Automated Calibration System for IMU Based on Database and LabVIEW

2013 ◽  
Vol 333-335 ◽  
pp. 2396-2400 ◽  
Author(s):  
Yan Deng ◽  
Chao Xing ◽  
Bin Zhou
Keyword(s):  
Inertial Measurement Unit ◽  
Calibration Procedure ◽  
Measurement Unit ◽  
Test Results ◽  
Calibration System ◽  
Inertial Measurement ◽  
Test Items ◽  
Long Time ◽  
Verification Test ◽  
Data Transferring

The calibration of Inertial Measurement Unit (IMU) is the premise of inertial navigation. It includes series of test items, takes a long time, and requires lots of data transferring and calculating operations. Traditional manual method is difficult to ensure its reliability and efficiency. This paper presented an automated IMU calibration system with three layers: the test hardware devices, the calibration software and the calibration database. Calibration software controlled the tests running in the temperature box, on the turntable, vibration table and marble horizontal table. Calibration database stored the test data and calibration parameters. Through the LabVIEW aided database technique, the system not only completed all the test items but also integrated and simplified the calibration procedure. The verification test results showed that the system improved the calibration efficiency and enhanced the calibration reliability greatly.

scholarly journals Integrated GNSS/IMU-Gyrocompass with Rotating IMU. Development and Test Results

2020 ◽  
Vol 12 (22) ◽  
pp. 3736
Author(s):  
Gennadiy Emel’yantsev ◽  
Oleg Stepanov ◽  
Aleksey Stepanov ◽  
Boris Blazhnov ◽  
Elena Dranitsyna ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Fiber Optic ◽  
Measurement Unit ◽  
Prototype Model ◽  
Navigation Satellite ◽  
Test Results ◽  
Rotating Platform ◽  
Inertial Measurement ◽  
Urban Conditions ◽  
The Given

The paper presents the developed integrated GNSS/IMU gyrocompass which, unlike the existing systems, contains a single-axis rotating platform with two antennas installed on it and an inertial measurement unit with tactical grade fiber-optic gyros. It is shown that the proposed design provides attitude solution by observing the signals of only one navigation satellite. The structure of the integrated GNSS/IMU gyrocompass, its specific features and prototype model used in the tests are described. The given test results in urban conditions confirmed heading determination accurate to ±1.5° (3σ).

Agricultural Machinery Operation Posture Rapid Detection Method Based on Intelligent Sensor

2013 ◽  
Vol 373-375 ◽  
pp. 936-939
Author(s):  
Nan Feng Zhang ◽  
Jing Feng Yang ◽  
Yue Ju Xue ◽  
Zhong Li ◽  
Xiao Lin Huang
Keyword(s):  
Real Time ◽  
Rapid Detection ◽  
Inertial Measurement Unit ◽  
Detection Method ◽  
Measurement Unit ◽  
Test Results ◽  
Agricultural Machinery ◽  
Intelligent Sensor ◽  
Inertial Measurement ◽  
Status Data

Based on agricultural machinery body posture detection parameters and wheels gesture detection parameters collected by gyro inertial measurement unit, an agricultural machinery operation posture rapid detection method is proposed in this paper. The test results show that, the test results of the method are accurate and available, and the method is effective and available for real-time body and wheel status data to further understand the agricultural machinery.

Inertial measurement unit of waverider buoy. Development and test results

2016 ◽  
Vol 7 (3) ◽  
pp. 239-246 ◽  
Author(s):  
D. G. Gryazin ◽  
L. P. Starosel’tsev ◽  
O. O. Belova ◽  
A. N. Dzyuba
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Test Results ◽  
Inertial Measurement

scholarly journals GPS/Reduced IMU with a Local Terrain Predictor in Land Vehicle Navigation

2008 ◽  
Vol 2008 ◽  
pp. 1-15 ◽  
Author(s):  
Debo Sun ◽  
Mark G. Petovello ◽  
M. Elizabeth Cannon
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Vehicle Navigation ◽  
Test Results ◽  
Inertial Measurement ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Global Positioning ◽  
The Cost

