WiFi Indoor Positioning and Tracking Algorithm Based on Compressive Sensing and Sage-Husa Adaptive Kalman Filter

Aiming at the problem that the positioning accuracy of WiFi indoor positioning technology based on location fingerprint has not reached the requirements of practical application, a WiFi indoor positioning and tracking algorithm combining adaptive affine propagation (AAPC), compressed sensing (CS) and Kalman filter is proposed. In the off-line phase, AAPC algorithm is used to generate clustering fingerprints with optimal clustering effect performance;In the online phase, CS and nearest neighbor algorithm are used for position estimation;Finally, the Kalman filter and physical constraints are combined to perform positioning and tracking. By collecting a large number of real experimental data, it is proved that the developed algorithm has higher positioning accuracy and more accurate trajectory tracking effect.

REAL-TIME TRACKING FOR FAST MOVING OBJECT ON COMPLEX BACKGROUND

A real-time tracking system for the fast moving object on the complex background is proposed.The Markov random filed（MRF）model based background subtraction algorithm is used to detect the changing pixels and track the moving object.The prior probability of the segmentation mask is modeled by using MRF,and the object tracking task is translated into the maximum a-posterior（MAP）problem.Experimental results show that the method is efficient at both offline and online moving objects on simple and complex background.

Strong Tracking Particle Filter Based on the Chi-Square Test for Indoor Positioning

In recent years,a number of wireless indoor positioning(WIP),such as Bluetooth,Wi-Fi,and Ultra-Wideband(UWB)technologies,are emerging.However,the indoor environment is complex and changeable.Walls,pillars,and even pedestrians may block wireless signals and produce non-line-of-sight(NLOS)deviations,resulting in decreased positioning accuracy and the inability to provide people with real-time continuous indoor positioning.This work proposed a strong tracking particle filter based on the chi-square test(SPFC)for indoor positioning.SPFC can fuse indoor wireless signals and the information of the inertial sensing unit(IMU)in the smartphone and detect the NLOS deviation through the chi-square test to avoid the influence of the NLOS deviation on the final positioning result.Simulation experiment results show that the proposed SPFC can reduce the positioning error by 15.1%and 12.3% compared with existing fusion positioning systems in the LOS and NLOS environment.

Novel Real-Time Seam Tracking Algorithm Based on Vector Angle and Least Square Method

Real-time seam tracking can improve welding quality and enhance welding efficiency during the welding process in automobile manufacturing.However,the teaching-playing welding process,an off-line seam tracking method,is still dominant in automobile industry,which is less flexible when welding objects or situation change.A novel real-time algorithm consisting of seam detection and generation is proposed to track seam.Using captured 3D points,space vectors were created between two adjacent points along each laser line and then a vector angle based algorithm was developed to detect target points on the seam.Least square method was used to fit target points to a welding trajectory for seam tracking.Furthermore,the real-time seam tracking process was simulated in MATLAB/Simulink.The trend of joint angles vs.time was logged and a comparison between the off-line and the proposed seam tracking algorithm was conducted.Results show that the proposed real-time seam tracking algorithm can work in a real-time scenario and have high accuracy in welding point positioning.

A machine vision approach to seam tracking in real-time in PAW of large-diameter stainless steel tube

Manual monitoring and seam tracking through watching weld pool images in real-time, by naked eyes or by industrial TV, are experience-depended, subjective, labor intensive, and sometimes biased. So it is necessary to realize the automation of computer-aided seam tracking. A PAW (plasma arc welding) seam tracking system was developed, which senses the molten pool and the seam in one frame by a vision sensor, and then detects the seam deviation to adjust the work piece motion adaptively to the seam position sensed by vision sensor. A novel molten pool area image-processing algorithm based on machine vision was proposed. The algorithm processes each image at the speed of 20 frames/second in real-time to extract three feature variables to get the seam deviation. It is proved experimentally that the algorithm is very fast and effective. Issues related to the algorithm are also discussed.

