Robust Design of Inertial Measurement Units Based on Accelerometers

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Zhongkai Qin ◽  
Luc Baron ◽  
Lionel Birglen
Keyword(s):  
Robust Design ◽  
Inertial Measurement Unit ◽  
Angular Acceleration ◽  
Linear Acceleration ◽  
Measurement Unit ◽  
Reliable Operation ◽  
Inertial Measurement ◽  
Acceleration Data ◽  
Measurement Units ◽  
Fail Safe

This paper presents a robust design scheme for an inertial measurement unit (IMU) composed only of accelerometers. From acceleration data measured by a redundant set of accelerometers, the IMU proposed in this paper can estimate the linear acceleration, angular velocity, and angular acceleration of the rigid-body to which it is attached. The robustness of our method to the uncertainty of the locations of the sensors and the measurement noise is obtained through redundancy and optimal configuration of the onboard sensors. In addition, the fail-diagnostics and fail-safe issues are also addressed for reliable operation.

scholarly journals Accuracy and Repeatability of Spatiotemporal Gait Parameters Measured with an Inertial Measurement Unit

2021 ◽  
Vol 10 (9) ◽  
pp. 1804
Author(s):  
Jorge Posada-Ordax ◽  
Julia Cosin-Matamoros ◽  
Marta Elena Losa-Iglesias ◽  
Ricardo Becerro-de-Bengoa-Vallejo ◽  
Laura Esteban-Gonzalo ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
High Speeds ◽  
Controlled Conditions ◽  
Gait Parameters ◽  
Measurement Units ◽  
Accuracy And Repeatability

In recent years, interest in finding alternatives for the evaluation of mobility has increased. Inertial measurement units (IMUs) stand out for their portability, size, and low price. The objective of this study was to examine the accuracy and repeatability of a commercially available IMU under controlled conditions in healthy subjects. A total of 36 subjects, including 17 males and 19 females were analyzed with a Wiva Science IMU in a corridor test while walking for 10 m and in a threadmill at 1.6 km/h, 2.4 km/h, 3.2 km/h, 4 km/h, and 4.8 km/h for one minute. We found no difference when we compared the variables at 4 km/h and 4.8 km/h. However, we found greater differences and errors at 1.6 km/h, 2.4 km/h and 3.2 km/h, and the latter one (1.6 km/h) generated more error. The main conclusion is that the Wiva Science IMU is reliable at high speeds but loses reliability at low speeds.

Systematic Calibration Method for FOG Inertial Measurement Units

2013 ◽  
Vol 662 ◽  
pp. 717-720 ◽  
Author(s):  
Zhen Yu Zheng ◽  
Yan Bin Gao ◽  
Kun Peng He
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Calibration Method ◽  
State Equation ◽  
Measurement Unit ◽  
Observation System ◽  
Body Frame ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Error Coefficients

As an inertial sensors assembly, the FOG inertial measurement unit (FIMU) must be calibrated before being used. The paper presents a one-time systematic IMU calibration method only using two-axis low precision turntable. First, the detail error model of inertial sensors using defined body frame is established. Then, only velocity taken as observation, system 33 state equation is established including the lever arm effects and nonlinear terms of scale factor error. The turntable experiments verify that the method can identify all the error coefficients of FIMU on low-precision two-axis turntable, after calibration the accuracy of navigation is improved.

scholarly journals Comparison of Trotting Stance Detection Methods from an Inertial Measurement Unit Mounted on the Horse’s Limb

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2983
Author(s):  
Marie Sapone ◽  
Pauline Martin ◽  
Khalil Ben Mansour ◽  
Henry Château ◽  
Frédéric Marin
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Detection Methods ◽  
Measurement Unit ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
New Methods ◽  
Measurement Units ◽  
Ground Types ◽  
Stride Duration

The development of on-board sensors, such as inertial measurement units (IMU), has made it possible to develop new methods for analyzing horse locomotion to detect lameness. The detection of spatiotemporal events is one of the keystones in the analysis of horse locomotion. This study assesses the performance of four methods for detecting Foot on and Foot off events. They were developed from an IMU positioned on the canon bone of eight horses during trotting recording on a treadmill and compared to a standard gold method based on motion capture. These methods are based on accelerometer and gyroscope data and use either thresholding or wavelets to detect stride events. The two methods developed from gyroscopic data showed more precision than those developed from accelerometric data with a bias less than 0.6% of stride duration for Foot on and 0.1% of stride duration for Foot off. The gyroscope is less impacted by the different patterns of strides, specific to each horse. To conclude, methods using the gyroscope present the potential of further developments to investigate the effects of different gait paces and ground types in the analysis of horse locomotion.

scholarly journals A Separated Calibration Method for Inertial Measurement Units Mounted on Three-Axis Turntables

