基于动作单元分析的人体动画合成方法研究

从运动捕获数据中提取出反映人体运动规律的基本动作单元,合成新的人体动画已成为研究热点.但已有动作单元提取方法忽略了运动序列的时序性和不同关节之间的运动相关性.针对该问题,提出了一种新的基本动作单元提取方法,首先,采用PCA方法对高维人体运动数据进行降维分析,并采用马氏距离平方度量姿态间的相似性;其次,结合动态时间归整方法和误差平方和准则对时序运动序列进行自动切分和标注;最后,建立不同动作单元之间的概率转移模型构建运动图,并根据约束条件合成新的逼真人体动画.     

基于多分辨率模型的快速运动过渡生成算法

运动捕获技术可以记录人体关节运动的细节,是当前最有前景的计算机动画技术.然而,运动数据的重用性一直是个难点,为此,多种运动编辑手段被提出.运动过渡是一种常见的编辑技术,它可以将输入的两端运动序列拼接,形成新的运动序列.其中,过渡点选择的合理与否直接影响着结果运动的质量.在两运动间选择过渡点,需要对输入运动的每一对帧之间分别计算帧间的距离,其计算复杂度是O(n2)的,通过引入多分辨率模型,文中将该复杂度降低到O(nlog2n),同时试验结果表明,此方法并未损害到结果运动的质量.     

视频中不完全运动特征的跟踪算法

在基于视频的人体运动捕获中，常用的特征跟踪算法对光照条件、图像噪音等非常敏感，而且不规则运动常使特征点或重叠、或自遮挡、或从视域中消失，给视频中运动特征跟踪带来很大的困难．为了有效地跟踪这些不完全运动的特征，提出一种有效的特征跟踪算法．实验结果表明，该方法不但能快速、精确地跟踪孤立特征，而且能有效地解决视频序列中存在较大噪音和不完全运动特征的跟踪问题．     

基于PD算法的两轮自平衡车直立控制

建立了两轮自平衡车的动力学模型;在Matlab环境中设计了基于PD控制算法的两轮车直立控制器;仿真分析了控制器中各参数对系统的影响。利用普通小功率直流电机,模拟量输出的陀螺仪和加速度传感器,BTS7960半桥芯片等低价位元件设计了一套硬件电路,并将仿真程序移植到16位Freescale单片机中对两轮自平衡车进行控制;实测数据验证了所设计控制算法的合理性和设计电路的正确性。     

基于骨干长度比例之运动重定目标算法

为了减轻动画制作劳动强度，提高动画制作产能以及自动产生仿真动画，提出了一种结合运动捕获器（Motion Capture)技术与逆向运动学原理的用于完成关节动画中实时运动重定目标（Motion Retargeting)的新算法，该算法的主要概念是首先根据“原动者”与“标的者”之身材比例，推算出、标的者”末端效应器之定位，然后再利用逆向运动学之算法求得“标的者”各关节之旋转角度，因为该算法充分地利用了捕获器所纪录的“原动者”运动信息的密集重复性，而且所设计之定位法则能满足原运动对未端效应器之约束，所以该方法能展现出与原运动十分相似的动画，同时不违背原设定之约束，实验数据也展示，并说明了该算法之效能与优点。     

基于单目视频运动跟踪的三维人体动画

针对传统人体动画制作成本高、人体运动受捕获设备限制等缺陷,提出了一种基于单目视频运动跟踪的三维人体动画方法。首先给出了系统实现框架,然后采用比例正交投影模型及人体骨架模型来恢复关节的三维坐标,关节的旋转欧拉角由逆运动学计算得到,最后采用H-anim标准对人体建模,由关节欧拉角驱动虚拟人产生三维人体动画。实验结果表明,该系统能够对人体运动进行准确的跟踪和三维重建,可应用于人体动画制作领域。     

基于可操作度的虚拟人手部避障运动控制算法

研究复杂作业环境中虚拟人手部避障运动的高精度控制问题,问题的关键是解决虚拟人手的设计.为了灵活操作能在操作的末端临时变换姿态,给控制过程中手臂转动路线,速度,加速度等参数的控制带来较大困难.传统的控制方法通过增加控制自由度来解决这个问题,但是一旦自由度增加,会带来冗余控制影响,弊端较为明显.提出一种采用可操作度矩阵的逆向运动学控制算法,引入可操作度模型进行肢体末端效应器运动路径的生成,与HAL链IK分析求解方法相结合,实现了真实感较强的肢体实时运动控制.通过仿真和动作捕获实验验证了算法的有效性,可应用于人机工程仿真中的避障控制和干涉检查.     

