Comparison of attitude determination methodologies with low cost inertial measurement unit for autonomous aerial vehicle

2013 ◽  
Author(s):  
M. H. Choi ◽  
R. Porter ◽  
B. Shirinzadeh
Keyword(s):  
Inertial Measurement Unit ◽  
Attitude Determination ◽  
Low Cost ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Aerial Vehicle

Sensor Fusion for Attitude and Bias Estimation for a VTOL UAV

2010 ◽  
Author(s):  
Najib A. Metni
Keyword(s):  
Inertial Measurement Unit ◽  
Low Cost ◽  
Measurement Unit ◽  
Bias Estimation ◽  
Inertial Measurement ◽  
Complementary Filter ◽  
Vtol Uav ◽  
Orientation Matrix ◽  
Local Parametrization ◽  
Aerial Vehicle

In this paper, a nonlinear complementary filter is presented to estimate the attitude of a Vertical Take Off and Landing Unmanned Aerial Vehicle (VTOL UAV). The measurements are taken from a low-cost IMU (Inertial Measurement Unit) which consists of 3-axis accelerometers, 3-axis gyroscopes and 3-axis magnetometers. From the proposed estimators, the full orientation matrix R will be retrieved. The proposed observers will estimate the instantaneous quaternions as well as the gyroscope bias. This representation of orientation by the rotation matrix and quaternions allows overcoming the problem of singularities that appear in local parametrization such as Euler angles. Therefore, both estimators may be used to describe any kind of 3-D motion. Convergence of the two observers is theoretically proved and simulations are conducted taking data from a real platform in hovering flight conditions.

Attitude Determination by Integration of Multi-Sensors Based on Federated Kalman Filter

2014 ◽  
Vol 602-605 ◽  
pp. 2958-2961
Author(s):  
Tao Lai ◽  
Guang Long Wang ◽  
Wen Jie Zhu ◽  
Feng Qi Gao
Keyword(s):  
Kalman Filter ◽  
Inertial Measurement Unit ◽  
Attitude Determination ◽  
Angular Rate ◽  
General Structure ◽  
Test System ◽  
Measurement Unit ◽  
Storage Test ◽  
Inertial Measurement ◽  
Federated Kalman Filter

Micro inertial measurement unit integration storage test system is a typical multi-sensor information fusion system consists of microsensors. The Federated Kalman filter is applied to micro inertial measurement unit integration storage test system. The general structure and characteristics of Federated Kalman filter is expounded. The four-order Runge-Kutta method based on quaternion differential equation was used to dispose the output angular rate data from gyroscope, and the recurrence expressions was established too. The control system based ARM Cortex-M4 master-slave structure is adopted in this paper. The result shown that the dimensionality reduced algorithm significantly reduces implementation complexity of the method and the amount computation. The filtering effect and real-time performance have much increased than traditionally method.

Maximum Correntropy Kalman Filter for Orientation Estimation With Application to LiDAR Inertial Odometry

2020 ◽  
Author(s):  
Seyed Fakoorian ◽  
Matteo Palieri ◽  
Angel Santamaria-Navarro ◽  
Cataldo Guaragnella ◽  
Dan Simon ◽  
...  
Keyword(s):  
Kalman Filtering ◽  
Inertial Measurement Unit ◽  
Low Cost ◽  
Attitude Estimation ◽  
High Rate ◽  
Measurement Unit ◽  
Orientation Estimation ◽  
Localization Accuracy ◽  
Inertial Measurement ◽  
Robotic Applications

Abstract Accurate attitude estimation using low-cost sensors is an important capability to enable many robotic applications. In this paper, we present a method based on the concept of correntropy in Kalman filtering to estimate the 3D orientation of a rigid body using a low-cost inertial measurement unit (IMU). We then leverage the proposed attitude estimation framework to develop a LiDAR-Intertial Odometry (LIO) demonstrating improved localization accuracy with respect to traditional methods. This is of particular importance when the robot undergoes high-rate motions that typically exacerbate the issues associated with low-cost sensors. The proposed orientation estimation approach is first validated using the data coming from a low-cost IMU sensor. We further demonstrate the performance of the proposed LIO solution in a simulated robotic cave exploration scenario.

An inertial measurement unit tracking system for body movement in comparison with optical tracking

2020 ◽  
Vol 234 (7) ◽  
pp. 728-737
Author(s):  
Rui Li ◽  
Barclay Jumet ◽  
Hongliang Ren ◽  
WenZhan Song ◽  
Zion Tsz Ho Tse
Keyword(s):  
Inertial Measurement Unit ◽  
Tracking System ◽  
Low Cost ◽  
Optical Tracking ◽  
Measurement Unit ◽  
Joint Movement ◽  
Joint Angles ◽  
Optical Tracking System ◽  
Microelectromechanical System ◽  
Inertial Measurement

The recent advancement of motion tracking technology offers better treatment tools for conditions, such as movement disorders, as the outcome of the rehabilitation could be quantitatively defined. The accurate and fast angular information output of the inertial measurement unit tracking systems enables the collection of accurate kinematic data for clinical assessment. This article presents a study of a low-cost microelectromechanical system inertial measurement unit-based tracking system in comparison with the conventional optical tracking system. The system consists of seven microelectromechanical system inertial measurement units, which could be mounted on the lower limbs of the subjects. For the feasibility test, 10 human participants were instructed to perform three different motions: walking, running, and fencing lunges when wearing specially designed sleeves. The subjects’ lower body movements were tracked using our inertial measurement unit-based system and compared with the gold standard—the NDI Polaris Vega optical tracking system. The results of the angular comparison between the inertial measurement unit and the NDI Polaris Vega optical tracking system were as follows: the average cross-correlation value was 0.85, the mean difference of joint angles was 2.00°, and the standard deviation of joint angles was ± 2.65°. The developed microelectromechanical system–based tracking system provides an alternative low-cost solution to track joint movement. Moreover, it is able to operate on an Android platform and could potentially be used to assist outdoor or home-based rehabilitation.

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