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2846 ◽  
Author(s):  
Chun-mei Dong ◽  
Shun-qing Ren ◽  
Xi-jun Chen ◽  
Zhen-huan Wang
Keyword(s):  
Inertial Measurement Unit ◽  
Functional Relationship ◽  
Calibration Method ◽  
Measurement Unit ◽  
Model Parameters ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Suboptimal Design ◽  
Calibration Accuracy ◽  
Simulation Results

Inertial Measurement Unit (IMU) calibration accuracy is easily affected by turntable errors, so the primary aim of this study is to reduce the dependence on the turntable’s precision during the calibration process. Firstly, the indicated-output of the IMU considering turntable errors is constructed and with the introduction of turntable errors, the functional relationship between turntable errors and the indicated-output was derived. Then, based on a D-suboptimal design, a calibration method for simultaneously identifying the IMU error model parameters and the turntable errors was proposed. Simulation results showed that some turntable errors could thus be effectively calibrated and automatically compensated. Finally, the theoretical validity was verified through experiments. Compared with the traditional method, the method proposed in this paper can significantly reduce the influence of the turntable errors on the IMU calibration accuracy.

scholarly journals Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4486
Author(s):  
Jeremy Cole ◽  
Alper Bozkurt ◽  
Edgar Lobaton
Keyword(s):  
Disaster Response ◽  
Inertial Measurement Unit ◽  
Optimization Problem ◽  
Low Cost ◽  
Boundary Value ◽  
Measurement Unit ◽  
Navigation Problem ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Gromphadorhina Portentosa

Disaster robotics is a growing field that is concerned with the design and development of robots for disaster response and disaster recovery. These robots assist first responders by performing tasks that are impractical or impossible for humans. Unfortunately, current disaster robots usually lack the maneuverability to efficiently traverse these areas, which often necessitate extreme navigational capabilities, such as centimeter-scale clearance. Recent work has shown that it is possible to control the locomotion of insects such as the Madagascar hissing cockroach (Gromphadorhina portentosa) through bioelectrical stimulation of their neuro-mechanical system. This provides access to a novel agent that can traverse areas that are inaccessible to traditional robots. In this paper, we present a data-driven inertial navigation system that is capable of localizing cockroaches in areas where GPS is not available. We pose the navigation problem as a two-point boundary-value problem where the goal is to reconstruct a cockroach’s trajectory between the starting and ending states, which are assumed to be known. We validated our technique using nine trials that were conducted in a circular arena using a biobotic agent equipped with a thorax-mounted, low-cost inertial measurement unit. Results show that we can achieve centimeter-level accuracy. This is accomplished by estimating the cockroach’s velocity—using regression models that have been trained to estimate the speed and heading from the inertial signals themselves—and solving an optimization problem so that the boundary-value constraints are satisfied.

scholarly journals Quantification of the relative arm-use in patients with hemiparesis using inertial measurement units

2020 ◽  
Author(s):  
Ann David ◽  
StephenSukumaran ReethaJanetSureka ◽  
Sankaralingam Gayathri ◽  
Salai Jeyseelan Annamalai ◽  
Selvaraj Samuelkamleshkumar ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Hand Dominance ◽  
Healthy Controls ◽  
Functional Movement ◽  
Inertial Measurement ◽  
Video Recordings ◽  
Measurement Units ◽  
Natural Settings ◽  
Functional Movements

Background: The most popular method for measuring upper limb activity is based on accelerometry. However, this method is prone to overestimation and is agnostic to the functional utility of a movement. In this study, we used an inertial measurement unit(IMU)-based gross movement score to quantify arm-use in hemiparetic patients at home. Objectives: (i) Validate the gross movement score detected by wrist-worn IMUs against functional movements identified by human assessors. (ii) Test the feasibility of using wrist-worn IMUs to measure arm-use in patients' natural settings. Methods: To validate the gross movement score two independent assessors analyzed and annotated the video recordings of 5 hemiparetic patients and 10 healthy controls performing a set of activities while wearing IMUs. The second study tracked arm-use of 5 hemiparetic patients and 5 healthy controls using two wrist-worn IMUs for 7 days and 3 days, respectively. The IMU data obtained from this study was used to develop quantitative measures (total and relative arm-use (RAU)) and a visualization method for arm-use. Results: The gross movement score detects functional movement with 50-60% accuracy in hemiparetic patients, and is robust to non-functional movements. Healthy controls showed a slight bias towards the dominant arm (RAU: 40.52)°. Patients' RAU varied between 15-47° depending upon their impairment level and pre-stroke hand dominance. Conclusions: The gross movement score performs moderately well in detecting functional movements while rejecting non-functional movements. The patients' total arm-use is less than healthy controls, and their relative arm-use is skewed towards the less-impaired arm.

