Automated pavement horizontal curve measurement methods based on inertial measurement unit and 3D profiling data

Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.

Is clinically measured knee range of motion after total knee arthroplasty‘good enough?’:A feasibility study using wearable inertial measurement units to compare knee range of motion captured during physical therapy versus at home

Total knee arthroplasty is highly successful,in part due to range of motion(RoM)recovery.This is typically estimated goniometrically/visually by physical therapists(PTs)in the clinic,which is imprecise.Accordingly,a validated inertial measurement unit(IMU)method for capturing knee RoM was deployed assessing postoperative RoM both in and outside of the clinical setting.The study's objectives were to evaluate the feasibility of continuously capturing knee RoM pre-/post-op via IMUs,dividing data into PT/non-PT portions of each day,and comparing PT/non-PT metrics.We hypothesized IMU-based clinical knee RoM would differ from IMU-based knee RoM captured outside clinical settings.10 patients(3 M,69±13 years)completed informed consent documents following ethics board approval.A validated IMU method captured long duration(8–12 h/day,~50 days)knee RoM pre-/post-op.Post-op metrics were subdivided(PT versus non-PT).Clinical RoM and patient reported outcome measures were also captured.Compliance and clinical disruption were evaluated.ANOVA compared post-op PT and non-PT means and change scores.Maximum flexion during PT was less than outside PT.PT stance/swing RoM and activity level were greater than outside PT.No temporal variable differences were found PT versus non-PT.IMU RoM measurements capture richer information than clinical measures.Maximum PT flexion was likely less than non-PT due to the exercises completed(i.e.high passive RoM vs.low RoM gait).PT gait flexion likely exceed non-PT because of‘white coat effects’wherein patients are closely monitored clinically.This implies data captured clinically represents optimum performance whereas data captured non-clinically represents realistic performance.

Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

Implementation and Validation of a Stride Length Estimation Algorithm,Using a Single Basic Inertial Sensor on Healthy Subjects and Patients Suffering from Parkinson’s Disease

As low cost and highly portable sensors, inertial measurements units (IMU) have become increas-ingly used in gait analysis, embodying an efficient alternative to motion capture systems. Mean-while, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gy-rometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson’s disease (PD). Estimated stride lengths were compared to GAITRite? walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the in-stantaneous stride length and opens the way to promising applications.

HUID:DBN-Based Fingerprint Localization and Tracking System with Hybrid UWB and IMU

High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID system.In particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization precision.To tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS conditions.Then,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization precision.The experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.

Robust and Accurate Monocular Visual Navigation Combining IMU for a Quadrotor

In this paper, we present a multi-sensor fusion based monocular visual navigation system for a quadrotor with limited payload, power and computational resources. Our system is equipped with an inertial measurement unit(IMU), a sonar and a monocular down-looking camera. It is able to work well in GPS-denied and markerless environments. Different from most of the keyframe-based visual navigation systems, our system uses the information from both keyframes and keypoints in each frame. The GPU-based speeded up robust feature(SURF)is employed for feature detection and feature matching. Based on the flight characteristics of quadrotor, we propose a refined preliminary motion estimation algorithm combining IMU data.A multi-level judgment rule is then presented which is beneficial to hovering conditions and reduces the error accumulation effectively. By using the sonar sensor, the metric scale estimation problem has been solved. We also present the novel IMU+3P(IMU with three point correspondences) algorithm for accurate pose estimation. This algorithm transforms the 6-DOF pose estimation problem into a 4-DOF problem and can obtain more accurate results with less computation time. We perform the experiments of monocular visual navigation system in real indoor and outdoor environments. The results demonstrate that the monocular visual navigation system performing in real-time has robust and accurate navigation results of the quadrotor.

