COLLISION DETECTION AMONG MOVING OBJECTSIN MACHINING PROCESS SIMULATION

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A collisions evaluation method in virtual environment for collaborativeassembly

Collision detection is critical for collaborative assembly simulation to assist design processing. However, collisions between polygonal models may not reflect collisions between real objects in reality because of polygonal approximation and designed tolerance. This problem reduces the reliability of simulation in collaborative assembly and sometimes even results in wrong conclusions. To solve the problem, we propose a novel collision evaluation algorithm based on generalized penetration depth, approximation information, and tolerance information. Given two interfered polygonal models, generalized penetration depth is calculated using relative motion information. Then two thresholds, which are based on approximation information and tolerance information, are integrated to evaluate collisions between polygonal models. In order to distinguish the status of collisions for further analysis, the collisions between polygonal models are categorized into three types by evaluation algorithm, namely real collision, potential collision, and fake collision. Computational efficiency and accuracy of the evaluation algorithm are verified in a virtual collaborative assembly environment.     

Collision detection between the wrists of two robot arms in a common workspace

Detecting collisions for planning collision-free motion of the wrists of two robot arms in a common workspace is discussed in this paper. A collision-free motion can be obtained by detecting collisions along the preplanned trajectories using a sphere model for the wrist of each robot and then modifying the paths and/or trajectories of one or both robots to avoid the collision. In this paper, a collision detection algorithm is described and its role in collision avoidance is discussed. Collision detection is based on the premise that (1) the wrists of robots move monotonically on their preplanned straight line trajectories and (2) collisions never occur between the two wrists at the beginning points or end points.Research supported by the NASA-Langley Research Center under Grants #NAG-1-632 and #NAG-1-772 and the AT&T Foundation.     

织物仿真中的冲突检测和处理

冲突检测以及冲突处理一直是织物仿真的“瓶颈”问题。该文论述了对柔性物体如织物与刚体的冲突检测问题。通过正冲突物体表面周围建立一个很狭小的相当于防护屏的力场来避开冲突。将这个力场分割成一些连续不重迭的完全围绕着表面的小单元，一旦某个点要进入某个单元，就产生一个排斥力，这个力的大小和方向由速度、法向、点与表面的距离决定。     

基于混合包围盒的碰撞检测算法

提出了一种基于k-dops包围盒与包围球相结合的碰撞检测算法。预处理阶段为几何对象构造包围盒二叉树,其中节点的内层构造k-dops包围盒,节点的外层构造包围球。碰撞检测阶段,首先利用包围球快速排除不可能发生相交的物体,然后利用k-dops包围盒进一步精确地判断物体对是否发生相交。通过与QuickCD算法的性能进行比较,证明了这种混合包围盒能够有效地提高复杂结构几何体之间碰撞检测的效率。     

基于线性规划的碰撞检测算法研究

介绍了虚拟环境中一种基于凸多面体面信息对偶线性规划模型(DualModel)的快速旋转和移动物体之间干涉碰撞实时检测方法。该文详细介绍了建模过程和求解步骤,物体由构成凸多面体的三角形面信息表示,而物体的运动由一组虚拟现实环境中的全局移动和旋转矩阵表示。这种数学编程方法具有数据结构简单、算法可靠和速度快等优点,同时能够很好地解决高速(运动帧)碰撞的问题。这一方法通过使用主-对偶(primal-dual)内点方法来解线性规划方程,具有很好的效果,能够检测多物体对之间的碰撞。实验结果表明,基于数学编程的方法相对两种著名的工具包I-COLLIDE和SOLID,具有速度快和稳定可靠的优点,而I-COLLIDE和SOLID工具包基于两种著名的算法:LinCanny(LC)最近特征算法和GJK算法(EnhancedGilbertJohnsonandKeethialgorithm)。     

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.     

基于GPU加速的多物体碰撞检测方法

为了在虚拟环境中更加真实地模拟现实环境中物体的运动,需要在仿真系统中加入碰撞检测模块。现有的碰撞检测算法虽然能够快速检测两个物体是否相交,但在物体数量非常多的场景中,因需要对物体两两进行判断,所以仍无法达到较高的检测速度。利用GPU并行计算的特性,在GPU上增加一个预先剔除的过程,大幅度地快速排除不相交的物体,提高了检测的速度。     

Combining physically-based simulation of colliding objects with trajectory control

This paper describes a method that facilitates the use of physically-based models by animators. The main point is to give the animator a familiar interface, while providing a simulation module which detects collisions, thus enhancing realism. The user gives a set of key-frames to guide motion, but does not have to address problems such as interpenetration avoidance, deformations due to collisions, or realism of motion. The simulator will correct the trajectories and compute deformations according to each object's physical properties (such as mass, inertia, stiffness) as well as the collisions and contacts automatically detected during motion. To achieve this, objects are provided with actuators capable of generating forces and torques computed via generalized proportional-derivative controllers. When deflected by external actions, actuated objects try to return to their initial path. Speed variations over time are computed during the simulation, and depend on the complexity of the paths, on the objects models, and on the events such as collisions occurring during motion. In addition simulations are generated at interactive rates, even in the case of complex articulated objects. This facilitates the fine tuning of an animation sequence.     

