DGR—5A机器人的动力学及控制

摘要 DGR-5A 机器人是我们自行设计的五自由度全关节型电动机器人.本文讨论了该机器人的动力学及控制问题.为此对机器人的各杆臂建立坐标系并详尽地计算了各杆臂的惯性参数.在推导了该机器人前三个自由度的动力学方程和分析了动力学特性之后,我们提出了一种实时计算量少,易于工程实现的控制方案.最后对该方案进行了仿真研究,仿真的结果是颇为令人满意的.     

A simple approximation to rigid body dynamics for computer animation

Recently, the dynamics of linked articulated rigid bodies has become a valuable tool for making realistic three-dimensional computer animations. An exact treatment of rigid body dynamics, however, is based on rather non-intuitive results from classical mechanics (e.g. the Euler equations for rotating bodies) and it relies heavily on sophisticated numerical schemes to solve (large) sets of coupled non-linear algebraic and differential equations. As a result, articulated rigid bodies are not yet supported by most real-time animation systems. This paper discusses an approach to rigid body dynamics which is based on (both conceptually and algorithmically much simpler) point mechanics; this gives rise to an asymptotically exact numerical scheme (NSI) which is useful in the context of real-time animation, provided that the number of degrees of freedom of the simulated system is not too large. Based on NSI, a second scheme (NS2) is derived which is useful for approximating the motions of linked articulated rigid bodies; NS2 turns out to be sufficiently fast to give at least qualitative results in real-time simulation. In general, the algorithm NS2 is not necessarily (asymptotically) exact, but a quantitative analysis shows that in the absence of reaction forces it conserves angular momentum.     

Fluid Simulation with Articulated Bodies

We present an algorithm for creating realistic animations of characters that are swimming through fluids. Our approach combines dynamic simulation with data-driven kinematic motions (motion capture data) to produce realistic animation in a fluid. The interaction of the articulated body with the fluid is performed by incorporating joint constraints with rigid animation and by extending a solid/fluid coupling method to handle articulated chains. Our solver takes as input the current state of the simulation and calculates the angular and linear accelerations of the connected bodies needed to match a particular motion sequence for the articulated body. These accelerations are used to estimate the forces and torques that are then applied to each joint. Based on this approach, we demonstrate simulated swimming results for a variety of different strokes, including crawl, backstroke, breaststroke, and butterfly. The ability to have articulated bodies interact with fluids also allows us to generate simulations of simple water creatures that are driven by simple controllers.     

基于CCD星体跟踪器的舰船位置估计算法研究

CCD星体跟踪器作为舰船位置测量仪器，因其定位精度高、无位置积累误差、快速和智能化工作而受到重视。本文根据CCD星体跟踪器确定舰船位置的原理，介绍了一种用改进遗传算法来进行位置估算的新方法，仿真结果表明效果良好。     

A Dynamic Motion Control Technique for Human-like Articulated Figures

This paper presents a dynamic motion control technique for human-like articulated figures in a physically based character animation system. This method controls a figure such that the figure tracks input motion specified by a user. When environmental physical input such as an external force or a collision impulse are applied to the figure, this method generates dynamically changing motion in response to the physical input. We have introduced comfort and balance control to compute the angular acceleration of the figure's joints. Our algorithm controls the several parts of a human-like articulated figure separetely through the minimum number of degrees-of-freedom. Using this approach, our algorithm simulates realistic human motions at efficient computational cost. Unlike existing dynamic simulation systems, our method assumes that input motion is already realistic, and is aimed at dynamically changing the input motion in real-time only when unexpected physical input is applied to the figure. As such, our method works efficiently in the framework of current computer games.     

TightCCD: Efficient and Robust Continuous Collision Detection using Tight Error Bounds

http://gamma.cs.unc.edu/BSC/ We present a realtime and reliable continuous collision detection (CCD) algorithm between triangulated models that exploits the floating point hardware capability of current CPUs and GPUs. Our formulation is based on Bernstein Sign Classification that takes advantage of the geometry properties of Bernstein basis and Bézier curves to perform Boolean collision queries. We derive tight numerical error bounds on the computations and employ those bounds to design an accurate algorithm using finite‐precision arithmetic. Compared with prior floatingpoint CCD algorithms, our approach eliminates all the false negatives and 90–95% of the false positives. We integrated our algorithm (TightCCD) with physically‐based simulation system and observe speedups in collision queries of 5–15X compared with prior reliable CCD algorithms. Furthermore, we demonstrate its benefits in terms of improving the performance or robustness of cloth simulation systems.     

