Average Position Error Research Articles

Genesis and track prediction of pre-monsoon cyclonic storms over North Indian Ocean in a multi-model ensemble framework

An attempt has been made in this study to evaluate the performance of a multi-model ensemble prediction system (MMEPS) in the extended range prediction of genesis and track of cyclonic storms (CS) over North Indian Ocean (NIO) during the onset phase of Indian summer monsoon. The MMEPS comprises of National Centres for Environmental Prediction Climate Forecast System version 2 and its atmospheric component, Global Forecast System version 2, at two different resolutions. In this study, we analyse the performance of this MMEPS in the prediction of six CS cases formed around the onset phase of the Indian summer monsoon over NIO. Along with this, we evaluate the usefulness of the genesis potential parameter used by India Meteorological Department (IMD) for the real-time cyclogenesis prediction. ERA-Interim re-analysis data sets are used to compare MME predictions from two initial conditions (IC) close to the genesis date of each storm. Results show that genesis forecasts from nearest available IC is capturing the vorticity and associated features of the storm better than far-IC. A modified version of vortex tracking scheme developed by Geophysical Fluid Dynamics Laboratory is used to obtain the mean track positions from MME outputs and compare with IMD-best tracks. Track verification is done by calculating average direct position error, cross-track error and along-track error against corresponding IMD-best tracks. It is found that track predictions from both near and far ICs have lower average errors initially with near-IC having lesser errors as compared to far-IC. Along-track error for pre-genesis track prediction from far-IC implies that the predicted tracks remarkably lag behind observed tracks for most of the cases. These errors could be contributed from the inability of the models in realistically capturing the region of evolution and intensification of both thermodynamic and dynamic parameters with increasing lead time.

In row cultivation controlled by plant patterns

Information about a regular crop seeding pattern is used to locate individual crop plants seeded with a precision seeder. The amount of vegetation along each of the crop rows are monitored using a bispectral line scanning camera, this generates a vegetation coverage signal. Convolution of the vegetation coverage signal with a damped harmonic oscillation, tuned to the crop plant spacing used in the field, gives a signal with distinct peaks near the real crop plant locations.The algorithm was tested on real field data, consisting of precision seeded maize. The seeding pattern were locked, such that a crop plant in one row will be next to a crop plant in the adjacent rows. The average absolution position error from the precision seeder is estimated to be around 15.5 mm.Compared to manual annotated ground truth plant positions, the system locates individual crop plants with an average absolute position error of 20.72 mm when using information from a single crop row and an average absolution position error of 14.79 mm when utilising information from five adjacent crop rows.

Real-Time Deformation Sensing for Flexible Manipulators With Bending and Twisting

Wire-driven flexible manipulators are increasingly used in medical applications, such as minimally invasive surgeries, due to its ability to operate in confined space by deforming the backbone. Existing flexible manipulators are mostly controlled in open loop, as there lacks a proper real-time deformation sensing method. The deformation of a flexible manipulator includes both the backbone shape bending and backbone twist. Current sensing methods for flexible manipulators only consider the shape and neglect the twist. However, the twist is of equal importance as it affects the end-effector orientation. In this paper, we propose a real-time deformation sensing and reconstruction method for flexible manipulators. By employing the real-time position and orientation information of part of the backbone, e.g., the base and tip, we can estimate the deformation of the flexible manipulator with adequate accuracy. What's more, a vision-based high-precision off-line shape and posture sensing method for twisted flexible manipulators is also proposed to verify the proposed electromagnetic real-time shape and posture sensing method. Results show that the proposed method could well sense the deformation of the backbone with average position error root-mean-square (rms) 1.9 mm and average twist error rms 0.61°.

A Compensation Method for Enhancing Aviation Drilling Robot Accuracy Based on Co-Kriging

The positional error of aviation drilling robot has a great influence on the strength and lives of aircrafts in the aircraft assembly. In order to improve the position accuracy of aviation drilling robot, an error compensation method based on co-kriging is proposed in this paper. The error similarity based on the kinematic of drilling robot is proposed firstly. Then, the positional errors of a set of points in the workspace are measured by using precision laser tracker. The measurement data are used to fit the cross-variogram of positional error. After the cross-variogram is obtained, the predicted positional errors of verification points can be estimated based on co-kriging. The positions after compensation are given to the drilling robot. The proposed method is carried out on an aviation drilling robot for practical compensation to verify the correctness and effectiveness of the error compensation method. The experimental results show that the average absolute positional error is reduced to 0.1150 mm from 0.7168 mm, and that the maximum absolute positional error is reduced to 0.2664 mm from 1.3073 mm. The experimental results also demonstrate that the proposed method can improve the absolute position accuracy of aviation robot and could meet the requirement of aircraft assembly.

