The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform

G Chapuis - One of the best experts on this subject based on the ideXlab platform.

  • nada a computer program for the simultaneous refinement of Orientation Matrix and modulation vector s
    Journal of Applied Crystallography, 2001
    Co-Authors: Andreas Schonleber, M Meyer, G Chapuis
    Abstract:

    NADA is a computer program for the simultaneous refinement of the components of the Orientation Matrix and the components of up to three modulation vectors by the method of least squares. Using the spatial peak positions and the Orientation Matrix of the main reflections from a single-crystal diffraction experiment and rough estimates of the modulation vector(s) components, NADA re-indexes the peaks (main and satellite reflections) with integers in higher dimensions (hklm1, hklm1m2 or hklm1m2m3, respectively) and refines the Orientation Matrix and modulation vector(s) components from the observed peak positions. Standard uncertainties on all refined parameters are calculated analytically.

  • NADA – a computer program for the simultaneous refinement of Orientation Matrix and modulation vector(s)
    Journal of Applied Crystallography, 2001
    Co-Authors: Andreas Schonleber, M Meyer, G Chapuis
    Abstract:

    NADA is a computer program for the simultaneous refinement of the components of the Orientation Matrix and the components of up to three modulation vectors by the method of least squares. Using the spatial peak positions and the Orientation Matrix of the main reflections from a single-crystal diffraction experiment and rough estimates of the modulation vector(s) components, NADA re-indexes the peaks (main and satellite reflections) with integers in higher dimensions (hklm1, hklm1m2 or hklm1m2m3, respectively) and refines the Orientation Matrix and modulation vector(s) components from the observed peak positions. Standard uncertainties on all refined parameters are calculated analytically.

Andreas Schonleber - One of the best experts on this subject based on the ideXlab platform.

  • nada a computer program for the simultaneous refinement of Orientation Matrix and modulation vector s
    Journal of Applied Crystallography, 2001
    Co-Authors: Andreas Schonleber, M Meyer, G Chapuis
    Abstract:

    NADA is a computer program for the simultaneous refinement of the components of the Orientation Matrix and the components of up to three modulation vectors by the method of least squares. Using the spatial peak positions and the Orientation Matrix of the main reflections from a single-crystal diffraction experiment and rough estimates of the modulation vector(s) components, NADA re-indexes the peaks (main and satellite reflections) with integers in higher dimensions (hklm1, hklm1m2 or hklm1m2m3, respectively) and refines the Orientation Matrix and modulation vector(s) components from the observed peak positions. Standard uncertainties on all refined parameters are calculated analytically.

  • NADA – a computer program for the simultaneous refinement of Orientation Matrix and modulation vector(s)
    Journal of Applied Crystallography, 2001
    Co-Authors: Andreas Schonleber, M Meyer, G Chapuis
    Abstract:

    NADA is a computer program for the simultaneous refinement of the components of the Orientation Matrix and the components of up to three modulation vectors by the method of least squares. Using the spatial peak positions and the Orientation Matrix of the main reflections from a single-crystal diffraction experiment and rough estimates of the modulation vector(s) components, NADA re-indexes the peaks (main and satellite reflections) with integers in higher dimensions (hklm1, hklm1m2 or hklm1m2m3, respectively) and refines the Orientation Matrix and modulation vector(s) components from the observed peak positions. Standard uncertainties on all refined parameters are calculated analytically.

Craig L Bull - One of the best experts on this subject based on the ideXlab platform.

  • an improved method for calibrating time of flight laue single crystal neutron diffractometers
    Journal of Applied Crystallography, 2014
    Co-Authors: Craig L Bull, Michael R W Johnson, Hayrullo Hamidov, Kazuki Komatsu, Malcolm Guthrie, M J Gutmann, J S Loveday, R J Nelmes
    Abstract:

    A robust and comprehensive method for determining the Orientation Matrix of a single-crystal sample using the neutron Laue time-of-flight (TOF) technique is described. The new method enables the measurement of the unit-cell parameters with an uncertainty in the range 0.015–0.06%, depending upon the crystal symmetry and the number of reflections measured. The improved technique also facilitates the location and integration of weak reflections, which are often more difficult to discern amongst the increased background at higher energies. The technique uses a mathematical model of the relative positions of all the detector pixels of the instrument, together with a methodology that establishes a reproducible reference frame and a method for determining the parameters of the instrument detector model. Since all neutron TOF instruments require precise detector calibration for their effective use, it is possible that the method described here may be of use on other instruments where the detector calibration cannot be determined by other means.