Real-Time Front Vehicle Detection Algorithm Based on Local Feature Tracking Method

This paper proposes an algorithm that extracts features of back side of the vehicle and detects the front vehicle in real-time by local feature tracking of vehicle in the continuous images.The features in back side of the vehicle are vertical and horizontal edges,shadow and symmetry.By comparing local features using the fixed window size,the features in the continuous images are tracked.A robust and fast Haarlike mask is used for detecting vertical and horizontal edges,and shadow is extracted by histogram equalization,and the sliding window method is used to compare both side templates of the detected candidates for extracting symmetry.The features for tracking are vertical edges,and histogram is used to compare location of the peak and magnitude of the edges.The method using local feature tracking in the continuous images is more robust for detecting vehicle than the method using single image,and the proposed algorithm is evaluated by continuous images obtained on the expressway and downtown.And it can be performed on real-time through applying it to the embedded system.

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅰ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Car-tesian space mainly through increasing the number of knots on the path and the number of the path′s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot′s hand and does not change the number of the path′s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots.

A Real-time Face/Hand Tracking Method for Chinese Sign Language Recognition

This paper introduces a new Chinese Sign Language recognition (CSLR) system and a method of real time tracking face and hand applied in the system. In the method, an improved agent algorithm is used to extract the region of face and hand and track them. Kalman filter is introduced to forecast the position and rectangle of search, and self adapting of target color is designed to counteract the effect of illumination.

Performance analysis of real-time and post-mission kinematic precise point positioning in marine environments

This article focuses on the performance analysis of both real-time and post-mission kinematic precise point positioning(PPP)in challenging marine environments.For this purpose,a real dynamic experiment lasting 6 h was carried out on a lake dam in?orum City of Turkey.While the kinematic test was continuing,the real-time PPP coordinates were obtained for each measurement epoch with a commercial real-time PPP(RT-PPP)service,namely the Trimble Center Point RTX.Then the post-mission PPP(PM-PPP)coordinates were calculated by using Multi-GNSS data and the Multi-GNSS Experiment(MGEX)precise products.The kinematic RT-PPP and PM-PPP results showed that the PPP coordinates were consistent with the relative solution at centimetre and decimetre level in horizontal and height components,respectively.This study implies that PPP technique is a powerful tool for highly accurate positioning in both real-time and post-mission modes,even for dynamic applications in harsh environments.

Dynamic Visible Light Positioning Based on Enhanced Visual Target Tracking

In visible light positioning systems,some scholars have proposed target tracking algorithms to balance the relationship among positioning accuracy,real-time performance,and robustness.However,there are still two problems:(1)When the captured LED disappears and the uncertain LED reappears,existing tracking algorithms may recognize the landmark in error;(2)The receiver is not always able to achieve positioning under various moving statuses.In this paper,we propose an enhanced visual target tracking algorithm to solve the above problems.First,we design the lightweight recognition/demodulation mechanism,which combines Kalman filtering with simple image preprocessing to quickly track and accurately demodulate the landmark.Then,we use the Gaussian mixture model and the LED color feature to enable the system to achieve positioning,when the receiver is under various moving statuses.Experimental results show that our system can achieve high-precision dynamic positioning and improve the system’s comprehensive performance.

Performance Evaluation of Three-Dimensional UWB Real-Time Locating Auto-Positioning System for Fire Rescue

Fire rescue challenges and solutions have evolved from straightfor-ward plane rescue to encompass 3D space due to the rise of high-rise city buildings.Hence,this study facilitates a system with quick and simplified on-site launching and generates real-time location data,enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise rescue.Auto-positioning with step-by-step instructions is proposed when launching the locating system,while no extra measuring instrument like Total Station(TS)is needed.Real-time location tracking is provided via a 3D space real-time locating system(RTLS)constructed using Ultra-wide Bandwidth technology(UWB),which requires electromagnetic waves to pass through concrete walls.A hybrid weighted least squares with a time difference of arrival(WLS/TDOA)positioning method is proposed to address real path-tracking issues in 3D space and to meet RTLS requirements for quick computing in real-world applications.The 3D WLS/TDOA algorithm is theoretically constructed with the Cramer-Rao lower bound(CRLB).The computing complexity is reduced to the lower bound for embedded hardware to directly compute the time differential of the arriving signals using the time-to-digital converter(TDC).The results of the experiments show that the errors are controlled when the positioning algorithm is applied in various complicated situations to fulfill the requirements of engineering applications.The statistical analysis of the data reveals that the proposed UWB RTLS auto-positioning system can track target tags with an accuracy of 0.20 m.