A compensation method based on error similarity and error correlation to enhance the position accuracy of an aviation drilling robot

The position accuracy of an aviation drilling robot has detrimental effects on the assembly quality, mechanical strength and life of an aircraft in aircraft manufacturing. To enhance the position accuracy of the robot, a compensation method based on error similarity and error correlation is proposed. Firstly, the positional error similarity in joint space based on the kinematic model of the robot and error correlation are presented to illustrate that co-kriging can be used to estimate the positional error of the robot. Then, a cross-variogram of positional errors is introduced. Co-kriging based on the cross-variogram is applied to estimate the estimated positional errors along the x, y, and z axes and the absolute positional error. The estimated values are filtered by using a median filter method to further enhance the estimation accuracy. The estimated positional errors after filtering are sent to the robot controller for compensation. Finally, simulations and experiments are respectively performed with a simulated robot and an aviation drilling robot to verify the correctness and effectiveness of the proposed method. The experimental results show that the average absolute positional error is reduced to 0.106 mm from 1.393 mm, and the maximum absolute positional error is reduced to 0.294 mm from 1.795 mm. The simulation and experimental results indicate that the proposed method can enhance the position accuracy of an aviation drilling robot and meet the tolerance requirements in aircraft assembly.

A Developmental Rehabilitation Robotic System for a Rat With Complete Thoracic Spinal Cord Injury in Quadruped Posture

Spinal cord injury (SCI) leads to the impairment of impulse conduction and subsequently to an abnormality of limbs function. To regain locomotor performance in SCI cases, we establish a robust combinatorial regenerative and rehabilitative approach to enhance axonal regeneration in the Sprague-Dawley rat with complete thoracic SCI. This system consists of a body weight support system, five-bar linkage for driving the rat's ankles, and treadmill for training motor functions. This system is tested in a rat which is totally transected at T9 and T10 of the spinal cord. A nanofiber scaffold is implanted in a gap between T9 and T10 of the spinal cord in a spinalized rat for stimulating axonal regrowth. The position errors are quantified under five static load conditions (no load, 10, 30, 60, and 100 g) and dynamic load condition. Average root mean square (RMS) position errors in x - and y- axes of the manipulator are 2.1% and 5.3%, respectively. According to a preliminary test, this system can provide the constant force to support the body weight and can drive the rat's hindlimbs without inducing anxiety or irritation. From our experiment, average RMS position errors in x - and y- axes of the manipulator are 10% and 11.7%, respectively. The contribution of this research is the developmental rehabilitation robotic system for a rat with complete thoracic SCI in quadruped posture which can provide more natural walking posture. The scope of this letter is a developmental rehabilitation robotic system.

Comparative analysis of positioning accuracy of GNSS receivers of Samsung Galaxy smartphones in marine dynamic measurements

One of the most popular functions of modern mobile phones is determining the coordinates of the device using built-in GNSS receivers. By using map images extensively available on the Internet, today's smartphones have become basic navigation devices of the average user.Mobile devices with built-in GNSS receivers are primarily used in land navigation. However, marine sailing, tourism and recreation are fields where the use of mobile phones as navigation devices is also very common. The average position errors of GNSS receivers mounted on smartphones decisively influence the ability and accuracy of navigation based on those devices.This publication analyses the accuracy of the dynamic positioning of six Samsung Galaxy smartphones during vessel manoeuvring. As part of the parallel tracking studies, the telephone positions were compared to those of precise GNSS receivers, using corrections from an active geodetic network with an accuracy of 2–3 cm (p = 0.95). As a result of the 4-h measurement, the accuracy statistics for each of the phone models were defined based on approximately 10,000 positions. Studies indicate that there are significant differences in the accuracy of positioning as performed by the models in question.

