A Probabilistic Method for Motion Analysis of Caisson Breakwaters

It is assumed that, during the design period, the waves acting on breakwaters are divided into three types： standing wave, broken wave and breaking wave,and the wave heights fit the Rayleigh distribution while the water depths, wave periods and duration of breaking wave impact force fit normal distribution. Based on the random samples of water depths, wave heights, wave periods and duration of breaking wave impact force, the types of waves acting on breakwaters are distinguished and the time-history model of the wave force is determined. The motions of caisson breakwaters under the wave force are simulated by a dynamic numerical model and the statistic characteristics of the dynamic responses are analyzed with the Monte Carlo method. A probabilistic procedure to analyze the motion of the breakwater is developed therein. The procedure is illustrated by an example.

MECHANISM DESIGN AND MOTION ANALYSIS OF A SPHERICAL MOBILE ROBOT

A new spherical mobile robot BHQ-1 is designed. The spherical robot is driven by two internally mounted motors that induce the ball to move straight and turn around on a fiat surface. A dynamic model of the robot is developed with Lagrange method and factors affecting the driving torque of two motors are analyzed. The relationship between the turning radius of the robot and the length of two links is discussed in order to optimize its mechanism design. Simulation and experimental results demonstrate the good controllability and motion performance of BHQ-1.

Motion Analysis of an Electric Vehicle with Two Independent Drive Motors

Motion analyses are performed with the help of stability and simulation analysis, which can provide theoretical bases for applications of an electric vehicle with two independent drive motors. Compared with one-motor drive electric vehicle, the two-motor drive electric vehicle has the advantage of easy layout, simple power train and good drivability and handling characteristics. Analysis shows the method connecting armatures of two DC motors in parallel can function as mechanical differential without a steering sensor, which can simplify structure and increase reliability of the controller. Computer simulations and experiment are carried out to verify conclusions.

Ultrasonographic visualization of lower eyelid structures and dynamic motion analysis

AIMTo define the ultrasonographic structure of normal lower eyelid anatomic compartments and their spacial relationship in dynamic motion.

Methods for bearings-only underwater target motion analysis

The problem of estimation of underwater target motion parameters via bearings only is the most of ten encountered and most difficult to solve in the underwater target motion analysis.As the bearings-only target motion analysis is a nonlinear and multiextremal global optimization problem, so most classical estimation methods often lead the solution to convergence to one of the local extremes other than the global extreme, especially, when the noise of target bearing observation is added. In this paper we propose to use the Generalized Least Square method on the rough estimation of target motion parameters, and then use the Sequential Uniform Design method to gain a more precise estimation on the bases of rough estimation.The latter ensures that the result convergences to the global extreme. The algorithm based on the above two methods is profitable for the bearings-only target motion analysis even under conditions of large bearing observation error.

Passive bearings-only target motion analysis based on association of multiple arrays

The method for Bearings-Only Target Motion Analysis (BO-TMA) based on bearing measurements fusion of two arrays is studied. The algorithms of pseudolinear processing, extended Kalman filter and maximum likelihood estimation are presented. The results of simulation experiments show that the BO-TMA method based on association of multiple arrays not only makes contributions towards eliminating maneuvers needed by bearings-only TMA based on single array,but also improves the stabilization and global convergence for varied estimation algorithms.

“动作捕捉”的王者——记美国魔神Motion Analysis公司

在美国洛杉矶刚刚结束的2017 SIGGRAPH展会上,由美国魔神公司(Motion Analysis Corp.)与中国台湾的OXON公司联手展示的VR动感体验引起轰动。展览期间,每天都有人在公司的展位边排队等候体验令人难忘的虚拟现实技术。美国魔神公司(以下简称“魔神公司”)

Motion information analysis system based on acceleration signals

A motion information analysis system based on the acceleration data is proposed in this paper,consisting of filtering,feature extraction and classification.The Kalman filter is adopted to eliminate the noise.With the time-domain and frequency-domain analysis,acceleration features like the amplitude,the period and the acceleration region values are obtained.Furthermore,the accuracy of the motion classification is improved by using the k-nearest neighbor （KNN） algorithm.

