Markerless Respiratory Motion Tracking Using Single Depth Camera

The aim of this study is to propose a novel system that has an ability to detect intra-fractional motion during radiotherapy treatment in real-time using three-dimensional surface taken by a depth camera, Microsoft Kinect v1. Our approach introduces three new aspects for three-dimensional surface tracking in radiotherapy treatment. The first aspect is a new algorithm for noise reduction of depth values. Ueda’s algorithm was implemented and enabling a fast least square regression of depth values. The second aspect is an application for detection of patient’s motion at multiple points in thracoabdominal regions. The third aspect is an estimation of three-dimensional surface from multiple depth values. For evaluation of noise reduction by Ueda’s algorithm, two respiratory patterns are measured by the Kinect as well as a laser range meter. The resulting cross correlation coefficients between the laser range meter and the Kinect were 0.982 for abdominal respiration and 0.995 for breath holding. Moreover, the mean cross correlation coefficients between the signals of our system and the signals of Anzai with respect to participant’s respiratory motion were 0.90 for thoracic respiration and 0.93 for abdominal respiration, respectively. These results proved that the performance of the developed system was comparable to existing motion monitoring devices. Reconstruction of three-dimensional surface also enabled us to detect the irregular motion and breathing arrest by comparing the averaged depth with predefined threshold values.

Reliability of Passive Physical Activity Assessment for Inpatients Using Marker⁃Free Motion Tracking System

Evidence⁃based practices of public health will benefit from quantification of passive physical activity assessment.This study aims to investigate the reliability of marker⁃free system(MFS)such as Microsoft Kinect in measuring upper extremity motion from different angles.Ten healthy participants performed elbow and shoulder extension/flexion along frontal and median anatomical planes for ten pace⁃controlled repetitions,during which the spatiotemporal positions of upper extremity joints were concurrently recorded by two sensors from 0°and 45°viewing angles.Reliability between the two sensors were evaluated using Pearson correlation coefficient,intra⁃class correlation coefficients,and 95%limits of agreement and coefficient of variation.Worse reliability was observed when possibility of occlusion was higher.However,better reliability was found when longer observation interval(10 s)was used as elementary measuring unit than shorter observation interval(2 s).The overall angular reliability of activity as displacement or changes in angle was not satisfactory.The results are expected to inform the industry for the extension of MFS to clinic applications.

Motion Tracking with Fast Adaptive Background Subtraction

To extract and tr ack moving objects is usually one of the most important tasks of intelligent video surveillance systems. This paper presents a fast and adaptive background subtraction algorithm and the motion tracking process using this algorithm. The algorithm uses only luminance components of sampled image sequence pixels and models every pixel in a statistical model. The algorithm is characterized by its ability of real time detecting sudden lighting changes, and extracting and tracking motion objects faster. It is shown that our algorithm can be realized with lower time and space complexity and adjustable object detection error rate with comparison to other background subtraction algorithms. Making use of the algorithm, an indoor monitoring system is also worked out and the motion tracking process is presented in this paper. Experimental results testify the algorithm's good performances when used in an indoor monitoring system.

Experimental Simulation and Analysis of the Yarn Motion Track in a Hairiness-Reducing Nozzle

A visible magnified and simulated nozzle was designed and installed on a winding machine according to the similarity principle of Reynolds number,to study the yarn motion track in hairiness-reducing nozzle.High-speed photography was used to observe the yarn instantaneous motion state in the nozzle.The results show that the yarn motion track seems to be a cylindrical helix which is close to inner wall in the twisting chamber and kept the same with different technical parameters,such as diameter of the twisting chamber and jet pressure in orifices.According to simulation results and reasonable simplification,the motion track equation and the rotational equation of the yarn could be derived.The velocity of the swirl and hairiness is faster than that of the yarn balloon,so there is enough time for hairiness to be wrapped into the main body of yarn and hence the hairiness is reduced.