Najib Metni - One of the best experts on this subject based on the ideXlab platform.

  • NONLINEAR ATTITUDE AND GYROSCOPE'S BIAS ESTIMATION FOR A VTOL UAV
    IFAC Proceedings Volumes, 2016
    Co-Authors: Jean-michel Pflimlin, Philippe Souères, Tarek Hamel, Najib Metni
    Abstract:

    Abstract This paper addresses the problem of attitude and heading restitution for a VTOL UAV. We describe an observation strategy to restitute the complete attitude Matrix of the vehicle starting from Inertial Measurement Unit (IMU) and magnetometers. This study is a part of the development of the ducted fan UAV designed by Bertin Technologies. First, a measured Orientation Matrix is calculated from both inertial vectors which are the gravity and the earth magnetic field. Then, an estimated Orientation is built by integrating gyroscopic readings, and corrected by the measured one. Nonlinear observation techniques are used to design a nonlinear estimator of the Orientation Matrix and an adaptive filter of the gyroscope's bias which ensure the convergence of the observer. Such an observer is as efficient as classical Extended Kalman Filtering based observers, and easier to implement in real time. Simulations are proposed to illustrate the concept.

  • Sensor Fusion for Attitude and Bias Estimation for a VTOL UAV
    ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis Volume 5, 2010
    Co-Authors: Najib Metni
    Abstract:

    In this paper, a nonlinear complementary filter is presented to estimate the attitude of a Vertical Take Off and Landing Unmanned Aerial Vehicle (VTOL UAV). The measurements are taken from a low-cost IMU (Inertial Measurement Unit) which consists of 3-axis accelerometers, 3-axis gyroscopes and 3-axis magnetometers. From the proposed estimators, the full Orientation Matrix R will be retrieved. The proposed observers will estimate the instantaneous quaternions as well as the gyroscope bias. This representation of Orientation by the rotation Matrix and quaternions allows overcoming the problem of singularities that appear in local parametrization such as Euler angles. Therefore, both estimators may be used to describe any kind of 3-D motion. Convergence of the two observers is theoretically proved and simulations are conducted taking data from a real platform in hovering flight conditions.Copyright © 2010 by ASME

  • Attitude and gyro bias estimation for a VTOL UAV
    Control Engineering Practice, 2006
    Co-Authors: Najib Metni, Jean-michel Pflimlin, Tarek Hamel, Philippe Souères
    Abstract:

    In this paper, a nonlinear complementary filter (x-estimator) is presented to estimate the attitude of a vertical take off and landing unmanned aerial vehicle (VTOL UAV). The measurements are taken from a low-cost IMU (inertial measurement unit) which consists of 3-axis accelerometers and 3-axis gyroscopes. The gyro bias are estimated online. A second nonlinear complementary filter (z-estimator) which combines 3-axis gyroscope readings with 3-axis magnetometer measurements, is also designed. Based on the proposed estimators, the full Orientation Matrix R will be retrieved. Note that R evolves on the special orthogonal group SO (3), since it is a transformation Matrix between two orthogonal frames. This representation of Orientation by the rotation Matrix allows to overcome the problem of singularities that appear in local parametrization such as Euler angles. Therefore, both estimators may be used to describe any type of 3D motion. The convergence of the two observers is theoretically and experimentally proven; simulations and experiments are conducted on a real platform in hovering flight conditions. © 2006 Elsevier Ltd. All rights reserved.