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅱ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Cartesian space mainly through increasing the number of knots on the path and the segments of the path. But, this method resulted in the heavier on line computational burden for the robot controller. In this paper, aiming at this drawback, the authors propose a new kind of real time accurate hand path tracking and joint trajectory planning method for robots. Through selecting some extra knots on the specified hand path by a certain rule, which enables the number of knots on each segment to increase from two to four, and through introducing a sinusoidal function and a cosinoidal function to the joint displacement equation of each segment, this method can raise the path tracking accuracy of robot′s hand greatly but does not increase the computational burden of robot controller markedly.

Real-time tracking of deformable objects based on MOK algorithm

The traditional oriented FAST and rotated BRIEF（ORB） algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB（MORB） algorithm is proposed. In order to improve the precision of matching and tracking, this paper puts forward an MOK algorithm that fuses MORB and Kanade-Lucas-Tomasi（KLT）. By using Kalman, the object＇s state in the next frame is predicted in order to reduce the size of search window and improve the real-time performance of object tracking. The experimental results show that the MOK algorithm can accurately track objects with deformation or with background clutters, exhibiting higher robustness and accuracy on diverse datasets. Also, the MOK algorithm has a good real-time performance with the average frame rate reaching 90.8 fps.

The linear position tracking servo systemusing a linear voice-coil motor

More and more linear servo systems have been used in servo applications. Direct drive technology can greatly increase the bandwidth and the tracking accuracy. A position servo-system based on linear voice-coil motor was designed for one linear oscillation movement application. Besides the conventional position, speed and current control loops, the speed and acceleration feed-forward control of command position signal were also used. The experimental test proved the correctness of the design, and the system can track the given periodic sinusoid position command signal of 15Hz with high accuracy. The linear voice-coil motor is very suitable for short stroke position tracking application with high dynamic response.

Exploration of instantaneous frequency for local control assessment in real-time hybrid simulation

Local control parameters such as instantaneous delay and instantaneous amplitude play an essential role in evaluating the performance and maintaining the stability of real-time hybrid simulation(RTHS).However,existing methods have limitations in obtaining this local assessment in either the time domain or frequency domain.In this study,the instantaneous frequency is introduced to determine local control parameters for actuator tracking assessment in a real-time hybrid simulation.Instantaneous properties,including amplitude,delay,frequency and phase,are then calculated based on analytic signals translated from actuator tracking signals through the Hilbert transform.Potential issues are discussed and solutions are proposed for calculation of local control parameters.Numerical simulations are first conducted for sinusoidal and chirp signals with time varying amplitude error and delay to demonstrate the potential of the proposed method.Laboratory tests also are conducted for a predefined random signal as well as the RTHS of a single degree of freedom structure with a self-centering viscous damper to experimentally verify the effectiveness of the proposed use of the instantaneous frequency.Results from the ensuing analysis clearly demonstrate that the instantaneous frequency provides great potential for local control assessment,and the proposed method enables local tracking parameters with good accuracy.

Speed-assigned Position Tracking Control of SRM With Adaptive Backstepping Control

A novel speed-assigned method is applied to the position tracking control of switched reluctance motor(SRM).A speed control freedom can be drawn into the position control through speed assignment. Adaptive backstepping control is used to design the position controller for the SRM. The accuracy of position tracking of the SRM can be enhanced with speed assignment. A disturbance observer is further designed to enhance the estimation accuracy of the unknown load torque. Simulation results certify that the design scheme is right and effective.

An Analysis on Position Estimation, Drifting and Accumulated Error Accuracy during 3D Tracking in Electronic Handheld Devices

This work focuses on a brief discussion of new concepts of using smartphone sensors for 3D painting in virtual or augmented reality. Motivation of this research comes from the idea of using different types of sensors which exist in our smartphones such as accelerometer, gyroscope, magnetometer etc. to track the position for painting in virtual reality, like Google Tilt Brush, but cost effectively. Research studies till date on estimating position and localization and tracking have been thoroughly reviewed to find the appropriate algorithm which will provide accurate result with minimum drift error. Sensor fusion, Inertial Measurement Unit (IMU), MEMS inertial sensor, Kalman filter based global translational localization systems are studied. It is observed, prevailing approaches consist issues such as stability, random bias drift, noisy acceleration output, position estimation error, robustness or accuracy, cost effectiveness etc. Moreover, issues with motions that do not follow laws of physics, bandwidth, restrictive nature of assumptions, scale optimization for large space are noticed as well. Advantages of such smartphone sensor based position estimation approaches include, less memory demand, very fast operation, making them well suited for real time problems and embedded systems. Being independent of the size of the system, they can work effectively for high dimensional systems as well. Through study of these approaches it is observed, extended Kalman filter gives the highest accuracy with reduced requirement of excess hardware during tracking. It renders better and faster result when used in accelerometer sensor. With the aid of various software, error accuracy can be increased further as well.