Aye-aye middle finger kinematic modeling and motion tracking during tap-scanning

The aye-aye(Daubentonia madagascariensis)is a nocturnal lemur native to the island of Madagascar with a unique thin middle finger.Its slender third digit has a remarkably specific adaptation,allowing them to perform tap-scanning to locate small cavities beneath tree bark and extract wood-boring larvae from it.As an exceptional active acoustic actuator,this finger makes an aye-aye’s biological system an attractive model for pioneering Nondestructive Evaluation(NDE)methods and robotic systems.Despite the important aspects of the topic in the aye-aye’s unique foraging and its potential contribution to the engineering sensory,little is known about the mechanism and dynamics of this unique finger.This paper used a motion-tracking approach for the aye-aye’s middle finger using simultaneous video graphic capture.To mimic the motion,a two-link robot arm model is designed to reproduce the trajectory.Kinematics formulations were proposed to derive the motion of the middle finger using the Lagrangian method.In addition,a hardware model was developed to simulate the aye-aye’s finger motion.To validate the model,different motion states such as trajectory paths and joint angles,were compared.The simulation results indicate the kinematics of the model were consistent with the actual finger movement.This model is used to understand the aye-aye’s unique tap-scanning process for pioneering new tap-testing NDE strategies for various inspection applications.

Ultrasensitive graphene-Si position-sensitive detector for motion tracking

Motion tracking has attracted great attention in the fields of real-time tracking,nanorobotics,and targeted therapy.For achieving more accurate motion tracking,the highly sensitive position-sensitive detector(PSD)is desirable.Here,we demonstrate a meliorated PSD based on graphene-Si heterojunction for motion tracking.The position sensitivity of PSD was improved by employing surface engineering of graphene.Through modulating the transport property of graphene,nearly 20-fold increase of sensitivity was achieved under weak light,and at the same time,the detection limit power was reduced to^2 nW.A motion tracking system was developed based on the improved PSD,and human arm swing was tracked,which demonstrated high sensitivity and real-time tracking capabilities of the PSD.In addition,the PSD can support up to^10 kHz high-frequency tracking.This work provides a new strategy for improving the performance of PSD,and promotes the development of two-dimensional materials in novel optoelectronic devices.

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.

Stabilization and trajectory tracking of autonomous airship's planar motion

The stabilization and trajectory tracking problems of autonomous airship＇s planar motion are studied. By defining novel configuration error and velocity error, the dynamics of error systems are derived. By applying Lyapunov stability method, the state feedback control laws are designed and the close-loop error systems are proved to be uniformly asymptotically stable by Matrosov theorem. In particular, the controller does not need knowledge on system parameters in the case of set-point stabilization, which makes the controller robust with respect to parameter uncertainty. Numerical simulations illustrate the effectiveness of the controller designed.

Kinect-Based Motion Recognition Tracking Robotic Arm Platform

The development of artificial intelligence technology has promoted the rapid improvement of human-computer interaction. This system uses the Kinect visual image sensor to identify human bone data and complete the recognition of the operator’s movements. Through the filtering process of real-time data by the host computer platform with computer software as the core, the algorithm is programmed to realize the conversion from data to control signals. The system transmits the signal to the lower computer platform with Arduino as the core through the transmission mode of the serial communication, thereby completing the control of the steering gear. In order to verify the feasibility of the theory, the team built a 4-DOF robotic arm control system and completed software development. It can display other functions such as the current bone angle and motion status in real time on the computer operation interface. The experimental data shows that the Kinect-based motion recognition method can effectively complete the tracking of the expected motion and complete the grasping and transfer of the specified objects, which has extremely high operability.

A multiple template approach for robust tracking of fast motion target

Target tracking is very important in computer vision and related areas. It is usually difficult to accurately track fast motion target with appearance variations. Sometimes the tracking algorithms fail for heavy appearance variations. A multiple template method to track fast motion target with appearance changes is presented under the framework of appearance model with Kalman filter. Firstly, we construct a multiple template appearance model, which includes both the original template and templates affinely transformed from original one. Generally speaking, appearance variations of fast motion target can be covered by affine transformation. Therefore, the affine tr templates match the target of appearance variations better than conventional models. Secondly, we present an improved Kalman filter for approx- imate estimating the motion trail of the target and a modified similarity evaluation function for exact matching. The estimation approach can reduce time complexity of the algorithm and keep accuracy in the meantime. Thirdly, we propose an adaptive scheme for updating template set to alleviate the drift problem. The scheme considers the following differences： the weight differences in two successive frames; different types of affine transformation applied to templates. Finally, experiments demonstrate that the proposed algorithm is robust to appearance varia- tion of fast motion target and achieves real-time performance on middle/low-range computing platform.