MOTION ANALYSIS游戏互动工作室

简介美国魔神公司的数字动作捕捉及分析系统,是一款可以实现室外日光直射条件下使用的动作捕捉系统,也是一款可以实现5000个标志点捕捉的数字动作捕捉系统。动作捕捉及分析系统由数字捕捉镜头,EagleHub和Cortex软件组成,可极其精确地捕捉复杂动作。实时功能使用户可以在同一时间观察到目标某个细微动作,也可以与魔神公司的其他镜头自由组合,从而优化工作室的效能。魔神公司是动作捕捉行业领导者,为全球近千用户提供卓越性能的光学动作捕捉及分析系统,遍及动画制作、运动分析、工业测量与控制等各个领域。具有代表性的电影、电视作品有《指环王》《猿人星球》《金刚》《天空上尉和明日世界》《最终幻想》等。

Gait Analysis of a Subject with Tarsometatarsal Prosthesis

Introduction: Gait analysis of an adult man after trans-metatarsal unilateral amputation is described. Objective: Instrumental gait analysis of a subject 15 years after trans-metatarsal unilateral amputation in two footwear conditions: while walking barefoot and with prosthesis. Materials and Methods: In a movement analysis laboratory, locomotion studies were carried out at freely chosen walking speed by a 65-year-old subject, obtaining kinematic, kinetic and surface electromyographic data in time and space. Gait analysis was performed using instrumental technologies from a digital eco-system applying walking protocols. Results: When the patient wore the prosthesis, several positive improvements were observed in various aspects of gait. These included enhancements in the base of support, gait speed, and joint range of movements. Additionally, there was a slight improvement in the vertical ground reaction forces pattern, indicating a positive effect of the assistive technology. Furthermore, the use of the prosthesis led to a more organized pattern of muscle activity, which further supports its beneficial impact. However, it is worth noting that some challenges still persisted, particularly regarding stabilizing the body during the double support phase. Despite this difficulty, the overall findings suggest that the use of the prosthesis offers valuable improvements to the patient’s gait dynamics. Conclusions: After conducting a thorough analysis of the parameters related to the gait of a subject who underwent a trans-metatarsal unilateral amputation fifteen years ago, it was found that the use of prosthesis had a positive impact. This study demonstrated important improvements in some kinematic and kinetic parameters, including muscle activation patterns, indicating an increase in comfort and confidence while utilizing the prosthetic device.

Online Observability-Constrained Motion Suggestion via Efficient Motion Primitive-Based Observability Analysis

An active perception methodology is proposed to locally predict the observability condition in a reasonable horizon and suggest an observability-constrained motion direction for the next step to ensure an accurate and consistent state estimation performance of vision-based navigation systems. The methodology leverages an efficient EOG-based observability analysis and a motion primitive-based path sampling technique to realize the local observability prediction with a real-time performance. The observability conditions of potential motion trajectories are evaluated,and an informed motion direction is selected to ensure the observability efficiency for the state estimation system. The proposed approach is specialized to a representative optimizationbased monocular vision-based state estimation formulation and demonstrated through simulation and experiments to evaluate the ability of estimation degradation prediction and efficacy of motion direction suggestion.

Nonlinear dynamic modeling of planar moving Timoshenko beam considering non-rigid non-elastic axial effects