MEMS Gyroscope Null Drift and Compensation Based on Neural Network

2011 ◽  
Vol 255-260 ◽  
pp. 2077-2081 ◽  
Author(s):  
Jaw Kuen Shiau ◽  
Der Ming Ma ◽  
Chen Xuan Huang ◽  
Ming Yu Chang
Keyword(s):  
Neural Network ◽  
Inertial Measurement Unit ◽  
Temperature Compensation ◽  
Micro Electro Mechanical System ◽  
Measurement Unit ◽  
Temperature Calibration ◽  
Inertial Measurement ◽  
Mems Gyroscope ◽  
Measurement Units ◽  
Effects Of Temperature

This study investigates the effects of temperature on micro-electro mechanical system (MEMS) gyroscope null drift and methods and efficiency of temperature compensation. First, this study uses in-house-designed inertial measurement units (IMUs) to perform temperature effect testing. The inertial measurement unit is placed into the temperature control chamber. Then, the temperature is gradually increased from 25 °C to 80 °C at approximately 0.8 degrees per minute. After that, the temperature is decreased to -40 °C and then returning to 25 °C. During these temperature variations, the temperature and static gyroscope output observes the gyroscope null drift phenomenon. The results clearly demonstrate the effects of temperature on gyroscope null voltage. A temperature calibration mechanism is established by using a neural network model. With the temperature calibration, the attitude computation problem due to gyro drifts can be improved significantly.

scholarly journals Gait Phase Detection for Lower-Limb Exoskeletons using Foot Motion Data from a Single Inertial Measurement Unit in Hemiparetic Individuals

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2988 ◽  
Author(s):  
Miguel D. Sánchez Sánchez Manchola ◽  
María J. Pinto Pinto Bernal ◽  
Marcela Munera ◽  
Carlos A. Cifuentes
Keyword(s):  
Lower Limb ◽  
Inertial Measurement Unit ◽  
Low Cost ◽  
Linear Acceleration ◽  
Measurement Unit ◽  
Phase Detection ◽  
Inertial Measurement ◽  
Phase Partitioning ◽  
Motion Data ◽  
Gait Phase

Due to the recent rise in the use of lower-limb exoskeletons as an alternative for gait rehabilitation, gait phase detection has become an increasingly important feature in the control of these devices. In addition, highly functional, low-cost recovery devices are needed in developing countries, since limited budgets are allocated specifically for biomedical advances. To achieve this goal, this paper presents two gait phase partitioning algorithms that use motion data from a single inertial measurement unit (IMU) placed on the foot instep. For these data, sagittal angular velocity and linear acceleration signals were extracted from nine healthy subjects and nine pathological subjects. Pressure patterns from force sensitive resistors (FSR) instrumented on a custom insole were used as reference values. The performance of a threshold-based (TB) algorithm and a hidden Markov model (HMM) based algorithm, trained by means of subject-specific and standardized parameters approaches, were compared during treadmill walking tasks in terms of timing errors and the goodness index. The findings indicate that HMM outperforms TB for this hardware configuration. In addition, the HMM-based classifier trained by an intra-subject approach showed excellent reliability for the evaluation of mean time, i.e., its intra-class correlation coefficient (ICC) was greater than 0 . 75 . In conclusion, the HMM-based method proposed here can be implemented for gait phase recognition, such as to evaluate gait variability in patients and to control robotic orthoses for lower-limb rehabilitation.

Verification of a special inertial measurement unit using a Quadrotor aircraft

2014 ◽  
Vol 2 (1) ◽  
pp. 40-55 ◽  
Author(s):  
Angel Flores-Abad ◽  
Pu Xie ◽  
Gabriela Martinez-Arredondo ◽  
Ou Ma
Keyword(s):  
Inertial Measurement Unit ◽  
Angular Acceleration ◽  
Flight Test ◽  
Measurement Unit ◽  
Processing Unit ◽  
Dynamics Modeling ◽  
Content Type ◽  
Inertial Measurement ◽  
Quadrotor Aircraft ◽  
Kinematics Modeling

Purpose – Calibration and 6-DOF test of a unique inertial measurement unit (IMU) using a Quadrotor aircraft. The purpose of this paper is to discuss the above issue. Design/methodology/approach – An IMU with the special capability of measuring the angular acceleration was developed and tested. A Quadrotor aircraft is used as 6-DOF test platform. Kinematics modeling of the Quadrotor was used in the determination of the Euler angles, while Dynamics modeling aided in the design the closed loop controller. For safety, the flight test was performed on a 6-DOF constrained reduced-gravity test stand. Findings – The developed IMU is suitable for measuring states and its time derivatives of mini UAVs. Not only that but also a simple control algorithm can be integrated in the same processing unit (a 32 microcontroller in this case). Originality/value – The tested IMU as well as the safety constrained test techniques are unique.

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