  • IROS - Attitude and gyro bias estimation for a flying UAV
    2005 IEEE RSJ International Conference on Intelligent Robots and Systems, 2005
    Co-Authors: Najib Metni, Jean-michel Pflimlin, Tarek Hamel, Philippe Souères
    Abstract:

    In this paper, a nonlinear complimentary filter (x-estimator) is presented to estimate the attitude of a UAV (unmanned aerial vehicle). The measurements are taken from a low-cost SMU (inertial measurement unit) which consists of 3-axis accelerometers and 3-axis gyroscopes. The gyro bias are estimated online. A second nonlinear complimentary filter (z-estimator) is also designed, it combines 3-axis gyroscope readings with 3-axis magnetometer measurements. From the proposed estimators, the full rotation Matrix R will be retrieved. Both estimators use the fact that the Orientation Matrix, evolving on SO(3), is not locally parameterized and thus could be used to describe any kind of 3D motion. Convergence of the two observers is theoretically proved and simulations as well as experiments are conducted on a real platform in hovering flight conditions.

  • Nonlinear attitude and gyroscope's bias estimation for a VTOL UAV
    IFAC Proceedings Volumes (IFAC-PapersOnline), 2005
    Co-Authors: Jean-michel Pflimlin, Philippe Souères, Tarek Hamel, Najib Metni
    Abstract:

    In this paper, a nonlinear complementary filter (x-estimator) is presented to estimate the attitude of a vertical take off and landing unmanned aerial vehicle (VTOL UAV). The measurements are taken from a low-cost IMU (inertial measurement unit) which consists of 3-axis accelerometers and 3-axis gyroscopes. The gyro bias are estimated online. A second nonlinear complementary filter (z-estimator) which combines 3-axis gyroscope readings with 3-axis magnetometer measurements, is also designed. Based on the proposed estimators, the full Orientation Matrix R will be retrieved. Note that R evolves on the special orthogonal group SO (3), since it is a transformation Matrix between two orthogonal frames. This representation of Orientation by the rotation Matrix allows to overcome the problem of singularities that appear in local parametrization such as Euler angles. Therefore, both estimators may be used to describe any type of 3D motion. The convergence of the two observers is theoretically and experimentally proven; simulations and experiments are conducted on a real platform in hovering flight conditions. © 2006 Elsevier Ltd. All rights reserved.

Sivaramakrishnan Sivasubramanian - One of the best experts on this subject based on the ideXlab platform.

  • Product distance Matrix of a graph and squared distance Matrix of a tree
    Applicable Analysis and Discrete Mathematics, 2020
    Co-Authors: Ravindra B. Bapat, Sivaramakrishnan Sivasubramanian
    Abstract:

    Let G be a strongly connected, weighted directed graph. We define a product distance η(i,j) for pairs i,j of vertices and form the corresponding product distance Matrix. We obtain a formula for the determinant and the inverse of the product distance Matrix. The edge Orientation Matrix of a directed tree is defined and a formula for its determinant and its inverse, when it exists, is obtained. A formula for the determinant of the (entry-wise) squared distance Matrix of a tree is proved.

  • squared distance Matrix of a tree inverse and inertia
    Linear Algebra and its Applications, 2016
    Co-Authors: Ravindra B. Bapat, Sivaramakrishnan Sivasubramanian
    Abstract:

    Abstract Let T be a tree with vertices V ( T ) = { 1 , … , n } . The distance between vertices i , j ∈ V ( T ) , denoted d i j , is defined to be the length (the number of edges) of the path from i to j. We set d i i = 0 , i = 1 , … , n . The squared distance Matrix Δ of T is the n × n Matrix with ( i , j ) -element equal to 0 if i = j , and d i j 2 if i ≠ j . It is known that Δ is nonsingular if and only if the tree has at most one vertex of degree 2. We obtain a formula for Δ − 1 , if it exists. When the tree has no vertex of degree 2, the formula is particularly simple and depends on a certain “two-step” Laplacian of the tree. We determine the inertia of Δ. The inverse and the inertia of the edge Orientation Matrix are also described.