Formulation of a new gradient descent MARG orientation algorithm: case study on robot teleoperation
File(s)
Published version
Author(s)
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.
Date Issued
2019-09-01
Date Acceptance
2019-04-30
Citation
Mechanical Systems and Signal Processing, 2019, 130 (1), pp.183-200
ISSN
0888-3270
Publisher
Elsevier
Start Page
183
End Page
200
Journal / Book Title
Mechanical Systems and Signal Processing
Volume
130
Issue
1
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
Office Of Naval Research Global
Engineering & Physical Science Research Council (E
Identifier
https://www.sciencedirect.com/science/article/pii/S0888327019303012
Grant Number
N62909-14-1-N221
EP/R511547/1
Subjects
Science & Technology
Technology
Engineering, Mechanical
Engineering
Inertial sensor fusion
mechatronic sensing
Robot teleoperation
Human-machine interface (HMI)
inertial measurement unit (IMU)
Wearable sensors
COMPLEMENTARY FILTER DESIGN
KALMAN FILTER
ATTITUDE ESTIMATION
SENSOR FUSION
NAVIGATION
Acoustics
0905 Civil Engineering
0913 Mechanical Engineering
0915 Interdisciplinary Engineering
Publication Status
Published
Date Publish Online
2019-05-11