Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81197
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
Keywords: Human-machine interface (HMI)
inertial measurement unit (IMU)
Inertial sensor fusion
mechatronic sensing
Robot teleoperation
Wearable sensors
Issue Date: 2019
Publisher: Academic Press
Source: Mechanical systems and signal processing, 2019, v. 130, p. 183-200 How to cite?
Journal: Mechanical systems and signal processing 
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.
URI: http://hdl.handle.net/10397/81197
ISSN: 0888-3270
EISSN: 1096-1216
DOI: 10.1016/j.ymssp.2019.04.064
Rights: © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
The following publication Wilson, S., Eberle, H., Hayashi, Y., Madgwick, S. O., McGregor, A., Jing, X., & Vaidyanathan, R. (2019). Formulation of a new gradient descent MARG orientation algorithm: Case study on robot teleoperation. Mechanical Systems and Signal Processing, 130, 183-200 is available at https://doi.org/10.1016/j.ymssp.2019.04.064
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