THE EFFECT OF IMU INACCURACIES ON AIRBORNE SAR IMAGING

When using motion compensation approaches based on the measurement of motion sensors, the residual uncompensated motion errors due to measurement instrument inaccuracies contribute to phase errors and hence degrade Synthetic Aperture Radar (SAR) images. This paper presents a model to compute the phase error caused by Inertial Measurement Unit (IMU) measurement inaccuracies. By analyzing SAR motion compensation method and the effect of lever arm, this model derives the con-tribution of each term of IMU inaccuracies towards the residual uncompensated motion errors and provides a method to calculate each order of the residual phase error. According to the model, com-puted results of the airborne X-band SAR system with POS AV510 accord closely with the actual image quality.

Intelligently Tuned Wavelet Parameters for GPS/INS Error Estimation

This paper presents a new algorithm for de-noising global positioning system （GPS） and inertial navigation system （INS） data and estimates the INS error using wavelet multi-resolution analysis algorithm （WMRA）-based genetic algorithm （GA） with a well-designed structure appropriate for practical and real time implementations because of its very short training time and elevated accuracy. Different techniques have been implemented to de-noise and estimate the INS and GPS errors. Wavelet de-noising is one of the most exploited techniques that have been recently used to increase the precision and reliability of the integrated GPS/INS navigation system. To ameliorate the WMRA algorithm, GA was exploited to optimize the wavelet parameters so as to determine the best wavelet filter, thresholding selection rule （TSR）, and the optimum level of decomposition （LOD）. This results in increasing the robustness of the WMRA algorithm to estimate the INS error. The proposed intelligent technique has overcome the drawbacks of the tedious selection for WMRA algorithm parameters. Finally, the proposed method improved the stability and reliability of the estimated INS error using real field test data.

Microminiature Inertial Measurement System and Its Applications

The microminiature inertial measurement system, a new style of inertial measurement system, has many advantages compared with traditional systems, such as small size, low mass, low cost, low power consumption, high bearing capacity, and long life. Undoubtedly, it will have wide applications in military and commercial fields. However, current micro inertial sensors do not have sufficient accuracy, so, its applications are limited to some extent. This paper describes a microminiature inertial measurement system and its design, operating theory and error control techniques. In addition, its performance and applications are evaluated.

Numerical algorithm for rigid body position estimation using the quaternion approach

This paper deals with rigid body attitude estimation on the basis of the data obtained from an inertial measurement unit mounted on the body. The aim of this work is to present the numerical algorithm, which can be easily applied to the wide class of problems concerning rigid body positioning, arising in aerospace and marine engineering, or in increasingly popular robotic systems and unmanned aerial vehicles. Following the considerations of kinematics of rigid bodies, the relations between accelerations of different points of the body are given. A rotation matrix is formed using the quaternion approach to avoid singularities. We present numerical procedures for determination of the absolute accelerations of the center of mass and of an arbitrary point of the body expressed in the inertial reference frame, as well as its attitude. An application of the algorithm to the example of a heavy symmetrical gyroscope is presented, where input data for the numerical procedure are obtained from the solution of differential equations of motion, instead of using sensor measurements.

MOTION COMPENSATION FOR HIGH RESOLUTION AIRBORNE SAR WITH IMU & GPS

Inertial measurement unit (IMU) is a standard motion sensor in modern airborne SAR systems. But how to remove its systematic error is a difficult problem, which impacts the improvement of resolution in azimuth. The technique of motion compensation presented in this paper, uses the GPS as a reference system to estimate and correct the systematic error of the IMU on the concept of linear unbiased minimum variance (LUMV). This new and effective method achieves very accurate position measurement (both high and low frequency) of the APC in not only short but also long terms, so that it can satisfy the requirement of high resolution airborne SAR. In the last section of the paper, some experimental simulations from raw data are given.

