Xuke Xia

Investigation of the Relationship Between Tracking Accuracy and Tracking Distance of a Novel Magnetic Tracking System

The position and orientation of an object embedding with a permanent magnet can be acquired in real time via a magnetic tracking system. However, one characteristic of the magnetic tracking technique is its varied tracking accuracy along with the tracking distance. Hence, this paper tends to investigate the relationship between the tracking accuracy and the distance from the magnet to the sensor array by both simulations and experiments. Results show that the relationship is expressed as a cubic polynomial equation, and that the equation coefficients are related to the properties of the magnet and the signal-to-noise ratio of the sensor outputs. When the magnet is located at a distance from 36 to 96 mm above the sensor array, the system had the best performance, while average localization and orientation errors were 0.70 mm and 1.22°, respectively. Thus, this system achieved the best tracking accuracy compared with the state-of-the-art of magnetic tracking systems. This paper is helpful to the researchers who want to implement a magnetic tracking system or need to know clearly the valid tracking distance of a magnetic tracking system.

A three-axis magnetic sensor array system for permanent magnet tracking

Orientations and positions of a permanent magnet can be acquired via a three-axis magnetic sensor array system. Thus, the position and orientation of an object embedded with the permanent magnet can be tracked in real-time. This magnet tracking system can be adapted to medical and industrial applications. How to detect the weak magnetic signal and the sensor fusion algorithm are vitally important for the accuracy performance of the tracking system. In this study, we present a novel magnet tracking system based on nine three-axis digital magnetic sensors, instead of analog output, with the valid tracking space of 0.5m×0.5m × 0.2m. Before calibration, the system achieved average localization error at 6.62mm and 2.98°. This system has the advantages such as low power consumption, portable, and convenient configuration via a SPI bus.

Quantitative assessment of parkinsonian tremor based on a linear acceleration extraction algorithm

Abstract Tremor detection plays a crucial role in Parkinson’s disease (PD) treatment and symptom monitoring. The current gold standard for the clinical assessment of parkinsonian tremor is the evaluation using the standard clinical rating scales, which is performed by the well-trained neurologists. However, this assessment approach relies mainly on the subjective judgment of the evaluator. This study, on the basis of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) criteria, proposed a custom quantitative assessment system for parkinsonian tremors. It adopted an attitude estimation-based gradient descent algorithm to separate the linear acceleration (caused by pure translational motion) from the accelerometer output, which combines gravity component. Signal features extracted from the linear accelerations and angular velocities during the tremor tasks were fitted to the clinicians’ ratings with a multiple regression model. Clinical experiments with 34 PD patients and 14 age-matched controls demonstrated that the prediction accuracy was improved by using the decomposed linear acceleration for the extraction of tremor features, which has promoted assessment accuracy compared with the relevant literature (r2 improved from 0.89 to 0.95 for rest tremor, and from 0.90 to 0.93 for postural tremor). In addition, the prediction accuracy was worse when using only the linear accelerations for regression analysis (r2 reduced from 0.95 to 0.87 for rest tremor, and from 0.93 to 0.84 for postural tremor), which means that the effect of rotational motion cannot be ignored in tremor quantification.

An Experimental Performance Evaluation of the Orientation Accuracy of Four Nine-Axis MEMS Motion Sensors

MEMS (Micro-Electro-Mechanical Systems) inertial motion sensors have greatly improved the intelligence of wearable devices, sports fitness equipment, and consumer electronics. To avoid the disadvantages of each discrete inertial sensor, the tendency is to combine and fuse several different types of inertial motion sensors; thus, consumer-grade inertial motion sensors even have the same performance with the industrial-grade sensors. This study presents an overview of multi-axis sensor fusion algorithms and their applications. Furthermore, three typical consumer-grade AHRS (attitude and heading reference system) were verified compared with an industrial-grade sensor module (MTi-300), and three-axis orientation outputs of these sensors were compared. Static and dynamic experiment results show that MTi-300 has the best orientation accuracy (static error=0.05°, dynamic error=0.5°) compared to the other three sensor modules. Moreover, BNO055 has a better dynamic performance while compared with the other two consumer-grade motion sensors.

Analysis of a Six-Axis Industrial Robot's Dynamic Path Accuracy Based on an Optical Tracker

Although robot calibration has maturational fundamental theories, its practical application is still in the primary phase. In fact, most users are hard to manipulate an industrial robot with high absolute positioning accuracy. Thus, this study intends to measure the dynamic path accuracy of a six-axis industrial robot based on an optical tracker, instead of an expensive laser tracker. The motion tracking approach was based on three robot motions, i.e. linear motion, circular motion, and cornering motion, with a series of varied motion speeds from 100 to 800mm/s. Results show the dynamic path errors (the difference between the presupposed position and the measured position) for linear, circular, and corner motions were 0.662±0.169mm, 1.901±0.109mm, and 17.334±7.572mm, respectively. Obviously, the corner path error was far more than the other two motions. Furthermore, we found that the relationship between path error and the robot motion speed, was not completely linear. The performance assessment aims to provide feedback information for the accurate robot motion control in a specific target workspace. It is therefore of paramount importance for industrial robot users who are interested in precise applications to fully understand the test methods used for assessing robot path precision.