scholarly journals Embedded inertial measurement unit reveals pole lean angle for cross-country skiing

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
John Bruzzo ◽  
Noel C. Perkins ◽  
Aki Mikkola
Keyword(s):  
Measurement System ◽  
Inertial Measurement Unit ◽  
Angular Rate ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Lean Angle ◽  
Cross Country Skiing ◽  
Cross Country ◽  
Mean Differences ◽  
Mean Square Errors

AbstractThis study introduces an inertial measurement unit-based measurement system for resolving the dynamic lean angle of a ski pole during double poling while cross-country skiing. The measurement system estimates both the pole lean angle and pole–terrain contact events. Reported are results from 20 trials providing validated estimates of ski pole lean angle and the timing of pole plant and pole lift events. The pole lean angle is estimated from a complementary filter that fuses estimates of orientation from the embedded accelerometer and angular rate gyro. Validation follows from comparison with video capture measurements. Bland–Altman analysis showed agreement between the two measurement modalities with less than 5% bias in the mean differences (relative to the lean angle range of motion). Companion correlation analysis confirms strong correlation ($$r = 0.99$$ r = 0.99 ) between the inertial measurement unit and video-estimated lean angles and with mean root-mean-square errors below 4.5$$^{\circ }$$ ∘ .

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.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

scholarly journals Angular velocity fusion of the microelectromechanical system inertial measurement unit array based on extended Kalman filter with correlated system noises

2020 ◽  
pp. 002029402091770
Author(s):  
Li Xing ◽  
Xiaowei Tu ◽  
Weixing Qian ◽  
Yang Jin ◽  
Pei Qi
Keyword(s):  
Kalman Filter ◽  
Angular Velocity ◽  
Extended Kalman Filter ◽  
Inertial Measurement Unit ◽  
Angular Rate ◽  
The State ◽  
Measurement Unit ◽  
Fusion Method ◽  
Microelectromechanical System ◽  
Inertial Measurement

The paper proposes an angular velocity fusion method of the microelectromechanical system inertial measurement unit array based on the extended Kalman filter with correlated system noises. In the proposed method, an adaptive model of the angular velocity is built according to the motion characteristics of the vehicles and it is regarded as the state equation to estimate the angular velocity. The signal model of gyroscopes and accelerometers in the microelectromechanical system inertial measurement unit array is used as the measurement equation to fuse and estimate the angular velocity. Due to the correlation of the state and measurement noises in the presented fusion model, the traditional extended Kalman filter equations are optimized, so as to accurately and reliably estimate the angular velocity. By simulating angular rates in different motion modes, such as constant and change-in-time angular rates, it is verified that the proposed method can reliably estimate angular rates, even when the angular rate has been out of the microelectromechanical system gyroscope measurement range. And results show that, compared with the traditional angular rate fusion method of microelectromechanical system inertial measurement unit array, it can estimate angular rates more accurately. Moreover, in the kinematic vehicle experiments, the performance advantage of the proposed method is also verified and the angular rate estimation accuracy can be increased by about 1.5 times compared to the traditional method.

scholarly journals An Implementation of Error Minimization Position Estimate in Wireless Inertial Measurement Unit using Modification ZUPT

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Adytia Darmawan ◽  
Sanggar Dewanto ◽  
Dadet Pramadihanto
Keyword(s):  
Inertial Measurement Unit ◽  
Robot Navigation ◽  
Angular Rate ◽  
Position Estimation ◽  
Experimental Result ◽  
Measurement Unit ◽  
Legged Robot ◽  
Positioning Systems ◽  
Inertial Measurement ◽  
Position Estimate

Position estimation using WIMU (Wireless Inertial Measurement Unit) is one of emerging technology in the field of indoor positioning systems. WIMU can detect movement and does not depend on GPS signals. The position is then estimated using a modified ZUPT (Zero Velocity Update) method that was using Filter Magnitude Acceleration (FMA), Variance Magnitude Acceleration (VMA) and Angular Rate (AR) estimation. Performance of this method was justified on a six-legged robot navigation system. Experimental result shows that the combination of VMA-AR gives the best position estimation.

scholarly journals A Sporting Chance

2011 ◽  
Vol 133 (07) ◽  
pp. 40-45
Author(s):  
Noel C. Perkins ◽  
Kevin King ◽  
Ryan McGinnis ◽  
Jessandra Hough
Keyword(s):  
Inertial Measurement Unit ◽  
Wireless Sensors ◽  
Microelectromechanical Systems ◽  
Angular Rate ◽  
Rigid Body Dynamics ◽  
The Body ◽  
Measurement Unit ◽  
Golf Club ◽  
Sports Training ◽  
Inertial Measurement

This article discusses using wireless sensors to improve sports training. One example of wireless sensors is inertial sensors that were first developed for automotive and military applications. They are tiny accelerometers and angular rate gyros that can be combined to form a complete inertial measurement unit. An inertial measurement unit (IMU) detects the three-dimensional motion of a body in space by sensing the acceleration of one point on the body as well as the angular velocity of the body. When this small, but rugged device is mounted on or embedded within sports gear, such as the shaft of a golf club, the IMU provides the essential data needed to resolve the motion of that equipment. This technology—and sound use of the theory of rigid body dynamics—is now being developed and commercialized as the ingredients in new sports training systems. It won’t be too long before microelectromechanical systems based hardware and sophisticated software combine to enable athletes at any level to get world-class training.

scholarly journals Physical Extraction and Feature Fusion for Multi-Mode Signals in a Measurement System for Patients in Rehabilitation Exoskeleton

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2588 ◽  
Author(s):  
Canjun Yang ◽  
Qianxiao Wei ◽  
Xin Wu ◽  
Zhangyi Ma ◽  
Qiaoling Chen ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Measurement System ◽  
Inertial Measurement Unit ◽  
Feature Fusion ◽  
Effective Control ◽  
Measurement Unit ◽  
Individual Measurement ◽  
Visual Measurement ◽  
Inertial Measurement

Measurement system of exoskeleton robots can reflect the state of the patient. In this study, we combined an inertial measurement unit and a visual measurement unit to obtain a repeatable fusion measurement system to compensate for the deficiencies of the single data acquisition mode used by exoskeletons. Inertial measurement unit is comprised four distributed angle sensors. Triaxial acceleration and angular velocity information were transmitted to an upper computer by Bluetooth. The data sent to the control center were processed by a Kalman filter to eliminate any noise. Visual measurement unit uses camera to acquire real time images and related data information. The two data acquisition methods were fused and have its weight. Comparisons of the fusion results with individual measurement results demonstrated that the data fusion method could effectively improve the accuracy of system. It provides a set of accurate real-time measurements for patients in rehabilitation exoskeleton and data support for effective control of exoskeleton robot.

Sign in / Sign up

Export Citation Format

Share Document