High Precision Fiber SINS with Spin Technology

Fiber strapdown inertial navigation system （FSINS） is presently used in several applications related to marine navigation. However, the absolute position from FSINS contains the error that increases with time, which prevents its long-term use for the ship cruise. In order to improve the performance of FSINS based on our present inertial sensors, the spin technology was proposed in the system to mitigate the navigation errors and a prototype of the proposed system was developed in Navigation Lab. The prototype contains the IMU, temperature controller, rotating configuration, navigation and I/O electronics group, control and display, power supply subsystem and other modules. In the proposed spin technology, the IMU is rotated back and forth in azimuth through four orthogonal positions relative to the ship’s longitudinal axis. Experimental testing was conducted for the prototype in the laboratory and the results showed that the RFSINS’s navigation performance is improved 10 times.

Technological advancements in the analysis of human motion and posture management through digital devices

Technological development of motion and posture analyses is rapidly progressing,especially in rehabilitation settings and sport biomechanics.Consequently,clear discrimination among different measurement systems is required to diversify their use as needed.This review aims to resume the currently used motion and posture analysis systems,clarify and suggest the appropriate approaches suitable for specific cases or contexts.The currently gold standard systems of motion analysis,widely used in clinical settings,present several limitations related to marker placement or long procedure time.Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies,especially outside laboratories.Similarly,new posture analysis techniques are emerging,often driven by the need for fast and non-invasive methods to obtain high-precision results.These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies.The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient.Herein,these devices and their uses are described,providing researchers,clinicians,orthopedics,physical therapists,and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis,therapy,and prevention.

An Improved Torque Sensorless Speed Control Method for Electric Assisted Bicycle With Consideration of Coordinate Conversion

In this paper,we propose an improved torque sensorless speed control method for electric assisted bicycle,this method considers the coordinate conversion.A low-pass filter is designed in disturbance observer to estimate and compensate the variable disturbance during cycling.A DC motor provides assisted power driving,the assistance method is based on the realtime wheel angular velocity and coordinate system transformation.The effect of observer is proved,and the proposed method guarantees stability under disturbances.It is also compared to the existing methods and their performances are illustrated through simulations.The proposed method improves the performance both in rapidity and stability.

Design of Automatic Batch Calibration and Correction System for IMU

Thanks to its light weight,low power consumption,and low price,the inertial measurement units(IMUs)have been widely used in civil and military applications such as autopilot,robotics,and tactical weapons.The calibration is an essential procedure before the IMU is put in use,which is generally used to estimate the error parameters such as the bias,installation error,scale factor of the IMU.Currently,the manual one-by-one calibration is still the mostly used manner,which is low in efficiency,time-consuming,and easy to introduce mis-operation.Aiming at this issue,this paper designs an automatic batch calibration method for a set of IMUs.The designed automatic calibration master controller can control the turntable and the data acquisition system at the same time.Each data acquisition front-end can complete data acquisition of eight IMUs one time.And various scenarios of experimental tests have been carried out to validate the proposed design,such as the multi-position tests,the rate tests and swaying tests.The results illustrate the reliability of each function module and the feasibility automatic batch calibration.Compared with the traditional calibration method,the proposed design can reduce errors caused by the manual calibration and greatly improve the efficiency of IMU calibration.

Seamless Indoor-Outdoor Switching Localization Algorithm based on CKF

To solve the problem of large positioning error and discontinuous positioning of special forces members when moving in cross-region indoors and outdoors, and to compensate for the linearization error and local convergence problem that may exist in the extended Kalman filter(EKF)in nonlinear systems, that is,the iterative results may be trapped in a local optimum situation, a seamless indoor-outdoor switching localization algorithm based on cubature Kalman filter (CKF) is proposed. CKF does not require the computation of Jacobian matrices, which can improve computational efficiency and filtering accuracy to a certain extent. In the system, an inertial measurement unit (IMU) is employed to correct the positioning errors of ultra-wideband (UWB)and BeiDou navigation satellite system(BDS).The positioning data from UWB and BeiDou in cross-region are weighted fused and then fused with the data from the IMU using CKF to obtain the final accurate positioning information. This study designs a scene-switching mechanism to achieve seamless switching between indoor and outdoor positioning scenes. By jointly analyzing the positioning accuracy of UWB and BeiDou,the positioning scene is determined, and appropriate counting thresholds are set to avoid frequent erroneous scene switches. Experimental results show that the proposed algorithm achieves a positioning accuracy of approximately 21.7 cm in cross-region,which can enable seamless integration of indoor and outdoor positioning,avoid positioning jumps, and enhance positioning accuracy.