Autonomous collision detection and avoidance for ARAGON USV: Development and field tests

This study addresses the development of algorithms for multiple target detection and tracking in the framework of sensor fusion and its application to autonomous navigation and collision avoidance systems for the unmanned surface vehicle (USV) Aragon. To provide autonomous navigation capabilities, various perception sensors such as radar, lidar, and cameras have been mounted on the USV platform and automatic ship detection algorithms are applied to the sensor measurements. The relative position information between the USV and nearby objects is obtained to estimate the motion of the target objects in a sensor‐level tracking filter. The estimated motion information from the individual tracking filters is then combined in a central‐level fusion tracker to achieve persistent and reliable target tracking performance. For automatic ship collision avoidance, the combined track data are used as obstacle information, and appropriate collision avoidance maneuvers are designed and executed in accordance with the international regulations for preventing collisions at sea (COLREGs). In this paper, the development processes of the vehicle platform and the autonomous navigation algorithms are described, and the results of field experiments are presented and discussed.     

Collision detection with relative screw motion

We introduce a framework for collision detection between a pair of rigid polyhedra. Given the initial and final positions and orientations of two objects, the algorithm determines whether they collide, and if so, when and where. All collisions, including collisions at different times, are computed at once along with properness values that measure the extent to which the collisions are between parts of the objects that properly face each other. This is useful for handling multiple (nearly) concurrent collisions and contact points.The relative motions of the rigid bodies are limited to screw motions. This limitation is not always completely accurate, but we can estimate the error introduced by the assumption.Our implementation uses rasterization to approximate the position and time of the collisions. This allows level-of-detail techniques that provide a tradeoff between accuracy and computational expense.The collision detection algorithms are only approximate, both because of the screw motion assumption and because of the rasterization. However, they can be made robust so as to give consistent information about collisions and to avoid sensitivity to roundoff errors.     

Efficient Collision Detection among Moving Spheres with Unknown Trajectories

Collision detection is critical for applications that demand a great deal of spatial interaction among objects. In such applications the trajectory of an object is often not known in advance either since a user is allowed to move an object at his/her will, or since an object moves under the rules that are hard to describe by exact mathematical formulas. In this paper we present a new algorithm that efficiently detects the collisions among moving spheres with unknown trajectories. We assume that the current position and velocity of every sphere can be probed at any time although its trajectory is unknown. We also assume that the magnitude of the acceleration of each sphere is bounded. Under these assumptions, we represent the bounding volume of the sphere as a moving sphere of variable radius, called a time-varying bound. Whenever the time-varying bounds of two spheres collide with each other, they are checked for actual collision. Exploiting these bounds, the previous event-driven approach for detecting the collisions among multiple moving spheres with ballistic trajectories is generalized for those with unknown trajectories. The proposed algorithm shows an interactive performance for thousands of moving spheres with unknown trajectories without any hardware help.     

运用改进的八叉树算法实现精确碰撞检测

提出一种精确碰撞检测算法,通过计算空间多面体之间距离实现碰撞检测功能.在计算2个多面体之间距离时,运用空间层次划分技术高效地寻找多面体中充分接近的三角面片,然后在这些三角面片中进行距离计算,以提高算法效率;同时运用改进的八叉树层次分割算法,与基本八叉树算法相比,减少了算法的空间复杂度.文中算法已经在超导Tokamak实验装置（EAST）虚拟装配仿真系统的碰撞检测模块中得到应用,通过实验比较,证明了该算法的可行性.     

Collision detection methodologies for rigid body assembly in a virtual environment

In this paper, a simulated three-dimensional virtual environment is created with a virtual 3D track ball for virtual object control. We propose a new technique called HV Partition to detect accurate collision in the assembly of two polyhedral solids in virtual simulation. This is a solid interference detection methodology achieved by automatically partitioning the object into smaller solid boxes. An important advantage of this methodology compared with other approaches is that it can deal with non-convex objects. This means that mechanical components, represented by non-convex polyhedra, traversing any degree of freedom, can be used in this virtual environment. Using this HV Partition method, the precise interference between two polyhedral solid objects can be found. The HV Partition methodology is applied following initial approximate collision detection using traditional bounding box and bounding sphere methods. The smaller the number of smaller boxes, the quicker is the performance of the collision algorithm. An optimal partition method is also given to reduce the number of smaller boxes in an object.     

