Multiparameter Numerical Investigation of Two Types of Moving Interactions Between the Deep-Sea Mining Vehicle Track Plate and Seabed Soil:Digging and Rotating Motions

To ensure the safe performance of deep-sea mining vehicles(DSMVs),it is necessary to study the mechanical characteristics of the interaction between the seabed soil and the track plate.The rotation and digging motions of the track plate are important links in the contact between the driving mechanism of the DSMV and seabed soil.In this study,a numerical simulation is conducted using the coupled Eulerian–Lagrangian(CEL)large deformation numerical method to investigate the interaction between the track plate of the DSMV and the seabed soil under two working conditions:rotating condition and digging condition.First,a soil numerical model is established based on the elastoplastic mechanical characterization using the basic physical and mechanical properties of the seabed soil obtained by in situ sampling.Subsequently,the soil disturbance mechanism and the dynamic mechanical response of the track plate under rotating and digging conditions are obtained through the analysis of the sensitivity of the motion parameters,the grouser structure,the layered soil features and the soil heterogeneity.The results indicate that the above parameters remarkably influence the interaction between the DSMV and the seabed soil.Therefore,it is important to consider the rotating and digging motion of the DSMV in practical engineering to develop a detailed optimization design of the track plate.

DPT‐tracker:Dual pooling transformer for efficient visual tracking

Transformer tracking always takes paired template and search images as encoder input and conduct feature extraction and target‐search feature correlation by self and/or cross attention operations,thus the model complexity will grow quadratically with the number of input images.To alleviate the burden of this tracking paradigm and facilitate practical deployment of Transformer‐based trackers,we propose a dual pooling transformer tracking framework,dubbed as DPT,which consists of three components:a simple yet efficient spatiotemporal attention model(SAM),a mutual correlation pooling Trans-former(MCPT)and a multiscale aggregation pooling Transformer(MAPT).SAM is designed to gracefully aggregates temporal dynamics and spatial appearance information of multi‐frame templates along space‐time dimensions.MCPT aims to capture multi‐scale pooled and correlated contextual features,which is followed by MAPT that aggregates multi‐scale features into a unified feature representation for tracking prediction.DPT tracker achieves AUC score of 69.5 on LaSOT and precision score of 82.8 on Track-ingNet while maintaining a shorter sequence length of attention tokens,fewer parameters and FLOPs compared to existing state‐of‐the‐art(SOTA)Transformer tracking methods.Extensive experiments demonstrate that DPT tracker yields a strong real‐time tracking baseline with a good trade‐off between tracking performance and inference efficiency.

基于DF-Track的水下鱼体跟踪方法

鱼类跟踪是分析鱼类行为、评估其健康水平的关键步骤。然而,由于真实水下养殖鱼群具有运动非线性、高外观相似度、鱼体互相遮挡、特征信息损失严重等特点,多目标跟踪鱼类是一项非常具有挑战性的任务。针对水下鱼体反射产生的伪影以及鱼体运动非线性、相互遮挡导致跟踪轨迹碎片化的问题,提出一种水下多鱼跟踪模型DF-Track。该模型采用基于检测的跟踪(TBD)范式,首先在YOLOv8的C2f结构中引入聚合感知注意力机制(APFA),提高在前向过程中提取图像特征的能力;然后使用SDI多层次特征融合模块对YOLOv8中的feature fusion部分进行重设计,减少特征融合阶段不同层级特征信息的冲突问题;最后提出一种优化轨迹管理的跟踪模型DF-Track,并引入Focal-EIoU补偿匹配空间中的运动估计偏差,平衡几何一致性。实验结果表明:与原YOLOv8相比,所提算法的精确率提高了1.7%,平均精度均值提高了2.1%;DF-Track与其他MOT跟踪算法相比,HOTA达到70.9%,MOTA达到91.9%,IDF1达到80.4%。证明DF-Track模型在水下鱼类跟踪任务中具有较好的性能。

MOVING OBJECT TRACKING IN DYNAMIC IMAGE SEQUENCE BASED ON ESTIMATION OF MOTION VECTORS OF FEATURE POINTS

An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.

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.

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.

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.

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.

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.

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.

OPTICALLY TRACKING THE MOTION OF MICROBEADS TO STUDY PHYSICAL BEHAVIORS OF THE LIVING CELL IN RESPONSE TO TRANSIENT STRETCH OR COMPRESSION

Optical magnetic twisting cytometry and traction force microscopy are two advanced cell mechanics research tools that employ optical methods to track the motion of microbeads that are either bound to the surface or embedded in the substrate underneath the cell.The former measures rheological properties of the cell such as cell stiffness,and the latter measures cell traction force dynamics.Here we describe the principles of these two cell mechanics research tools and an example of using them to study physical behaviors of the living cell in response to transient stretch or compression.We demonstrate that,when subjected to a stretch
unstretch manipulation,both the stiffness and traction force of adherent cells promptly reduced,and then gradually recover up to the level prior to the stretch.Immunofluorescent staining and Western blotting results indicate that the actin cytoskeleton of the cells underwent a corresponding disruption and reassembly process almost in step with the changes of cell mechanics.Interestingly,when subjected to compression,the cells did not show such particular behaviors.Taken together,we conclude that adherent cells are very sensitive to the transient stretch but not transient compression,and the stretch-induced cell response is due to the dynamics of actin polymerization.

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 yam 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.

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.

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.

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。

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。

用于多目标跟踪的高斯混合轨迹预测模型

针对视频中目标之间的遮挡会增加轨迹关联难度的问题,提出了一种高斯混合轨迹预测模型来改善遮挡情况下的关联效果.该模型采用Transformer结构,从对象的历史运动信息中提取更长的时间依赖性,以便更准确地预测跟踪对象在未来的轨迹分布;同时,将模型的输出设置为高斯混合分布,采用多个高斯分布相加来定义跟踪对象在未来的轨迹分布,以利用轨迹分布来计算检测目标和跟踪对象之间的空间相似性.实验结果表明:该模型能够改善跟踪性能,在MOT17数据集上HOTA达到了56.3%.

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。

基于三维激光点云的序列运动图像点目标快速跟踪方法

由于现有方法未充分考虑小目标和遮挡目标检测的问题,导致目标跟踪效果不佳,由此针对点目标跟踪较为困难的问题,提出基于三维激光点云的序列运动图像点目标快速跟踪方法。首先下采样序列运动图像三维激光点云并去除其中的地面数据,通过动态阈值改进欧式聚类方法,分割图像为目标和背景,然后改进SECOND算法,在目标检测阶段融入自适应空间特征融合模块和二维卷积神经网络,同时采用3D DIoU替代Smooth L1作为损失函数,提升SECOND算法的目标检测性能,最后在激光雷达坐标系中构建各点目标的三维中心,利用3D卡尔曼滤波器连续跟踪目标,以交并比和欧式距离为度量标准,通过贪婪算法匹配最近邻目标,实现序列运动图像点目标快速跟踪。实验结果表明,所提方法IoU值更高,可达到0.971,且对目标的跟踪更理想。