Predictive dynamics: an optimization-based novel approach for human motion simulation

Predictive dynamics is a novel approach for simulating human motion. It avoids direct integration of differential-algebraic equations in order to create the resulting simulations for redundant digital human models. Instead, it formulates an optimization problem by defining appropriate performance measures and constraints to recover the real motion of the dynamic system. In the formulation, both kinematics and kinetics parameters serve as unknowns, and equations of motion are treated as equality constraints. Procedures to choose physical performance measures and appropriate constraints based on the available information about the bio-system are presented. The proposed methodology is illustrated and studied by first predicting the swinging motion of a single pendulum with externally applied torque. The pendulum can represent the motion of upper and lower extremities. This simple problem has analytical solutions and is used to gain insights for the predictive dynamics approach. In addition, a complex human walking task is simulated by using the approach, and realistic results are obtained. Such motion prediction capabilities have a wide variety of applications for industries ranging from automotive to military to clinical analysis and design.     

基于运动捕获文件的人体微多普勒信号仿真

针对传统人体微多普勒信号仿真算法适应模型简单、与人体相似度不高的问题,提出了一种基于运动捕获文件的仿真方法。该方法从运动捕获文件中获得各关节点的位置随时间的变化,根据关节点的相对位置建立由12个椭球体组成的人体三维模型,并根据此模型仿真RCS回波。此方法所建模型与实际人体外形相似度高,可对任意运动模式的人体雷达回波进行仿真。仿真结果验证了所提算法的正确性。     

Hybrid force and motion control of flexible joint parallel manipulators using inverse dynamics approach

An inverse dynamics control algorithm is developed for hybrid motion and contact force trajectory tracking control of flexible joint parallel manipulators. First, an open-tree structure is considered by the disconnection of adequate number of unactuated joints. The loop closure constraint equations are then included. Elimination of the joint reaction forces and the other intermediate variables yield a fourth-order relation between the actuator torques and the end-effector position and contact force variables, showing that the control torques do not have an instantaneous effect on the end-effector contact forces and accelerations because of the flexibility. The proposed control law provides simultaneous and asymptotically stable control of the end-effector contact forces and the motion along the constraint surfaces by utilizing the feedback of positions and velocities of the actuated joints and rotors. A two degree of freedom planar parallel manipulator is considered as an example to illustrate the effectiveness of the method.     

LCD models to analyze and simulate motion artifacts

Abstract— In this paper, two models to evaluate the temporal behavior of liquid‐crystal displays are described: a model assuming a linear display behavior and a model that incorporates non‐linear effects. For the linear temporal model, it can be predicted that the response time starts to contribute to motion blur when it is longer than one‐sixth of the hold time and becomes dominant when it is longer than eight times the hold time. The non‐linear model can be used to visualize the appearance of effects that cannot be determined via linear system theory. Also, some means to reduce display artifacts are described and its impact is illustrated. Although the main focus in this article is on the temporal behavior of liquid‐crystal displays, the spatial properties defined by the pixel structure can be simulated as well. A formula for the spatio‐temporal display behavior is given, which can be evaluated numerically to simulate the perceived image for arbitrary image‐sequence input material.     

Cofields: a physically inspired approach to motion coordination

As computing becomes increasingly pervasive, autonomous computers are going to be embedded in everyday objects in our physical environment. In such scenarios, mobility itself will be pervasive. Mobile users, mobile devices, computer-enabled vehicles, and mobile software components will define a dynamic, networked world in which a large set of autonomous components will interact with each other to orchestrate their activities. We focus on the problem of coordinating autonomous agent's movements in a distributed environment. Orchestrating mobile autonomous agents can take inspiration from the laws of physics. Agent's movements could be driven by locally perceived computational force fields, or cofields, generated by the agents themselves and propagated through an embedded infrastructure.     

Impulse-based substructuring in a floating frame to simulate high frequency dynamics in flexible multibody dynamics

An original approach for flexible multibody dynamics is proposed, which combines the free–free formulation of elastic body deformation with an impulse-based representation of linear vibration. The resulting system of equations being remarkably simple, this impulse-based substructuring method is straightforward to implement. Simple applications of a flexible rotating beam submitted to various excitation inputs have been selected and developed so as to assess the accuracy of the proposed methodology.     

