A Low-Cost Inertial Sensor Based on Shaped Magnetic Fluids

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

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Visual Measurement System for Wheel–Rail Lateral Position Evaluation

Sensors ◽

10.3390/s21041297 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1297

Author(s):

Viktor Skrickij ◽

Eldar Šabanovič ◽

Dachuan Shi ◽

Stefano Ricci ◽

Luca Rizzetto ◽

...

Keyword(s):

Measurement System ◽

Inertial Sensor ◽

Low Cost ◽

Image Point ◽

Low Velocity ◽

Point Selection ◽

Lateral Direction ◽

Initial Field ◽

Visual Measurement ◽

Track Geometry

Railway infrastructure must meet safety requirements concerning its construction and operation. Track geometry monitoring is one of the most important activities in maintaining the steady technical conditions of rail infrastructure. Commonly, it is performed using complex measurement equipment installed on track-recording coaches. Existing low-cost inertial sensor-based measurement systems provide reliable measurements of track geometry in vertical directions. However, solutions are needed for track geometry parameter measurement in the lateral direction. In this research, the authors developed a visual measurement system for track gauge evaluation. It involves the detection of measurement points and the visual measurement of the distance between them. The accuracy of the visual measurement system was evaluated in the laboratory and showed promising results. The initial field test was performed in the Vilnius railway station yard, driving at low velocity on the straight track section. The results show that the image point selection method developed for selecting the wheel and rail points to measure distance is stable enough for TG measurement. Recommendations for the further improvement of the developed system are presented.

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DYSKIMOT: An ultra-low-cost inertial sensor to assess head’s rotational kinematics in adults during the Didren-Laser Test

10.31224/osf.io/6n4ke ◽

2019 ◽

Author(s):

Renaud Hage ◽

Christine Detrembleur ◽

Frédéric Dierick ◽

Laurent Pitance ◽

Laurent Jojczyk ◽

...

Keyword(s):

Time Series ◽

Clinical Practice ◽

Gold Standard ◽

Inertial Sensor ◽

Low Cost ◽

Real Life ◽

Optoelectronic System ◽

Qualitative Level ◽

Cervical Motion ◽

Head Rotations

Various noninvasive measurement devices can be used to assess cervical motion. Size, complexity and cost of gold-standard systems make them not suited in clinical practice, and actually difficult to use outside dedicated laboratory. Nowadays, ultra-low-cost inertial measurement units are available but without any packaging nor user-friendly interface. DYSKIMOT is a home- designed, small-sized, motion sensor based on the latter technology, aiming at being used by clinicians in “real-life situations”. In the present study. DYSKIMOT was compared with a gold- standard optoelectronic system (Elite). Our goal was to evaluate the accuracy of DYSKIMOT in assessing the kinematics in fast head rotations. Kinematics was simultaneously recorded by the DYSKIMOT and Elite systems during the execution of the DidRen Laser test and performed by 15 participants and 9 patients. Kinematic variables were computed from the position, speed and acceleration time series. Two-way ANOVA, Passing-Bablok regressions and Dynamic Time Warping analysis showed good to excellent agreement between Elite and DYSKIMOT, both at the qualitative level of the time series shape and at the quantitative level of peculiar kinematical events’ measured values. In conclusion, DYSKIMOT sensor is as relevant as a gold-standard system to assess kinematical features during fast head rotations in participants and patients, demonstrating its usefulness in clinical practice or research in ecological environment.

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A Universal Approach for Processing any MEMS Inertial Sensor Configuration for Land-Vehicle Navigation

Journal of Navigation ◽

10.1017/s0373463307004213 ◽

2007 ◽

Vol 60 (2) ◽

pp. 233-245 ◽

Cited By ~ 24

Author(s):