Enhanced Localization of Robotic Capsule Endoscopes Using Positron Emission Markers and Rigid-Body Transformation

Using positron emission markers for the localization of a robotic capsule endoscope is promising because it does not require onboard space or built-in battery for operation. Further, its compatibility with magnetic actuation is another significant advantage compared with conventional magnetic localization methods reported in the literature. In this paper, we propose a new tracking algorithm based on rigid-body transformation and gamma rays emitted from three positron emission markers onboard to localize an endoscopic capsule operating within the gastrointestinal tract of the human body. Different from traditional rigid-body transformation based on datasets of 3-D points, our method estimates the transformation parameters (e.g., translation vector and rotation angle) from several groups of 3-D lines in order to determine the locations of the markers emitting the gamma rays. Validated by both simulation data using a voxelized phantom in the Geant4 Application for Emission Tomography toolkit and the experimental data collected from a positron emission tomography scanner, the new localization method shows a significant improvement in the tracking accuracy (an average position error of 0.4 mm and orientation error of 1.9°) and the failure rate (18/9600 localization runs), compared to the localization results reported in the literature.

Medium‐Range Forecast Skill for Extraordinary Arctic Cyclones in Summer of 2008–2016

AbstractArctic cyclones (ACs) are a severe atmospheric phenomenon that affects the Arctic environment. This study assesses the forecast skill of five leading operational medium‐range ensemble forecasts for 10 extraordinary ACs that occurred in summer during 2008–2016. Average existence probability of the predicted ACs was >0.9 at lead times of ≤3.5 days. Average central position error of the predicted ACs was less than half of the mean radius of the 10 ACs (469.1 km) at lead times of 2.5–4.5 days. Average central pressure error of the predicted ACs was 5.5–10.7 hPa at such lead times. Therefore, the operational ensemble prediction systems generally predict the position of ACs within 469.1 km 2.5–4.5 days before they mature. The forecast skill for the extraordinary ACs is lower than that for midlatitude cyclones in the Northern Hemisphere but similar to that in the Southern Hemisphere.

Usability and Validation of the Smarter Balance System: An Unsupervised Dynamic Balance Exercises System for Individuals With Parkinson's Disease.

Conventional physical and balance rehabilitation programs to improve balance performance and increase postural stability are often limited due to cost, availability of physical therapists, and accessibility to rehabilitation facilities. Exercise compliance is also affected by a loss of memory and decline in motivation in prescribed home-based balance training. We have developed the smarter balance system (SBS) incorporating multimodal biofeedback (visual plus vibrotactile) intended for clinical and home-based balance rehabilitation and assessed its efficacy on physical therapists' recommended dynamic weight-shifting balance exercises (dynamic WSBE) in individuals with Parkinson's disease (PD). The SBS consists of a smartphone and custom belt housing a processing unit, miniaturized sensors, and vibrating actuators (tactors). Visual and vibrotactile biofeedback guidance during dynamic WSBE is generated by the SBS's custom app based on 90% of the user's limits of stability (LOS). Ten individuals with idiopathic PD having impaired postural stability participated in one unsupervised session comprising 24 trials of the dynamic WSBE in a laboratory setting. Participants' limits of stability (LOS) in the anterior-posterior (A/P) and medial-lateral (M/L) direction were measured at the pre- and post-session. To assess the efficacy of SBS to provide guidance during balance rehabilitation using dynamic WSBE, cross-correlation (XCOR), position error (PE), and percent of tactor activation (PTA) were measured. There was a significant increase in LOS between the pre- and post-training session in both A/P and M/L directions. The average XCOR across all participants were 0.87 (SD = 0.11) and 0.76 (SD = 0.11) for the A/P and M/L direction respectively. The average PE and PTA for the A/P direction was 1.17 deg (SD = 0.60) and 65.35% (SD = 15.1) respectively and 0.74 deg (SD = 0.28) and 31.3% (SD = 16.42) in the M/L direction respectively. There was no significant effect of trials for XCOR, PE, and PTA. Participants' LOS significantly increased after one session of the dynamic WSBE. Individuals with PD could accurately follow the target movements during the dynamic WSBE using the SBS. Future studies will assess the efficacy and acceptability of the SBS during long-term in-home rehabilitative training for balance-impaired individuals.

MRTouch: Adding Touch Input to Head-Mounted Mixed Reality.