In order to reduce the cost and volume of land vehicle navigation (LVN) systems, a “reduced” inertial measurement unit (IMU) consisting of only one vertical gyro and two or three accelerometers is generally used and is often integrated with other sensors. Since there are no horizontal gyros in a reduced IMU, the pitch and roll cannot be calculated or observed directly from the inertial data, and the navigation performance is thus affected by local terrain variations. In this work, a reduced IMU is integrated with global positioning system (GPS) data and a novel local terrain predictor (LTP) algorithm. The latter is used primarily to help estimate the pitch and roll of the reduced IMU system and thus to improve the navigation performance. In this paper, two reduced IMU configurations and two grades of IMUs are investigated using field data. Test results show that the LTP is valid. Specifically, inclusion of the LTP provides more than an 80% horizontal velocity improvement relative to the case when the LTP is not used in a GPS/reduced IMU configuration.

Inertial measurement unit for waverider buoy. Development and test results

2015 ◽  
Vol 24 (1) ◽  
pp. 88-99 ◽  
Author(s):  
D. G. Gryazin ◽  
◽  
L. P. Staroseltsev ◽  
O. O. Belova ◽  
A. N. Dzyuba ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Test Results ◽  
Inertial Measurement

scholarly journals Inertial measurement unit-based pose estimation: Analyzing and reducing sensitivity to sensor placement and body measures

2019 ◽  
Vol 6 ◽  
pp. 205566831881345 ◽  
Author(s):  
Rezvan Kianifar ◽  
Vladimir Joukov ◽  
Alexander Lee ◽  
Sachin Raina ◽  
Dana Kulić
Keyword(s):  
Pose Estimation ◽  
Inertial Measurement Unit ◽  
Kinematic Model ◽  
Sensor Placement ◽  
Estimation Method ◽  
Calibration Procedure ◽  
The Body ◽  
Estimation Accuracy ◽  
Measurement Unit ◽  
Inertial Measurement

Introduction Inertial measurement units have been proposed for automated pose estimation and exercise monitoring in clinical settings. However, many existing methods assume an extensive calibration procedure, which may not be realizable in clinical practice. In this study, an inertial measurement unit-based pose estimation method using extended Kalman filter and kinematic chain modeling is adapted for lower body pose estimation during clinical mobility tests such as the single leg squat, and the sensitivity to parameter calibration is investigated. Methods The sensitivity of pose estimation accuracy to each of the kinematic model and sensor placement parameters was analyzed. Sensitivity analysis results suggested that accurate extraction of inertial measurement unit orientation on the body is a key factor in improving the accuracy. Hence, a simple calibration protocol was proposed to reach a better approximation for inertial measurement unit orientation. Results After applying the protocol, the ankle, knee, and hip joint angle errors improved to [Formula: see text], and [Formula: see text], without the need for any other calibration. Conclusions Only a small subset of kinematic and sensor parameters contribute significantly to pose estimation accuracy when using body worn inertial sensors. A simple calibration procedure identifying the inertial measurement unit orientation on the body can provide good pose estimation performance.

scholarly journals Portable Gait Lab: Estimating Over-Ground 3D Ground Reaction Forces Using Only a Pelvis IMU

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6363
Author(s):  
Mohamed Irfan Mohamed Refai ◽  
Bert-Jan F. van Beijnum ◽  
Jaap H. Buurke ◽  
Peter H. Veltink
Keyword(s):  
Inertial Measurement Unit ◽  
Center Of Mass ◽  
Calibration Procedure ◽  
Measurement Unit ◽  
Average Error ◽  
Ground Reaction Forces ◽  
Inertial Measurement ◽  
Reaction Forces ◽  
Error State ◽  
Over Ground Walking

As an alternative to force plates, an inertial measurement unit (IMU) at the pelvis can offer an ambulatory method for measuring total center of mass (CoM) accelerations and, thereby, the ground reaction forces (GRF) during gait. The challenge here is to estimate the 3D components of the GRF. We employ a calibration procedure and an error state extended Kalman filter based on an earlier work to estimate the instantaneous 3D GRF for different over-ground walking patterns. The GRF were then expressed in a body-centric reference frame, to enable an ambulatory setup not related to a fixed global frame. The results were validated with ForceShoesTM, and the average error in estimating instantaneous shear GRF was 5.2 ± 0.5% of body weight across different variable over-ground walking tasks. The study shows that a single pelvis IMU can measure 3D GRF in a minimal and ambulatory manner during over-ground gait.

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