A new approach to code motion and its application to hoisting

An approach to code motion and hoisting, a program optimization technique, is discussed. The safety and profitability of optimization in general and hoisting in particular are analyzed. By restricting the analysis to a spanning tree imposed on the program graph, a linear algorithm is developed that provides sufficient but not necessary conditions for hoisting.     

Hybrid learning-based neuro-fuzzy inference system: a new approach for system modeling

In this article, a hybrid learning neuro-fuzzy inference system (HLNFIS) with a new inference mechanism is proposed for system modeling. In the HLNFIS, the incoming signal is fuzzified by the proposed improved Gaussian membership function (IGMF), which is derived from two standard Gaussian functions. With the premise construction with IGMFs, the system inference ability can be upgraded. The fuzzy inference processor, which involves both numerical and linguistic reasoning, is introduced in rule base construction. For effective parameter learning, the hybrid algorithm of random optimization (RO) and least square estimation (LSE) is exploited, where the premise and the consequence parameters of are updated by RO and LSE, respectively. To validate the feasibility and the potential of the proposed approach, three examples of system modeling are conducted. Through experimental results and comparisons the proposed HLNFIS shows excellent performance for complex modeling.     

Using computer vision to simulate the motion of virtual agents

In this paper, we propose a new model to simulate the movement of virtual humans based on trajectories captured automatically from filmed video sequences. These trajectories are grouped into similar classes using an unsupervised clustering algorithm, and an extrapolated velocity field is generated for each class. A physically‐based simulator is then used to animate virtual humans, aiming to reproduce the trajectories fed to the algorithm and at the same time avoiding collisions with other agents. The proposed approach provides an automatic way to reproduce the motion of real people in a virtual environment, allowing the user to change the number of simulated agents while keeping the same goals observed in the filmed video. Copyright © 2007 John Wiley & Sons, Ltd.     

Hybrid motion/force control: a review

Abstract

This paper reviews hybrid motion/force control, a control scheme which enables robots to perform tasks involving both motion, in the free space, and interactive force, at the contacts. Motivated by the large amount of literature on this topic, we facilitate comparison and elucidate the key differences among different approaches. An emphasis is placed on the study of the decoupling of motion control and force control. And we conclude that it is indeed possible to achieve a complete decoupling; however, this feature can be relaxed or sacrificed to reduce the robot’s joint torques while still completing the task.     

A new predictive motion control of a planar vehicle under uncertainty via convex optimization

This paper proposes an optimization-based planning framework for target tracking of a planar vehicle in the presence of some moving obstacles and uncertainty resources. The framework is modeled based on Linear-Time Varying Model Predictive Control (LTV-MPC). Moreover, a successive linearization approach is presented to formulate the obstacle avoidance mission as a set of linear constraints. Finally this LTV-MPC problem is translated to a close-form convex optimization problem by applying some mathematical and algebraic simplifications. Simulation results show beneficially of the proposed path planning method to navigate an autonomous vehicle successfully regardless of different uncertainty resources.     

Integrating preventive and predictive maintenance policies with system dynamics: A decision table approach

A decision table is a practical tool that helps systems planners to make operational decisions, especially when they are under stress. With the effect of recent trends, such as the use of machine learning, data mining, and reinforcement learning methods, the maintenance decision has been a dynamic issue depending on system conditions. An expert may execute the maintenance or wait for the next periodic maintenance due to lack of maintenance workers, tools or budget, resources, etc., although the intelligent method predicts a failure approaching. Even sometimes, he/she may ignore the current periodic maintenance. Our method allows making some changes in the maintenance plan systematically. It integrates the results of preventive and predictive maintenance policies, and as different from the literature, it allows ignoring some maintenance actions depending on the maintenance resource levels in a decision table. Such a strategy helps to allocate limited resources to maintenance actions reasonably. We conducted an extensive simulation study on a real-life dataset. The preventive maintenance period is determined using classical approaches such as Weibull analysis. A machine learning algorithm is utilized to predict the type of failure. We have analyzed the performance of the proposed decision table approach under a variety of scenarios and with different parameter settings. We also showed the effect of parameter settings and the marginal utility of each maintenance policy. In addition, the approach provides several choices for planners. As a result, the proposed approach improves the system’s sustainability compared to traditional policies.     