Xiaoji Niu ◽

Sameh Nasser ◽

Chris Goodall ◽

Naser El-Sheimy

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

Navigation Systems ◽

Micro Electro Mechanical Systems ◽

Land Vehicle ◽

Mems Sensor ◽

Navigation Algorithm ◽

Main Challenge ◽

Universal Approach ◽

Sensor Configuration

Recent navigation systems integrating GPS with Micro-Electro-Mechanical Systems (MEMS) Inertial Measuring Units (IMUs) have shown promising results for several applications based on low-cost devices such as vehicular and personal navigation. However, as a trend in the navigation market, some applications require further reductions in size and cost. To meet such requirements, a MEMS full IMU configuration (three gyros and three accelerometers) may be simplified. In this context, different partial IMU configurations such as one gyro plus three accelerometers or one gyro plus two accelerometers could be investigated. The main challenge in this case is to develop a specific navigation algorithm for each configuration since this is a time-consuming and costly task. In this paper, a universal approach for processing any MEMS sensor configuration for land vehicular navigation is introduced. The proposed method is based on the assumption that the omitted sensors provide relatively less navigation information and hence, their output can be replaced by pseudo constant signals plus noise. Using standard IMU/GPS navigation algorithms, signals from existing sensors and pseudo signals for the omitted sensors are processed as a full IMU. The proposed approach is tested using land-vehicle MEMS/GPS data and implemented with different sensor configurations. Compared to the full IMU case, the results indicate the differences are within the expected levels and that the accuracy obtained meets the requirements of several land-vehicle applications.

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A Study on Multi-Copter Position Control Using Low- Cost MEMS Inertial Sensor

10.14257/astl.2017.149.03 ◽

2018 ◽

Author(s):

Min-Seok Jie ◽

Seung-Hun Kim ◽

Won-Hyuck Choi

Keyword(s):

Position Control ◽

Inertial Sensor ◽

Low Cost

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A rapid seismic data calibration technique using integrated micro-electro-mechanical system inertial sensor groups for a 3C vertical seismic profile

Geophysics ◽

10.1190/geo2016-0218.1 ◽

2017 ◽

Vol 82 (6) ◽

pp. P109-P118

Author(s):

Huailiang Li ◽

Xianguo Tuo ◽

Tong Shen ◽

Mark Julian Henderson ◽

Jérémie Courtois

Keyword(s):

Mechanical System ◽

Seismic Data ◽

Inertial Sensors ◽

Inertial Sensor ◽

Low Cost ◽

Measuring Method ◽

Seismic Profile ◽

Micro Electro Mechanical System ◽

Vertical Seismic Profile ◽

Sensor Package

Calibration of 3C vertical seismic profile (VSP) data is an exciting challenge because the orientation of the tool is random when only seismic data are considered. We have augmented the sensor package on the VSP tool with micro-electro-mechanical system (MEMS) inertial sensors and applied a gesture measuring method to determine the tool orientation and calibration. This technique can quickly produce high precision, orientation, and angle information when integrated with the seismometer. The augmented sensor package consists of a low-cost triaxial MEMS gyroscope, an electronic compass, and an accelerometer. The technique to process the gesture information is based on the OpenGL software for 3D modeling. We have tested this approach on a large number of field data sets and it appeared to be faster and more reliable than other approaches.

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Kalman filter-based yaw angle estimation by fusing inertial and magnetic sensing: a case study using low cost sensors

Sensor Review ◽

10.1108/sr-10-2014-0723 ◽

2015 ◽

Vol 35 (3) ◽

pp. 244-250 ◽

Cited By ~ 8

Author(s):

Pedro Neto ◽

Nuno Mendes ◽

A. Paulo Moreira

Keyword(s):

Kalman Filter ◽

Inertial Sensor ◽

Low Cost ◽

Human Robot Interaction ◽

Magnetic Sensor ◽

Robot Interaction ◽

Magnetic Sensing ◽

Content Type ◽

Reliable Estimation ◽

Yaw Angle

Purpose – The purpose of this paper is to achieve reliable estimation of yaw angles by fusing data from low-cost inertial and magnetic sensing. Design/methodology/approach – In this paper, yaw angle is estimated by fusing inertial and magnetic sensing from a digital compass and a gyroscope, respectively. A Kalman filter estimates the error produced by the gyroscope. Findings – Drift effect produced by the gyroscope is significantly reduced and, at the same time, the system has the ability to react quickly to orientation changes. The system combines the best of each sensor, the stability of the magnetic sensor and the fast response of the inertial sensor. Research limitations/implications – The system does not present a stable behavior in the presence of large vibrations. Considerable calibration efforts are needed. Practical implications – Today, most of human–robot interaction technologies need to have the ability to estimate orientation, especially yaw angle, from small-sized and low-cost sensors. Originality/value – Existing methods for inertial and magnetic sensor fusion are combined to achieve reliable estimation of yaw angle. Experimental tests in a human–robot interaction scenario show the performance of the system.