Linear Time Stable PD Controllers for Physics-based Character Animation

In physics-based character animation, Proportional-Derivative (PD) controllers are commonly used for tracking reference motions in motor control tasks. Stable PD (SPD) controllers significantly improve the numerical stability of traditional PD controllers and support large gains and large integration time steps during simulation [TLT11]. For an articulated rigid body system with n degrees of freedom, all SPD implementations to date, however, use an O(n³) dense matrix factorization based method. In this paper, we propose a linear time algorithm for SPD computation, which is based on Featherstone's forward dynamics formulation for articulated rigid body systems in generalized coordinates [Fea14]. We demonstrate the performance advantage of our algorithm by comparing with both the conventional dense matrix factorization based method and an alternative sparse matrix factorization based method. We show that the proposed algorithm provides superior stability when controlling complex models at large time steps. We further demonstrate that our algorithm can improve the learning speed and quality of a Deep Reinforcement Learning (DRL) system for physics-based character animation.     

Soft Articulated Characters with Fast Contact Handling

Fast contact handling of soft articulated characters is a computationally challenging problem, in part due to complex interplay between skeletal and surface deformation. We present a fast, novel algorithm based on a layered representation for articulated bodies that enables physically-plausible simulation of animated characters with a high-resolution deformable skin in real time. Our algorithm gracefully captures the dynamic skeleton-skin interplay through a novel formulation of elastic deformation in the pose space of the skinned surface. The algorithm also overcomes the computational challenges by robustly decoupling skeleton and skin computations using careful approximations of Schur complements, and efficiently performing collision queries by exploiting the layered representation. With this approach, we can simultaneously handle large contact areas, produce rich surface deformations, and capture the collision response of a character/s skeleton.     

Articulated pose identification with sparse point features

We propose a general algorithm for identifying an arbitrary pose of an articulated subject with sparse point features. The algorithm aims to identify a one-to-one correspondence between a model point-set and an observed point-set taken from freeform motion of the articulated subject. We avoid common assumptions such as pose similarity or small motions with respect to the model, and assume no prior knowledge from which to infer an initial or partial correspondence between the two point-sets. The algorithm integrates local segment-based correspondences under a set of affine transformations, and a global hierarchical search strategy. Experimental results, based on synthetic pose and real-world human motion data demonstrate the ability of the algorithm to perform the identification task. Reliability is increasingly compromised with increasing data noise and segmental distortion, but the algorithm can tolerate moderate levels. This work contributes to establishing a crucial self-initializing identification in model-based point-feature tracking for articulated motion.     

Algorithm optimization in molecular dynamics simulation

Establishing the neighbor list to efficiently calculate the inter-atomic forces consumes the majority of computation time in molecular dynamics (MD) simulation. Several algorithms have been proposed to improve the computation efficiency for short-range interaction in recent years, although an optimized numerical algorithm has not been provided. Based on a rigorous definition of Verlet radius with respect to temperature and list-updating interval in MD simulation, this paper has successfully developed an estimation formula of the computation time for each MD algorithm calculation so as to find an optimized performance for each algorithm. With the formula proposed here, the best algorithm can be chosen based on different total number of atoms, system average density and system average temperature for the MD simulation. It has been shown that the Verlet Cell-linked List (VCL) algorithm is better than other algorithms for a system with a large number of atoms. Furthermore, a generalized VCL algorithm optimized with a list-updating interval and cell-dividing number is analyzed and has been verified to reduce the computation time by 30∼60% in a MD simulation for a two-dimensional lattice system. Due to similarity, the analysis in this study can be extended to other many-particle systems.     

一种空间面阵CCD成像的曝光时间计算方法

提出一种基于图像质量评价的空间面阵CCD相机成像最佳曝光时间的自动计算方法。在对静止卫星CCD成像链路仿真的基础 上,利用改进的图像曝光估计算法确定出指定拍摄地点和拍摄时间的空间面阵CCD相机曝光的正常范围,通过筛选的图像质量评价指标计算出相应的曝光时间。实验结果表明,该方法所得曝光时间对应的图像质量是最佳的。     

Efficient global penetration depth computation for articulated models

We present an algorithm for computing the global penetration depth between an articulated model and an obstacle or between the distinctive links of an articulated model. In so doing, we use a formulation of penetration depth derived in configuration space. We first compute an approximation of the boundary of the obstacle regions using a support vector machine in a learning stage. Then, we employ a nearest neighbor search to perform a runtime query for penetration depth. The computational complexity of the runtime query depends on the number of support vectors, and its computational time varies from 0.03 to 3 milliseconds in our benchmarks. We can guarantee that the configuration realizing the penetration depth is penetration free, and the algorithm can handle general articulated models. We tested our algorithm in robot motion planning and grasping simulations using many high degree of freedom (DOF) articulated models. Our algorithm is the first to efficiently compute global penetration depth for high-DOF articulated models.     