Dynamic Motion Resistance for Tracked Vehicle

Based on previous achievements,a dynamic pressure-sinkage equation for saturated clay is established.First,aquasi-static penetration rate is selected,and the ratio of the dynamic penetration rate to the quasi-static rate is used to characterize the degree of dynamic effect,then theβth power of the ratio is used to quantify the dynamic effect of sinkage.The dynamic effect exponentβis obtained using penetration tests with different penetration rates.Then,a dynamic motion resistance equation for a tracked vehicle is established based on the dynamic pressure-sinkage equation.The equation incorporates both penetration and bulldozing resistance.Finally,a series of simulation experiments with varying travel speeds and slip rates is carried out.The results show that an increase in the speed leads to stronger terrain stiffness,resulting in a decrease in sinkage and motion resistance.However,the enhancement effect becomes weaker with an increase in the travel speed.

Identification of traffic object's motion behavior based on track

To extract the track parameters of a traffic object in traffic video and identify its motion behavior,a new method is proposed based on CamShift(Continuously Adaptive Mean Shift)and HMM(Hidden Markov Model).First,an object entering the video scene is located and tracked by the CamShift based algorithm,then its track parameters are obtained.Next,the track parameters are processed to form the observation sequence of HMM,and the motion behavior modeling and probability evaluation are implemented based on HMM.At last,the behavior identification and behavior statistics of the tracked traffic object in video are achieved.Experiments show that this method can be used to sort and recognize the motion behavior of the traffic object by its corresponding behavior track,and to do some statistics or corresponding process schemes.

Improved chirp scaling algorithm integrated motion compensation for parallel-track bistatic synthetic aperture radar

To compensate motion errors of images from the parallel-track bistatic synthetic aperture radar（BiSAR）,an improved chirp scaling algorithm（CSA） is proposed.Since velocity vector of the moving aircrafts in the parallel-track BiSAR system can not remain invariant in an aperture,an actual aperture is divided into subapertures so that it is reasonable to assume that the aircrafts move with constant acceleration vector in a subaperture.Based on this model,an improved CSA is derived.The new phase factors incorporate three-dimensional acceleration and velocity.The motion compensation procedure is integrated into the CSA without additional operation required.The simulation results show that the presented algorithm can efficiently resolve motion compensation for parallel-track BiSAR.

基于DCS-惯性权重组合的柔性机械臂运动轨迹控制系统研究

为了有效调控机械臂运动幅度,避免柔性机械臂实际运动轨迹与目标轨迹发生较大的偏差,设计一种基于分散控制系统(DCS)-惯性权重组合的柔性机械臂运动轨迹控制系统,它是一个集合了计算机、通信、显示和控制的计算机系统,该系统由过程控制和过程监控。通过DCS算法控制监测对象行为幅度并计算柔性机械臂惯性权重,利用DCS-惯性权重组合求解素数控制指标的具体数值,实现了对柔性机械臂运动轨迹控制系统的软件设计。实验结果表明,DCS-惯性权重组合算法作用下的机械臂末端坐标在横轴、纵轴、空间轴方向上的运动幅值均可以被控制在10个单位长度之内,并且在0.52 s内进入机械臂运动轨迹最佳控制状态,运动轨迹差值最大仅为0.01 rad,验证了该系统具备可行性和有效性。

高速履带车辆横摆运动响应特性分析与试验验证

为研究高速履带车辆操纵特性,奠定高速电驱动履带车辆的操纵稳定性评价及控制的基础,建立了高速履带车辆非线性转向动力学模型及2自由度线性转向动力学模型,并对模型进行试验验证。利用2自由度线性模型推导了高速履带车辆横摆运动传递函数,基于此进行了高速履带车辆横摆运动时域和频域响应特性分析,提出履带车辆稳态横摆角速度增益及临界阻尼车速的定义。研究结果表明:履带车辆稳态横摆角速度增益均小于1,履带车辆具有不足转向特性;履带车辆系统阻尼比在1左右;当车速小于临界阻尼车速时,车辆系统为过阻尼系统,横摆角速度响应的上升时间在0.2 s内;当车速等于临界阻尼车速时,车辆系统为临界阻尼系统,横摆角速度响应的上升时间大于10 s;当车速大于临界阻尼车速时,车辆系统为欠阻尼系统,横摆角速度响应的上升时间迅速减小至2~3 s。