Fast collision detection among multiple moving spheres

This paper presents an event-driven approach that efficiently detects collisions among multiple ballistic spheres moving in the 3D space. Adopting a hierarchical uniform space subdivision scheme, we are able to trace the trajectories of spheres and their time-varying spatial distribution. We identify three types of events to detect the sequence of all collisions during our simulation: collision, entering, and leaving. The first type of event is due to actual collisions, and the other two types occur when spheres move from subspace to subspace in the space. Tracing all such events in the order of their occurring times, we are able to avoid fixed time step simulation. When the size of the largest sphere is bounded by a constant multiple of that of the smallest, it takes O(n¯_c log n+n¯_e log n) time with O(n) space after O(n log n) time preprocessing to simulate n moving spheres, where n¯_c and n¯_e are the number of actual collisions and that of entering and leaving events during the simulation, respectively. Since n¯_e, depends on the size of subspaces, we modify the collision model from kinetic theory for molecular gas to determine the subspace sizes for the space subdivision scheme, that minimize simulation time. Experimental results show that collision detection can be done in linear time in n over a large range     

融合神经网络的布料碰撞检测算法

目的 针对当前在虚拟环境中布料柔体碰撞检测效率慢和准确性低的问题,提出一种根节点双层包围盒树结构和融合OpenNN （open neural networks library）神经网络加速预测碰撞检测的算法。方法 首先改进了碰撞检测常用的包围盒技术,提出根节点双层包围盒算法,减少包围盒的构造时间。其次使用神经网络优化碰撞检测技术,利用神经网络可以处理大量数据的优势,每次可以检测大量基本图元是否发生碰撞,解决了碰撞检测计算复杂性高的问题。最后准确地找到碰撞粒子并做出碰撞响应。结果 在相同的复杂布料模型情况下,根节点双层包围盒算法在运行速度上比传统混合包围盒算法快,耗时缩减了5.51%~11.32%。基于OpenNN算法的总耗时比根节点双层包围盒缩减了11.70%,比融合DNN （deep neural network）的自碰撞检测算法减少了6.62%。随着碰撞检测难度的增大,当布料模型的精度增加84%时,传统物理碰撞检测方法用时增加96%,融合DNN的自碰撞检测算法用时增加90.11%,而本文基于神经网络的算法用时仅增加了68.37%,同时表现出更高的稳定性,满足使用者对实时性的要求。结论 对于模拟场景中简单模型的碰撞,本文提出的根节点双层包围盒算法比传统的包围盒方法耗时短。对于复杂模型,基于OpenNN神经网络的碰撞检测算法在效率上优于传统的包围盒算法和融合DNN的自碰撞检查算法,而且模拟效果的准确性也得以保证,是一种高效的碰撞检测方法。     

Java 3D中运动物体间碰撞检测的研究

碰撞检测是虚拟制造中重要的课题之一,文章针对Java3D对三维物体碰撞检测支持的局限性,通过扩展Java3D的功能,构造了一种碰撞检测系统,采用了二叉树层次球模型来表示实体,对运动物体间进行碰撞检测,满足了可靠性和时间的连续性,较好地适应复杂环境的碰撞检测的需求。     

机器人碰撞检测方法形式化

为应对更为复杂的任务需求,现代机器人产业发展愈发迅猛.出于协调工作的灵活性、柔顺性以及智能性等多项考虑因素,多臂/多机器人充分发挥了机器人的强大作用,成为现代机器人产业的重要研究热点.在机器人双臂协调运行当中,机械臂之间以及机械臂与外部障碍物之间容易发生碰撞,可能会造成财产损失甚至人员伤亡.对机器人碰撞检测方法进行形式化验证,以球体和胶囊体形式化模型为基础,构建基本几何体单元之间最短距离和机器人碰撞的高阶逻辑模型,证明其相关属性及碰撞条件,建立机器人碰撞检测方法基础定理库,为多机系统碰撞检测算法可靠性与稳定性的验证提供技术支撑和验证框架.     

IBCD: a fast collision detection algorithm based on image space using OBB

Image‐based collision detection algorithms make efficient use of the graphics rendering hardware and reduce the computational cost of CPU. In this article, a fast collision detection algorithm based on image space is presented, which combines graphics hardware capabilities with a simplified geometric representation (oriented bounding box) in order to rapidly detect collisions between complex objects. The method can deal with arbitrary polyhedra, while preserving the merits of image‐based collision detection algorithms. This is achieved by decomposing the surfaces of an object into a list of convex pieces. High efficiency of the algorithm is obtained by organizing the convex pieces into a binary tree with each node representing a convex piece, and by adopting triangle strip compression. The algorithm has been implemented and compared with related algorithms. Copyright © 2003 John Wiley & Sons, Ltd.