Due to the importance of vibration effects on the functional accuracy of mechanical systems,this research aims to develop a precise model of a nonlinearly vibrating single-link mobile flexible manipulator.The manipulator consists of an elastic arm,a rotary motor,and a rigid carrier,and undergoes general in-plane rigid body motion along with elastic transverse deformation.To accurately model the elastic behavior,Timoshenko’s beam theory is used to describe the flexible arm,which accounts for rotary inertia and shear deformation effects.By applying Newton’s second law,the nonlinear governing equations of motion for the manipulator are derived as a coupled system of ordinary differential equations(ODEs)and partial differential equations(PDEs).Then,the assumed mode method(AMM)is used to solve this nonlinear system of governing equations with appropriate shape functions.The assumed modes can be obtained after solving the characteristic equation of a Timoshenko beam with clamped boundary conditions at one end and an attached mass/inertia at the other.In addition,the effect of the transverse vibration of the inextensible arm on its axial behavior is investigated.Despite the axial rigidity,the effect makes the rigid body dynamics invalid for the axial behavior of the arm.Finally,numerical simulations are conducted to evaluate the performance of the developed model,and the results are compared with those obtained by the finite element approach.The comparison confirms the validity of the proposed dynamic model for the system.According to the mentioned features,this model can be reliable for investigating the system’s vibrational behavior and implementing vibration control algorithms.

A deep Koopman operator-based modelling approach for long-term prediction of dynamics with pixel-level measurements

Although previous studies have made some clear leap in learning latent dynamics from high-dimensional representations,the performances in terms of accuracy and inference time of long-term model prediction still need to be improved.In this study,a deep convolutional network based on the Koopman operator(CKNet)is proposed to model non-linear systems with pixel-level measurements for long-term prediction.CKNet adopts an autoencoder network architecture,consisting of an encoder to generate latent states and a linear dynamical model(i.e.,the Koopman operator)which evolves in the latent state space spanned by the encoder.The decoder is used to recover images from latent states.According to a multi-step ahead prediction loss function,the system matrices for approximating the Koopman operator are trained synchronously with the autoencoder in a mini-batch manner.In this manner,gradients can be synchronously transmitted to both the system matrices and the autoencoder to help the encoder self-adaptively tune the latent state space in the training process,and the resulting model is time-invariant in the latent space.Therefore,the proposed CKNet has the advantages of less inference time and high accuracy for long-term prediction.Experiments are per-formed on OpenAI Gym and Mujoco environments,including two and four non-linear forced dynamical systems with continuous action spaces.The experimental results show that CKNet has strong long-term prediction capabilities with sufficient precision.

Segmental Kinematic Coupling of the Human Spinal Column during Locomotion

As one of the most important daily motor activities, human locomotion has been investigated intensively in recent decades. The locomotor functions and mechanics of human lower limbs have become relatively well understood. However, so far our understanding of the motions and functional contributions of the human spine during locomotion is still very poor and simultaneous in-vivo limb and spinal column motion data are scarce. The objective of this study is to investigate the delicate in-vivo kinematic coupling between different functional regions of the human spinal column during locomotion as a stepping stone to explore the locomotor function of the human spine complex. A novel infrared reflective marker cluster system was constrncted using stereophotogrammetry techniques to record the 3D in-vivo geometric shape of the spinal column and the segmental position and orientation of each functional spinal region simultaneously. Gait measurements of normal walking were conducted. The preliminary results show that the spinal column shape changes periodically in the frontal plane during locomotion. The segmental motions of different spinal functional regions appear to be strongly coupled, indicating some synergistic strategy may be employed by the human spinal column to facilitate locomotion. In contrast to traditional medical imaging-based methods, the proposed technique can be used to investigate the dynamic characteristics of the spinal column, hence providing more insight into the functional biomechanics of the human spine.

Video Analysis Based on Volumetric Event Detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television （CCTV） data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today＇s approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called ＂pre-suspicion＂ mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.

Key Pose Frame Extraction Method of Human Motion Based on 3D Framework and X-Means

The key pose frames of a human motion pose sequence,play an important role in the compression,retrieval and semantic analysis of continuous human motion.The current available clustering methods in literatures are difficult to determine the number of key pose frames automatically,and may destroy the postures’ temporal relationships while extracting key frames.To deal with this problem,this paper proposes a new key pose frames extraction method on the basis of 3D space distances of joint points and the improved X-means clustering algorithm.According to the proposed extraction method,the final key pose frame sequence could be obtained by describing the posture of human body with space distance of particular joint points and then the time-constraint X-mean algorithm is applied to cluster and filtrate the posture sequence.The experimental results show that the proposed method can automatically determine the number of key frames and save the temporal characteristics of motion frames according to the motion pose sequence.