难加工材料纵扭超声振动辅助铣削加工研究进展

纵扭复合超声振动辅助铣削(LTUVAM)是在刀具轴向与扭转方向上施加高频微幅振动的一种辅助铣削技术,具有降低切削力与切削热、提高工件表面质量、提高表面残余压应力、减少刀具磨损等诸多优点。本文围绕难加工材料的铣削加工进行了系统综述。在设备制造方面,阐述了纵扭复合超声振动系统的结构设计方法与工作原理;在工艺开发方面,从LTUVAM的切削刃运动轨迹及切削特性入手,分析各类材料的切削加工性能,并总结了LTUVAM的优势及应用。最后,本文对LTUVAM的未来发展趋势进行展望。

基于遥感GIS信息融合的测绘机器人滑模跟踪控制系统

测绘机器人是实现测绘自动化的执行设备,测绘机器人的工作空间更为复杂,给机器人的跟踪控制工作带来较大挑战;为提高测绘机器人跟踪控制效果,设计了基于遥感GIS信息融合的测绘机器人滑模跟踪控制系统;加设遥感信息采集器和GIS信息采集器,改装遥感GIS信息处理器以及滑模跟踪控制器,完成硬件系统的优化设计;考虑信息结构以及信息之间的逻辑关系,构建系统数据库,为遥感GIS信息提供充足的存储空间;根据测绘任务生成机器人滑模移动轨迹,作为机器人的控制目标;采集测绘机器人实时遥感与GIS信息,利用遥感GIS信息融合技术跟踪机器人实时位姿,比对位姿跟踪结果与生成的控制目标,计算滑模跟踪控制量,完成系统的测绘机器人滑模跟踪控制软件功能优化;系统测试结果表明:设计系统的控制误差平均值为1.9 m,抖振幅值为0.8 dB,具有较好的控制效果。

基于机械臂运动轨迹控制双生成对抗网络的设计

为了提高机械臂的运动准确性,以改善机械臂的工作效率,设计了一种用于机械臂运动轨迹控制的双生成对抗网络。首先,对机械臂的结构进行了分析,根据机械臂的结构特点建立了机械臂的坐标系,在该坐标系上,通过机械臂各关节点的变换矩阵,求取了机械臂的运动学方程;然后,将机械臂末端执行器的位置向量、关节速度等信息与编码器相结合,以获取双向生成性对抗网络,并在双向生成性对抗网络的基础上,设计了双生成对抗网络,以对机械臂的运动轨迹进行控制;最后,利用所提方法与干扰观测器方法对机械臂的运动轨迹进行控制测试。测试结果显示,所提方法的控制准确度比干扰观测器方法的控制准确度提高了40.13%,而且所提方法控制机械臂运动过程中,出现的波动也比干扰观测器方法的控制过程要小。说明所提方法不仅能较为准确地控制机械臂运动,而且控制过程较为平稳,有助于提高机械臂的工作效率。

基于视频的振动测量技术研究进展

振动测量是保障结构安全和良好状态的基本手段。高精度的振动测量可为结构设计、安装调试、健康管理等振动试验提供精确的输入与响应测试。相较于传统的振动测量手段,基于视频的振动测量技术将相机的全部像素转化为高精度振动传感器,利用视频图像方式让人们肉眼可视结构在物理世界的真实振动形态,具有非接触、全视场、高空间分辨率、灵活方便等优点,近年来受到业界的广泛关注。该文主要介绍了视频振动测量技术的系统构成与测量过程、当前主要方法和相关技术最新进展,并总结了视频振动测量技术与其他技术相比存在的优势。通过分析与对比,肯定了视频方法是解决振动测量问题的有效手段和对传统测量方法的有力补充,随着相关技术和硬件设备的发展,视频振动测量方法将具有越来越大的研究意义和应用价值。

基于人工鱼群算法的篮球跳投轨迹实时跟踪

篮球运动轨迹跟踪方法由于轨迹特征提取效果差,导致跟踪误差高,提出一种基于人工鱼群算法的篮球跳投轨迹实时跟踪方法。提取三维坐标系下图像中篮球边缘轮廓信息,通过滤波函数消除篮球跳投图像噪声,基于人工鱼群算法提取图像中篮球跳投轨迹特征,寻找篮球运动轨迹的最优解集,改进篮球实时跟踪匹配路径,形成轨迹跟踪函数。实验结果可知,该方法的平均轨迹跟踪误差为18.28mm,与常规方法相比降低了6.22mm以上。因此,该跟踪方法的篮球轨迹跟踪精度更高,并且实时跟踪轨迹与真实轨迹更吻合。