We present MRTouch, a novel multitouch input solution for head-mounted mixed reality systems. Our system enables users to reach out and directly manipulate virtual interfaces affixed to surfaces in their environment, as though they were touchscreens. Touch input offers precise, tactile and comfortable user input, and naturally complements existing popular modalities, such as voice and hand gesture. Our research prototype combines both depth and infrared camera streams together with real-time detection and tracking of surface planes to enable robust finger-tracking even when both the hand and head are in motion. Our technique is implemented on a commercial Microsoft HoloLens without requiring any additional hardware nor any user or environmental calibration. Through our performance evaluation, we demonstrate high input accuracy with an average positional error of 5.4 mm and 95% button size of 16 mm, across 17 participants, 2 surface orientations and 4 surface materials. Finally, we demonstrate the potential of our technique to enable on-world touch interactions through 5 example applications.

A passive acoustic based system to locate leak hole in underwater natural gas pipelines

Underwater natural gas pipelines can be punctured for a variety of reasons, but the most notable are corrosion and aging. This study proposes a novel passive acoustic based system, to detect acoustic signals, locate the leak holes, and determine the size of the leak holes remotely. The nature of acoustic signals, which are generated by leakages in underwater natural gas pipelines, is also examined. The success of this proposed localization method, which is based on the received signal strength technique, is analyzed by numerical studies and simulation works. Parameters, which are used in the numerical studies, are taken from a hypothetical pipeline whose specifications are similar to Maghreb-Europe Gas pipeline. The proposed method is examined for various measurement numbers, underwater ambient noises, the diameters of the leak holes and receiver numbers. It is shown that leakages can be located with low average position errors from several kilometers by depending on underwater ambient noise, detection method, receiver number, source strength and measurement number.

Indoor Parking Localization Based on Dual Weighted Particle Filter

For successful autonomous valet parking, accurate knowledge of vehicle location in the global map is crucial. Using sensors and maps can be an alternative method for the indoor parking localization to compensate for lack of GPS coverage. However, maps only have static elements such as walls and pillars and semi-static elements such as parked vehicles are not included. Thus, sensor data rarely match with the map data due to the semi-static elements. We developed a robust localization algorithm using a laser scanner, a static map and a feature extraction algorithm. Overall map features consisted of the center positions of parking slots and pillars. Parking slot measurements were extracted from parked vehicles. Position estimation errors occur when matching the vehicle center positions to the parking slot center positions. This error can be reduced by detecting pillars and giving more weight to the observation of these static elements. The contribution of this approach is that we can use not only static objects but also semi-static objects and that position estimation error is reduced. The algorithm was evaluated in the scaled down indoor parking model. The average position errors of this algorithm are compared with errors of odometry data and SIS particle filter.

An Improved 6-D Pose Detection Method Based on Opposing-Magnet Pair System and Constraint Multiple Magnets Tracking Algorithm

Magnetic tracking method is mainly based on sensing of the magnetic field generated by the magnetic source. Usually a small permanent magnet is used as the magnetic source, and magnetic dipole model is used to estimate the magnetic field. The disadvantage of this approach is that only 5-D pose information can be estimated, but the spin rotation with respect to the direction of magnetic moment cannot be detected. In our previous work, we proposed a novel 6-D (3-D position and 3-D orientation) pose detection method, which was based on an opposing-magnet pair system. The disadvantage is that different rotational parameters may lead to the same pose result due to the symmetric structure of object magnets. In order to solve this problem, we propose an improved 6-D pose detection method in this paper, which is based on a novel constraint multiple magnets tracking algorithm. Two magnets of different sizes with opposite magnetic directions have been combined together to serve as the tracking target. By applying the constraint multi-magnet tracking algorithm, 5-D pose of each magnet can be obtained. Therefore, we can estimate the missing spin rotational information according to the relative movement between these two magnets. Experimental results verified the feasibility of the proposed method. The average position error is 2.3 mm and the orientation error is 4.36°, when the volume ratio between these two magnets is 1:1.5.

A Novel 6-D Pose Detection Method Using Opposing-Magnet Pair System

Magnetic tracking method can achieve wireless tracking and has no line-of-sight problem; therefore, it is a good choice to track micro devices inside human body for minimally invasive examination or operation. In this letter, we propose a novel six-degree-of-freedom (DoF) pose detection method, which is based on multiple magnets tracking method. Two magnets with opposite magnetic moment directions have been combined together to serve as the tracking target. By defining pose parameters based on the position and orientation constrains of the two magnets, 6-DoF pose information can be estimated with the optimization method. Experimental results verified the proposed method. The average position error is 3.5mm and the orientation error is 1.9°.