Gait Analysis of a Subject with Total Hip Arthroplasty

Introduction: gait analysis of a subject with total hip replacement is described. Objective: instrumental gait analysis of a subject 12 years after the total hip arthroplasty. Materials and Methods: in a movement analysis laboratory, locomotion studies were carried out at freely chosen walking speed by a 64-year-old subject, obtaining kinematic, kinetic and surface electromyographic data in time and space. All measurements were assessments by applying walking protocols on a straight surface of 8 m long. Results: abnormal slight activations of semitendinosus and tibialis anterior muscles, of the left limb, were observed throughout the gait cycle, no spatiotemporal parameters far from normal values were detected. Conclusions: it was possible to obtain an exhaustive analysis of the parameters associated with the gait of a subject after 12 years of total hip arthroplasty.

Motion Error Compensation of Multi-legged Walking Robots

Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.

Rotational Swashplate Pulse Continuously Variable Transmission Based on Helical Gear Axial Meshing Transmission

The current research on pulse continuously variable transmission（CVT） is mainly focused on reducing the pulse degree and making pulse degrees a constant value. Current research mainly confined to find out new design parameters by using the method of optimization, and reduce the pulse degree of pulse CVT and its range of variation. But the fact is that the reduction of the pulse degree is not significant. This article presents a new structure of mechanical pulse CVT--the rotational swashplate pulse CVT with driven by helical gear axial meshing. This transmission is simple and compact in structure and low in pulsatile rate （it adopts 6 guide rods）, and the pulsatile degree is irrelevant to the transmission ratio. Theoretically, pulsatile rate could be reduced to zero if appropriate curved surface of the swashplate is used. Compared with the connecting rod pulse CVT, the present struc^tre uses helical gear mechanism as transmission part and it avoids unbalanced inertial force in the former model. This paper analyzes the principle of driving of this transmission, presents its mechanical structure, and discusses its motion characteristics. Experimental prototype of this type of CVT has been manufactured. Tests for the transmission efficiency（when the rotational speed of the output shaft is the maximum） and the angular velocity of the output shaft have been carried out, and data have been analyzed. The experimental results show that the speed of the output shaft for the experimental prototype is slightly lower than the theoretical value, and the transmission efficiency of the experimental prototype is about 70%. The pulse degree of the CVT discussed in this paper is less than the existing pulse CVT of other types, and it is irrelevant to the transmission ratio of the CVT. The research provides the new idea to the CVT study.

Development of a Wearable Upper Limb Rehabilitation Robot Based on Reinforced Soft Pneumatic Actuators

Dyskinesia of the upper limbs caused by stroke,sports injury,or trafc accidents limits the ability to perform the activities of daily living.Besides the necessary medical treatment,correct and scientifc rehabilitation training for the injured joint is an important auxiliary means during the treatment of the efected upper limb.Conventional upperlimb rehabilitation robots have some disadvantages,such as a complex structure,poor compliance,high cost,and poor portability.In this study,a novel soft wearable upper limb rehabilitation robot(SWULRR)with reinforced soft pneumatic actuators(RSPAs)that can withstand high pressure and featuring excellent loading characteristics was developed.Driven by RSPAs,this portable SWULRR can perform rehabilitation training of the wrist and elbow joints.In this study,the kinematics of an SWULRR were analyzed,and the force and motion characteristics of RSPA were studied experimentally.The results provide a reference for the development and application of wearable upper limb rehabilitation robots.An experimental study on the rotation angle of the wrist and the pressure of the RSPA was conducted to test the efect of the rehabilitation training and verify the rationality of the theoretical model.The process of wrist rehabilitation training was tested and evaluated,indicating that SWULRR with RSPAs will enhance the fexibility,comfort,and safety of rehabilitation training.This work is expected to promote the development of wearable upper-limb rehabilitation robots based on modular reinforced soft pneumatic actuators.