DeepAI AI Chat
Log In Sign Up

Multi-kernel Correntropy-based Orientation Estimation of IMUs: Gradient Descent Methods

by   Shilei Li, et al.
Harbin Institute of Technology
Beijing Institute of Technology
NetEase, Inc
The Hong Kong University of Science and Technology

This paper presents two computationally efficient algorithms for the orientation estimation of inertial measurement units (IMUs): the correntropy-based gradient descent (CGD) and the correntropy-based decoupled orientation estimation (CDOE). Traditional methods, such as gradient descent (GD) and decoupled orientation estimation (DOE), rely on the mean squared error (MSE) criterion, making them vulnerable to external acceleration and magnetic interference. To address this issue, we demonstrate that the multi-kernel correntropy loss (MKCL) is an optimal objective function for maximum likelihood estimation (MLE) when the noise follows a type of heavy-tailed distribution. In certain situations, the estimation error of the MKCL is bounded even in the presence of arbitrarily large outliers. By replacing the standard MSE cost function with MKCL, we develop the CGD and CDOE algorithms. We evaluate the effectiveness of our proposed methods by comparing them with existing algorithms in various situations. Experimental results indicate that our proposed methods (CGD and CDOE) outperform their conventional counterparts (GD and DOE), especially when faced with external acceleration and magnetic disturbances. Furthermore, the new algorithms demonstrate significantly lower computational complexity than Kalman filter-based approaches, making them suitable for applications with low-cost microprocessors.


page 1

page 8


Diffusion Maximum Correntropy Criterion Algorithms for Robust Distributed Estimation

Robust diffusion adaptive estimation algorithms based on the maximum cor...

The E-Bayesian Estimation and its E-MSE of Lomax distribution under different loss functions

This paper studies the E-Bayesian (expectation of the Bayesian estimatio...

Magnetometer-free inertial motion tracking of arbitrary joints with range of motion constraints

In motion tracking of connected multi-body systems Inertial Measurement ...

A Fast and Robust Algorithm for Orientation Estimation using Inertial Sensors

We present a novel algorithm for online, real-time orientation estimatio...

A Unified Approach to Robust Mean Estimation

In this paper, we develop connections between two seemingly disparate, b...