Synthesizing Character Animation with Smoothly Decomposed Motion Layers

The processing of captured motion is an essential task for undertaking the synthesis of high-quality character animation. The motion decomposition techniques investigated in prior work extract meaningful motion primitives that help to facilitate this process. Carefully selected motion primitives can play a major role in various motion-synthesis tasks, such as interpolation, blending, warping, editing or the generation of new motions. Unfortunately, for a complex character motion, finding generic motion primitives by decomposition is an intractable problem due to the compound nature of the behaviours of such characters. Additionally, decomposed motion primitives tend to be too limited for the chosen model to cover a broad range of motion-synthesis tasks. To address these challenges, we propose a generative motion decomposition framework in which the decomposed motion primitives are applicable to a wide range of motion-synthesis tasks. Technically, the input motion is smoothly decomposed into three motion layers. These are base-level motion, a layer with controllable motion displacements and a layer with high-frequency residuals. The final motion can easily be synthesized simply by changing a single user parameter that is linked to the layer of controllable motion displacements or by imposing suitable temporal correspondences to the decomposition framework. Our experiments show that this decomposition provides a great deal of flexibility in several motion synthesis scenarios: denoising, style modulation, upsampling and time warping.     

基于Jack的穿舱外服航天员工作空间研究

研究穿着舱外航天服的航天员工作空间是航天人机工程的重要课题,也是我国神州任务下一步的工作重点.作者提出了在Jack仿真平台的基础上,结合人体反向运动学算法,对航天员的出舱活动的可达空间进行仿真研究的方法.应用该方法可以建立穿着舱外航天服的航天员工作空间仿真系统,将运动学算法解算出来的人体工作空间数据在Jack平台上进行仿真,在现阶段和现有条件下研究航天员出舱活动是非常实用和有效的,可以为神州任务的航天员的工效评价提供参考依据.     

Animated human agents with motion planning capability for 3D-space postural goals

In this paper, we present a rule-based heuristic method of motion planning for an animated human agent with massively redundant degrees of freedom. It constructs motion plans to achieve 3D-space goals of control points on the body, e.g. a hand, while avoiding collisions. Like the artificial potential field approach, the method performs motion decisions in 3D world space rather than in joint space. To handle the massively redundant degrees of freedom, we use a qualitative kinematic model, which specifies motions of body parts and dependencies among them, without specifying the exact distance parameters. This model helps the body select appropriate primitive motions for given goals of control points more globally than does the gradient vector of an artificial potential field of the body. The method simulates (in imagination) the suggested plan to find whether some body parts hit objects, and how much they penetrate the objects. Based on this simulated collision information, the method suggests intermediate goals of the collision body parts. A subplan to achieve these intermediate goals is again postulated by using the qualitative kinematic model. This explicit reasoning helps alleviate the basic cause of local minima in the potential field approach, namely, conflicts between attractive potential fields due to goal positions of control points and repulsive potential fields due to obstacles.     

DI-Guy中人体动作生成方法研究

针对实时人物动作角色软件DI-Guy在运动编辑及新动作生成方面的局限,提出了结合3D人体动画软件及标准动.作捕捉数据文件在Vega环境中基于DI-Guy平台进行虚拟人动作生成的开发思路,给出了人体动作建模软件Poser中动作数据文件生成的详细开发过程,分析了Vega环境下动作捕捉数据文件的应用方法.依据上述开发思路进行了DI-Guy下用户定制动作的添加生成,所添加、定制的动作逼真、形象,而且系统运行速度不受影响,同时系统也可直接调用DI-Guy原有高层动作函数,大大方便了应用系统的开发.实验结果表明开发模式对于扩展DI-Guy的应用范围及提高虚拟人应用系统的开发效率具有重要的实用价值.     

Transition Motion from Ladder Climbing to Brachiation with Optimal Load-Allocation Control

Abstract

This paper describes the transition motion from ladder climbing to brachiation for a multi-locomotion robot (MLR). The MLR has versatile modes of locomotion, such as biped walking, quadruped walking, brachiation and ladder climbing. The transition is a challenging motion, because the environmental boundaries change and the robot has to switch the form of its locomotion depending on its surroundings, situations and purposes. The robot supports itself with three end-effectors that maintain its stability, while one hand transfers from a rung on the vertical ladder to a new rung behind the robot for brachiation. A closed kinematic chain is formed by the robot links and the ladder. In this case, if the number of position-controlled active joints is greater than the number of the chain’s degrees of freedom, an internal stress appears because of unavoidable position errors. The huge internal stress may lead some motors to become overloaded. Since the safety of each motor is very important for a serial-link robot, a load-allocation algorithm is proposed to balance the loads of the joint motors. The algorithm is verified through experiments.     

Enhanced avatar control using neural networks

This paper presents realistic avatar movements using a limited number of sensors. An inverse kinematics algorithm, SHAKF, is used to configure an articulated skeletal model, and a neural network is employed to predict the movement of joints not bearing sensors. The results show that the neural network is able to give a very close approximation to the actual rotation of the joints. This allows a substantial reduction in the number of sensors to configure an articulated human skeletal model.