An engineering approach to human resources performance evaluation: Hybrid MCDM application with interactions

Human performance evaluation is one of the most important fields to analyze for the continuity of an organization. Evaluation files filled by the managers generally end up in dusty folders where no one looks. This decreases the credibility of the evaluators and the process itself. Whereas the management thinks that they are taking the valuable time from the people who can do better things instead of these evaluations. In this paper, we add an engineering point of view to this process by giving a Hybrid Multicriteria Decision Making (MCDM) approach to evaluate employees’ performances working for a same task and explain an efficient way of handling the qualitative and quantitative data simultaneously. The real life situations where performance criteria show interaction will be possible to solve and the different types of interactions will be handled with the proposed hybrid method using Analytical Network Process (ANP) and Choquet Integral (CI) simultaneously. We also give a numerical illustration at the end of the study with the appropriate concluding remarks including the advantages of the proposed method.     

A statistical approach to predictive detection

Service providers typically define quality of service problems using threshold tests, such as “Are HTTP operations greater than 12 per second on server XYZ?” Herein, we estimate the probability of threshold violations for specific times in the future. We model the threshold metric (e.g., HTTP operations per second) at two levels: (1) non-stationary behavior (as is done in workload forecasting for capacity planning) and (2) stationary, time-serial dependencies. Our approach is assessed using simulation experiments and measurements of a production Web server. For both assessments, the probabilities of threshold violations produced by our approach lie well within two standard deviations of the measured fraction of threshold violations.     

Subspace clustering of high-dimensional data: a predictive approach

In several application domains, high-dimensional observations are collected and then analysed in search for naturally occurring data clusters which might provide further insights about the nature of the problem. In this paper we describe a new approach for partitioning such high-dimensional data. Our assumption is that, within each cluster, the data can be approximated well by a linear subspace estimated by means of a principal component analysis (PCA). The proposed algorithm, Predictive Subspace Clustering (PSC) partitions the data into clusters while simultaneously estimating cluster-wise PCA parameters. The algorithm minimises an objective function that depends upon a new measure of influence for PCA models. A penalised version of the algorithm is also described for carrying our simultaneous subspace clustering and variable selection. The convergence of PSC is discussed in detail, and extensive simulation results and comparisons to competing methods are presented. The comparative performance of PSC has been assessed on six real gene expression data sets for which PSC often provides state-of-art results.     

人体运动分析的实例学习方法

目的 面向实时、准确、鲁棒的人体运动分析应用需求,从运动分析的特征提取和运动建模问题出发,本文人体运动分析的实例学习方法。方法 在构建人体姿态实例库基础上,首先,采用运动检测方法得到视频每帧的人体轮廓;其次,基于形状上下文轮廓匹配方法,从实例库中检索得到每帧视频的候选姿态集;最后,通过统计建模和转移概率建模实现人体运动分析。结果 对步行、跑步、跳跃等测试视频进行实验,基于轮廓的形状上下文特征表示和匹配方法具有良好的表达能力;本文方法运动分析结果,关节夹角平均误差在5°左右,与其他算法相比,有效提高了运动分析的精度。结论 本文人体运动分析的实例学习方法,能有效分析单目视频中的人体运动,并克服了映射的深度歧义,对运动的视角变化鲁棒,具有良好的计算效率和精度。     

Interactive videodiscs: a new approach to healthcare education

Linking computer and video technology has produced a new way to educate healthcare providers. These keyboard classrooms offer faster comprehension, better retention and lower costs than most traditional methods.     

Cognitive robotics: a new approach to artificial intelligence

This paper describes a research program about how to achieve artificial intelligence by building robots. It is part of the behavior-oriented AI approach, but differs in some of its hypotheses and methodological approach. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998