基于射波刀Xsight spine prone tracking模式治疗脊柱肿瘤患者的摆位准确性分析

目的:射波刀脊柱肿瘤治疗提供了两种追踪模式,即脊柱追踪系统(Xsight spine tracking,XST)和俯卧位脊柱追踪系统(Xsight spine prone tracking,XSPT)。本研究通过比较两种脊柱追踪模式的摆位误差,评估射波刀采用XSPT模式治疗脊柱肿瘤患者的摆位准确性。方法:回顾性分析2020年7月至2021年6月在北京大学第三医院行射波刀治疗的腰骶脊柱肿瘤患者18例,分别采用仰卧位(真空垫固定)和俯卧位(热塑体网与俯卧板固定)进行CT模拟定位。按照XST与XSPT两种追踪方式设计治疗计划,治疗中分别记录两种体位脊柱追踪的摆位修正误差,平移修正为进出、左右、升降方向,角度修正为顺时针-逆时针旋转、仰俯、倾斜。同时采集俯卧位治疗模式下同步呼吸追踪的相关误差。两种追踪模式的摆位修正误差参数通过配对t检验方法进行分析,比较两组修正误差的差异。同时分析俯卧位同步呼吸相关误差,评估呼吸模型的预测准确性。结果:升降方向仰卧位修正误差为(0.18±0.16)mm,俯卧位为(0.31±0.26)mm,差异具有统计学意义(P<0.05);进出方向仰卧位修正误差为(0.27±0.24)mm,俯卧位为(0.50±0.40)mm,差异具有统计学意义(P<0.05)。俯卧位呼吸模型相关误差左右、进出和升降的平均值分别为(0.21±0.11)mm、(0.41±0.38)mm和(0.68±0.42)mm。结论:治疗中受呼吸运动的影响,相比于仰卧位定位方式,俯卧位在升降与进出方向摆位误差相对较大,但俯卧位治疗方式具有同步呼吸追踪系统,且该系统可以实现治疗过程中呼吸动度的实时修正。俯卧位脊柱追踪模式的一致性与准确性同样能够满足临床治疗需求。

Robust Controller Design for Satellite Attitude Tracking System

The attitude tracking control problem for a satellite with parameter uncertainties and external disturbances is considered in this paper. For this class of multi-input multi-output uncertain nonlinear systems, a design method of robust output tracking controllers is proposed based on the upper-bounds of the uncertainties. Using the input/output feedback linearization approach and Lyapunov method, a control law is designed, which guarantees that the system output exponentially tracks the given desired output. The proposed controller is easy to compute and complement. Simulation results show that, in the closed-loop system, precise attitude control is accomplished in spite of the uncertainties in the system.

RFID Based e-quality Tracking in Service-oriented Manufacturing Execution System

The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-MES）, real-time e-quality tracking （e-QT）, in which real-time data are computed, has played more and more important roles in manufacturing. This paper presents an e-QT model through the study of real-time status data tracking and quality data collecting. An implementing architecture of the e-QT model is constructed on the basis of radio frequency identification devices （RFID） data-tracking network. In order to develop the e-QT system, some key enabling technologies, such as configuration, data collection, and data processing, etc, are studied. The relation schema between hardware is built for the RFID data-tracking network based on the configuration technique. Real-time data are sampled by using data collecting technique. Furthermore, real-time status and quality data in a shop-floor can be acquired in terms of using the real-time data computing method. Finally, a prototype system is developed and a running example is given so as to verify the feasibility of methods proposed in this paper. The proposed research provides effective e-quality tracking theoretical foundation through the use of RFID technology for the discrete manufacturing.