Imperial College London


Faculty of EngineeringDepartment of Mechanical Engineering

Reader in Biomechatronics



+44 (0)20 7594 7020r.vaidyanathan CV




717City and Guilds BuildingSouth Kensington Campus






BibTex format

author = {Wilson, S and Eberle, H and Hayashi, Y and Madgwick, SOH and McGregor, A and Jing, X and Vaidyanathan, R},
doi = {10.1016/j.ymssp.2019.04.064},
journal = {Mechanical Systems and Signal Processing},
pages = {183--200},
title = {Formulation of a new gradient descent MARG orientation algorithm: Case study on robot teleoperation},
url = {},
volume = {130},
year = {2019}

RIS format (EndNote, RefMan)

AB - We introduce a novel magnetic angular rate gravity (MARG) sensor fusion algorithm for inertial measurement. The new algorithm improves the popular gradient descent (Madgwick’) 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.
AU - Wilson,S
AU - Eberle,H
AU - Hayashi,Y
AU - Madgwick,SOH
AU - McGregor,A
AU - Jing,X
AU - Vaidyanathan,R
DO - 10.1016/j.ymssp.2019.04.064
EP - 200
PY - 2019///
SN - 0888-3270
SP - 183
TI - Formulation of a new gradient descent MARG orientation algorithm: Case study on robot teleoperation
T2 - Mechanical Systems and Signal Processing
UR -
UR -
VL - 130
ER -