A robust optical/inertial data fusion system for motion tracking of the robot manipulator

We present an optical/inertial data fusion system for motion tracking of the robot manipulator, which is proved to be more robust and accurate than a normal optical tracking system(OTS). By data fusion with an inertial measurement unit(IMU), both robustness and accuracy of OTS are improved. The Kalman filter is used in data fusion. The error distribution of OTS pro-vides an important reference on the estimation of measurement noise using the Kalman filter. With a proper setup of the system and an effective method of coordinate frame synchronization, the results of experiments show a significant improvement in terms of robustness and position accuracy.

Inertial Motion Tracking on Mobile and Wearable Devices:Recent Advancements and Challenges

Motion tracking via Inertial Measurement Units(IMUs)on mobile and wearable devices has attracted significant interest in recent years.High-accuracy IMU-tracking can be applied in various applications,such as indoor navigation,gesture recognition,text input,etc.Many efforts have been devoted to improving IMU-based motion tracking in the last two decades,from early calibration techniques on ships or airplanes,to recent arm motion models used on wearable smart devices.In this paper,we present a comprehensive survey on IMU-tracking techniques on mobile and wearable devices.We also reveal the key challenges in IMU-based motion tracking on mobile and wearable devices and possible directions to address these challenges.

A gyroscope-based system for intraoperative measurement of tibia coronal plane alignment in total knee arthroplasty

Coronal plane alignment in total knee arthroplasty(TKA)is an important predictor of clinical outcomes including patient satisfaction and device longevity.Radiography and computer assisted navigation are the two primary technologies currently available to surgeons for intraoperative assessment of alignment;however,neither is particularly well-suited for use in this increasingly high volume procedure.Herein we propose a novel gyroscopebased instrument for intraoperative validation of tibia coronal plane alignment,and provide initial analytical and experimental performance assessments.The gyroscope-based alignment estimate is derived from simplified joint geometry and verified experimentally using a custom tibial trial insert containing a consumer-grade inertial measurement unit(IMU).Average accuracy of the gyroscope-based tibia coronal angle estimate was found to be within
1in mechanical leg jig and cadaver testing.These results indicate that the proposed gyroscope-based method shows promise for low cost,accurate intraoperative validation of limb alignment in TKA patients.Integrating IMU technology into the TKA surgical workflow via low-cost instrumentation will enable surgeons to easily validate implant alignment in real time,thereby reducing cost,operating room time,and future revision burden.

Fuzzy Logic Control of a Head-movement Based Semi-autonomous Human–machine Interface

Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–machine interface which is controlled by human head movements is designed and implemented.The proposed system enables users to steer the desired movement direction and to control the speed of an output device by using head movements.Head movements of the users are detected using a 6 DOF IMUs measuring three-axis accelerometer and three-axis gyroscope.The head movement axes and the Euler angles have been associated with movement direction and speed,respectively.To ensure driving safety,the speed of the system is determined by considering the speed requested by the user and the obstacle distance on the route.In this context,fuzzy logic algorithm is employed for closed-loop speed control according to distance sensors and reference speed data.A car model was used as the output device on the machine interface.However,the wireless communication between human and machine interfaces provides to adapt this system to any remote device or systems.The implemented system was tested by five subjects.Performance of the system was evaluated in terms of task completion times and feedback from the subjects about their experience with the system.Results indicate that the proposed system is easy to use;and the control capability and usage speed increase with user experience.The control speed is improved with the increase in user experience.