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Formulation of a new gradient descent MARG orientation algorithm: Case study on robot teleoperation

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Vaidyanathan Mech Sys Sig Proc 130 pp 183-200 2019.pdfPublished version3.05 MBAdobe PDFView/Open
Title: Formulation of a new gradient descent MARG orientation algorithm: Case study on robot teleoperation
Authors: Wilson, S
Eberle, H
Hayashi, Y
Madgwick, SOH
McGregor, A
Jing, X
Vaidyanathan, R
Item Type: Journal Article
Abstract: We introduce a novel magnetic angular rate gravity (MARG) sensor fusion algorithm for inertial measurement. The new algorithm improves the popular gradient descent (ʻMadgwick’) algorithm increasing accuracy and robustness while preserving computational efficiency. Analytic and experimental results demonstrate faster convergence for multiple variations of the algorithm through changing magnetic inclination. Furthermore, decoupling of magnetic field variance from roll and pitch estimation is proven for enhanced robustness. The algorithm is validated in a human-machine interface (HMI) case study. The case study involves hardware implementation for wearable robot teleoperation in both Virtual Reality (VR) and in real-time on a 14 degree-of-freedom (DoF) humanoid robot. The experiment fuses inertial (movement) and mechanomyography (MMG) muscle sensing to control robot arm movement and grasp simultaneously, demonstrating algorithm efficacy and capacity to interface with other physiological sensors. To our knowledge, this is the first such formulation and the first fusion of inertial measurement and MMG in HMI. We believe the new algorithm holds the potential to impact a very wide range of inertial measurement applications where full orientation necessary. Physiological sensor synthesis and hardware interface further provides a foundation for robotic teleoperation systems with necessary robustness for use in the field.
Issue Date: 1-Sep-2019
Date of Acceptance: 30-Apr-2019
URI: http://hdl.handle.net/10044/1/70358
DOI: https://dx.doi.org/10.1016/j.ymssp.2019.04.064
ISSN: 0888-3270
Publisher: Elsevier
Start Page: 183
End Page: 200
Journal / Book Title: Mechanical Systems and Signal Processing
Volume: 130
Copyright Statement: © 2019 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Sponsor/Funder: Office Of Naval Research Global
Engineering & Physical Science Research Council (E
Funder's Grant Number: N62909-14-1-N221
EP/R511547/1
Keywords: Acoustics
0905 Civil Engineering
0913 Mechanical Engineering
0915 Interdisciplinary Engineering
Publication Status: Published
Open Access location: https://www.sciencedirect.com/science/article/pii/S0888327019303012?via%3Dihub
Online Publication Date: 2019-05-11
Appears in Collections:Mechanical Engineering
Division of Surgery
Faculty of Medicine



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