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A Tightly Coupled Positioning Solution for Land Vehicles in Urban Canyons

Journal of Sensors ◽

10.1155/2017/5965716 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 5

Author(s):

Xu Li ◽

Rong Jiang ◽

Xianghui Song ◽

Bin Li

Keyword(s):

Urban Areas ◽

Unscented Kalman Filter ◽

Inertial Sensor ◽

Low Cost ◽

Information Source ◽

Satellite Measurement ◽

3D Navigation ◽

Filter Model ◽

Land Vehicles ◽

Tightly Coupled

The integration between Global Navigation Satellite System (GNSS) and on-board sensors is widely used for vehicle positioning. However, as the main information source in the integration, the positioning performance of single- or multiconstellation GNSSs is severely degraded in urban canyons due to the effects of Non-Line-Of-Sight (NLOS) and multipath propagations. How to mitigate such effects is vital to achieve accurate positioning performance in urban canyons. This paper proposes a tightly coupled positioning solution for land vehicles, fusing dual-constellation GNSSs with other low-cost complementary sensors. First, the nonlinear filter model is established based on a cost-effective reduced inertial sensor system with 3D navigation solution. Then, an adaptive fuzzy unscented Kalman filter (AF-UKF) algorithm is developed to achieve the global fusion. In the implementation of AF-UKF, the fuzzy calibration logic (FCL) is designed and introduced to adaptively adjust the dependence on each received satellite measurement to effectively mitigate the NLOS and multipath interferences in urban areas. Finally, the proposed solution is evaluated through experiments. The results validate the feasibility and effectiveness of the proposed solution.

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M&NEMS: A new approach for ultra-low cost 3D inertial sensor

2009 IEEE Sensors ◽

10.1109/icsens.2009.5398195 ◽

2009 ◽

Cited By ~ 52

Author(s):

Ph. Robert ◽

V. Nguyen ◽

S. Hentz ◽

L. Duraffourg ◽

G. Jourdan ◽

...

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

New Approach

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High-Efficiency Wavelet Compressive Fusion for Improving MEMS Array Performance

Sensors ◽

10.3390/s20061662 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1662 ◽

Cited By ~ 2

Author(s):

Siyuan Liang ◽

Weilong Zhu ◽

Feng Zhao ◽

Congyi Wang

Keyword(s):

Real Time ◽

High Efficiency ◽

Microelectromechanical Systems ◽

Inertial Sensor ◽

Low Cost ◽

Rapid Development ◽

Experimental Results ◽

Zero Bias ◽

Real Time Processing ◽

Application Range

With the rapid development of microelectromechanical systems (MEMS) technology, low-cost MEMS inertial devices have been widely used for inertial navigation. However, their application range is greatly limited in some fields with high precision requirements because of their low precision and high noise. In this paper, to improve the performance of MEMS inertial devices, we propose a highly efficient optimal estimation algorithm for MEMS arrays based on wavelet compressive fusion (WCF). First, the algorithm uses the compression property of the multiscale wavelet transform to compress the original signal, fusing the compressive data based on the support. Second, threshold processing is performed on the fused wavelet coefficients. The simulation result demonstrates that the proposed algorithm performs well on the output of the inertial sensor array. Then, a ten-gyro array system is designed for collecting practical data, and the frequency of the embedded processor in our verification environment is 800 MHz. The experimental results show that, under the normal working conditions of the MEMS array system, the 100 ms input array data require an approximately 75 ms processing delay when employing the WCF algorithm to support real-time processing. Additionally, the zero-bias instability, angle random walk, and rate slope of the gyroscope are improved by 8.0, 8.0, and 9.5 dB, respectively, as compared with the original device. The experimental results demonstrate that the WCF algorithm has outstanding real-time performance and can effectively improve the accuracy of low-cost MEMS inertial devices.

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