumed to be satisfied including the rules of dealing with redundant knowledge. A general case is considered in which a process to be controlled by a multiplicity of actuators is a distributed one and the condition of distribution can be formulated analytically. Operation of a lumped multi-actuator process is a particular case which has a broad practical application

Robust Photogeometric Localization over Time for Map-Centric Loop Closure

Map-centric SLAM is emerging as an alternative of conventional graph-based SLAM for its accuracy and efficiency in long-term mapping problems. However, in map-centric SLAM, the process of loop closure differs from that of conventional SLAM and the result of incorrect loop closure is more destructive and is not reversible. In this paper, we present a tightly coupled photogeometric metric localization for the loop closure problem in map-centric SLAM. In particular, our method combines complementary constraints from LiDAR and camera sensors, and validates loop closure candidates with sequential observations. The proposed method provides a visual evidence-based outlier rejection where failures caused by either place recognition or localization outliers can be effectively removed. We demonstrate the proposed method is not only more accurate than the conventional global ICP methods but is also robust to incorrect initial pose guesses.Comment: To Appear in IEEE ROBOTICS AND AUTOMATION LETTERS, ACCEPTED JANUARY 201

Model reduction for analysis of cascading failures in power systems

In this paper, we apply a principal-orthogonal decomposition based method to the model reduction of a hybrid, nonlinear model of a power network. The results demonstrate that the sequence of fault events can be evaluated and predicted without necessarily simulating the whole system