An Algorithm with Logarithmic Time Complexity for Interactive Simulation of Hierarchically Articulated Bodies Using a Distributed-memory Architecture

The dynamic simulation of large systems of hierarchically articulated bodies is very time-consuming and cannot be done in real time using current one-processor workstations. This paper discusses the parallelization of dynamic simulation algorithms for such systems. First, the methods used in computer animation for solving initial-value problems are compared. Using test suites based on articulated bodies, the Gear method for non-stiff problems is identified as the solver with the least right-hand-side evaluations of the differential equations for the executed tests. On the basis of this method and the articulated-body method, a ‘simulation engine’ for distributed-memory architectures is presented. By reimplementing the Gear method and rearranging its parts, logarithmic time complexity is achieved for hierarchically articulated bodies. By using the simulation engine, interactive, physically based animation of large articulated figures is possible.     

基于多传感器的家庭服务机器人局部导航方法研究

本文提出了一种基于多传感器的家庭服务机器人局部导航方法。首先,采用单个摄像头获取居室内障碍物的图像信息,利用超声波传感器和红外线传感器探测障碍物的距离信息。然后,据此计算在机器人运动方向上障碍物的遮挡空间或者多个障碍物之间的实际距离,再根据机器人自身的大小计算避开障碍物应该转动的方向及角度,从而实现居室内的自主导航。最后,仿真实验结果证明了该方法的有效性。     

CCD扫描噪声建模及自适应滤波算法

为去除图像因扫描引入的电荷耦合器件(CCD)噪声,提出一种基于变窗口的自适应滤波算法。分析CCD主要噪声：散粒,固有和输出噪声的噪声特性,建立CCD扫描噪声模型,根据噪声和边缘处理方式的不同设计了局部和全局自适应滤波器。实验结果表明,该算法具有较好的信噪分离能力,在充分抑制噪声的同时,很好地保持了边缘,提高对比度,视觉效果良好。     

基于CCD的多方向平行射束投影系统图像重建

高分辨率的空间敏感阵列以及实时、精确的图象重建算法是层析成象技术的关键。为了得到足够的投影数据,提出了几种用于光学层析成像的多方向平行射束投影结构,这几种结构均采用CCD器件作为敏感阵列,可得到高分辨率的被测物场投影信息。同时分析了这几种投影结构下图象重建中权重系数的计算方法,并对不同结构的图象重建效果进行了比较,得出了投影方向数、投影数据与重建图象质量之间的关系。仿真结果表明,采用CCD的平行射束投影系统可重建出很高质量的图象。     

Analyzing and capturing articulated hand motion in image sequences

Capturing the human hand motion from video involves the estimation of the rigid global hand pose as well as the nonrigid finger articulation. The complexity induced by the high degrees of freedom of the articulated hand challenges many visual tracking techniques. For example, the particle filtering technique is plagued by the demanding requirement of a huge number of particles and the phenomenon of particle degeneracy. This paper presents a novel approach to tracking the articulated hand in video by learning and integrating natural hand motion priors. To cope with the finger articulation, this paper proposes a powerful sequential Monte Carlo tracking algorithm based on importance sampling techniques, where the importance function is based on an initial manifold model of the articulation configuration space learned from motion-captured data. In addition, this paper presents a divide-and-conquer strategy that decouples the hand poses and finger articulations and integrates them in an iterative framework to reduce the complexity of the problem. Our experiments show that this approach is effective and efficient for tracking the articulated hand. This approach can be extended to track other articulated targets.     

Online Motion Capture Marker Labeling for Multiple Interacting Articulated Targets

In this paper, we propose an online motion capture marker labeling approach for multiple interacting articulated targets. Given hundreds of unlabeled motion capture markers from multiple articulated targets that are interacting each other, our approach automatically labels these markers frame by frame, by fitting rigid bodies and exploiting trained structure and motion models. Advantages of our approach include: 1) our method is an online algorithm, which requires no user interaction once the algorithm starts. 2) Our method is more robust than traditional the closest point-based approaches by automatically imposing the structure and motion models. 3) Due to the use of the structure model which encodes the rigidity of each articulated body of captured targets, our method can recover missing markers robustly. Our approach is efficient and particularly suited for online computer animation and video game applications.     

3D关节角色基于OBB的实时动态碰撞检测

论文实现了为3D角色的每个骨骼构建一个OBB(OrientedBoundingBox,有向包围盒)用于实时动态碰撞检测的方法,并在实现中以MicrosoftDirectXAPI为基础,通过扩展X模型文件模版,将离线计算的OBB嵌入3D关节角色模型免去运行时的计算。该方法较大地提高了3D角色实时动态碰撞检测效率,可应用于第一人称射击游戏、3D角色模拟游戏、机器人寻径以及虚拟战术环境中。     

菲涅耳全息图的CCD记录及重现

为了更好地进行菲涅耳全息图的CCD记录及重现,设计了一种CCD同轴全息图的重构算法,该方法首先用CCD代替传统干版直接记录菲涅耳同轴全息图,并以位图形式存储到计算机中;然后利用数值计算代替光学衍射过程来再现物体的像;最后通过实验验证了该算法及数字全息图的不可撕毁性。