Effect of PDOP on performance of Kalman Filters for GNSS-based space vehicle position estimation

A theoretical performance analysis of Kalman Filters for Global Navigation Satellite System GNSS-based space vehicle position estimation in varying Position Dilution of Precision (PDOP) conditions is presented. The PDOP indicates the possible accuracy of GNSS measurements using Least Square Estimation (LSE). The Kalman Filter combines the knowledge of the vehicle motion with the GNSS measurements and then provides better accuracy than the LSE. For the same nonlinear vehicular motion and PDOP condition, the ratio of average position error and noise standard deviation varies depending on the type of Kalman Filter used. The presented theoretical analysis explains and characterizes this behavior for four Kalman Filters, which are the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF) and two newly developed Unscented Type Kalman Filters. The experiment shows that for highly nonlinear space vehicle motion, the performance of the UKF is better than the EKF in high PDOP conditions and all the filters perform similarly for low PDOP conditions. For a space vehicle with lower nonlinearity in the motion, the performances of all the filters are indistinguishable for any PDOP condition.

Design and Optimization Strategy of Sensor Array Layout for Magnetic Localization System

Magnetic tracking technology is emerging to provide an occlusion-free tracking scheme for the estimation of full pose of various instruments. This brings substantial benefits for intra-corporeal applications, such as tracking of flexible robots or wireless endoscopic devices, and thus is helpful for further computer-assisted diagnosis, interventions, and surgeries. Towards efficient magnetic tracking, we propose a magnetic localization and orientation system in this paper. By modeling the cylindrical magnet, the magnetic models have been compared and analyzed. Moreover, we present a sensor layout strategy based on grid method and its optimization method for better performance. Based on the magnetic model and the layout optimization results, we have built a sensor array for magnetic positioning. Extensive simulations and experiments have shown the feasibility of the proposed system with the average positional and orientational errors of $1.4 mm$ and 3.4°, respectively.

A Switched Systems Approach Based on Changing Muscle Geometry of the Biceps Brachii During Functional Electrical Stimulation

Functional electrical stimulation (FES) is commonly used for people with neurological conditions. As the muscle geometry changes (i.e., muscle lengthening/shortening), the force induced by static electrode placement may also change. Experimental results indicate that muscle forces can be increased by spatially switching stimulation as the muscle geometry changes with joint angle. In this letter, an electric field is switched between multiple electrodes placed across the biceps brachii to track a desired trajectory. A switched systems approach is used to develop a position-based switching law, including a switched robust sliding mode controller that successfully tracks the desired angular trajectory about the elbow, despite changes in muscle geometry. Lyapunov-based methods for switched systems are used to prove global exponential tracking. Experimental results from nine able-bodied subjects are presented and the developed control system achieves an average position and velocity error of −0.21 ± 1.17 deg and −0.43 ± 5.38 deg/s, respectively, and, on average, reduces fatigue by 13.6%, as compared to traditional single-electrode methods, demonstrating the performance of the uncertain nonlinear switched control system.

Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments

RGB-D sensors capture RGB images and depth images simultaneously, which makes it possible to acquire the depth information at pixel level. This paper focuses on the use of RGB-D sensors to construct a visual map which is an extended dense 3D map containing essential elements for image-based localization, such as poses of the database camera, visual features, and 3D structures of the building. Taking advantage of matched visual features and corresponding depth values, a novel local optimization algorithm is proposed to achieve point cloud registration and database camera pose estimation. Next, graph-based optimization is used to obtain the global consistency of the map. On the basis of the visual map, the image-based localization method is investigated, making use of the epipolar constraint. The performance of the visual map construction and the image-based localization are evaluated on typical indoor scenes. The simulation results show that the average position errors of the database camera and the query camera can be limited to within 0.2 meters and 0.9 meters, respectively.

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high-quality motion capture data is available in large quantities, this creates possibilities to further simplify hardware setups, by use of data-driven methods to decrease the number of body-worn sensors. In this work, we contribute to this field by analyzing the capabilities of using either artificial neural networks (eager learning) or nearest neighbor search (lazy learning) for such a problem. Sparse orientation features, resulting from sensor fusion of only five inertial measurement units with magnetometers, are mapped to full-body poses. Both eager and lazy learning algorithms are shown to be capable of constructing this mapping. The full-body output poses are visually plausible with an average joint position error of approximately 7 cm, and average joint angle error of 7. Additionally, the effects of magnetic disturbances typical in orientation tracking on the estimation of full-body poses was also investigated, where nearest neighbor search showed better performance for such disturbances.