A review of collision detection for deformable objects

Interactive environments for dynamically deforming objects play an important role in surgery simulation and entertainment technology. These environments require fast deformable models and very efficient collision handling techniques. While collision detection for rigid bodies is well-investigated, collision detection for deformable objects introduces additional challenging problems. This paper focusses on these aspects and summarizes recent research in the area of deformable collision detection. Various approaches based on bounding volume hierarchies, distance fields, and spatial partitioning are discussed. Further, image-space techniques and stochastic methods are considered. Applications in cloth modeling and surgical simulation are presented.

Rapid collision detection for deformable objects using inclusion-fields applied to cloth simulation

We present an algorithm for collision detection between multiple deformable objects translating in a large environment. We use Spatial Partitioning to subdivide the scene and a Bounding Volume Hierarchy to decompose the objects, using octrees in both cases. The algorithm is divided in two parts, the Broad and Narrow Phases, with objects that can be rigid or deformable. In the Broad Phase, an octree is used to partition the scene and cull away the object’s Bounding Volumes that are distant. In the Narrow Phase, a hierarchical decomposition of Axis Aligned Bounding Boxes or spheres is employed to reduce the number of primitives in the pairwise comparisons. In summary this work is a general-purpose collision detection technique for performing real time collision detection of deformable bodies in interactive 3D applications.

Physical based modelling (PBM) uses physics simulation engines (PSE) to provide the dynamic behaviour and collision detection of virtual objects in virtual environments emulating the real world. There exists a variety of PSEs, each one with pros and cons according to the application in which they are employed. Each physics engine uses its proprietary collision detection algorithm. Collision detection is a key aspect of assembly tasks and its performance is dependent on the way virtual objects are represented. In general, objects can be divided into two groups: convex and concave, the latter being the most common and challenging for collision detection algorithms. This study reports on three different methods to represent concave objects. GIMPACT, Hierarchical Approximate Convex Decomposition (HACD) and Approximate Convex Decomposition (ACD), which are evaluated and compared based on their collision detection performances. An exact convex decomposition algorithm, named as ConvexFT, is also proposed and analyzed in this paper. Finally the performance of the three existing methods and the ConvexFT proposed approach are compared in order to assess which model representation algorithm is best suited for haptic-virtual assembly tasks.

We propose a new technique to detect objects and collisions of geometric objects in cyber space. This technique uses depth values of the Z-buffer in rendering scene. We use the orthographic projection for collision detection. Our method uses two depth value sets. One is obtained through rendering the cyber space from the sensor object toward a target point. This set does not have the depth values of the sensor object. Another one is obtained through rendering only the sensor object in the reverse direction. From these two depth value sets, we obtain the distance between the sensor object and others for each pixel. This technique requires only one or two rendering processes and it is independent from the complexity of the object's shape, deformation or motion. In this paper we evaluate the efficiency of this method on the GPUs we currently use.

February 01 2006 Efficient Collision Culling among Deformable Objects using Graphics Processors Naga K. Govindaraju, Naga K. Govindaraju Search for other works by this author on: This Site Google Scholar Ming C. Lin, Ming C. Lin Search for other works by this author on: This Site Google Scholar Dinesh Manocha Dinesh Manocha Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill NC 27599-3175 Search for other works by this author on: This Site Google Scholar Author and Article Information Naga K. Govindaraju Ming C. Lin Dinesh Manocha Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill NC 27599-3175 Correspondence to: naga@cs.unc.edu © 2006 by the Massachusetts Institute of Technology2006 Presence: Teleoperators and Virtual Environments (2006) 15 (1): 62–76. https://doi.org/10.1162/pres.2006.15.1.62 Cite Icon Cite Permissions Share Icon Share Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Naga K. Govindaraju, Ming C. Lin, Dinesh Manocha; Efficient Collision Culling among Deformable Objects using Graphics Processors. Presence: Teleoperators and Virtual Environments 2006; 15 (1): 62–76. doi: https://doi.org/10.1162/pres.2006.15.1.62 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentAll JournalsPRESENCE: Virtual and Augmented Reality Search Advanced Search Abstract We present a fast collision culling algorithm for performing inter- and intra-object collision detection among complex models using graphics hardware. Our algorithm utilizes visibility queries on the GPUs to eliminate a subset of geometric primitives that are not in close proximity and computes a potentially colliding set (PCS) of primitives. We perform no precomputation and the algorithm proceeds in multiple stages: object-level PCS computation, subobject level PCS computation, followed by exact collision detection. We extend our PCS computation algorithm to perform intra-object or self-collisions between complex models. Furthermore, we describe a novel visibility-based classification scheme to reduce the size of potentially-colliding sets of objects and primitives, and the number of visibility queries for further improving the performance and culling efficiency. We have implemented our algorithm on a PC with an NVIDIA GeForce FX 6800 Ultra graphics card and applied it to three complex simulations, each consisting of objects with tens of thousands of triangles. In practice, we are able to compute all the self-collisions for cloth simulation up to image-space precision at interactive rates. This content is only available as a PDF. © 2006 by the Massachusetts Institute of Technology2006 You do not currently have access to this content.

Computational time of collision detection can be exceeded when there are too many checking for non-colliding primitives on some particular areas of high-resolution deformable objects. The problem is usually solved with best-fit bounding volume hierarchies (BVHs) which require much more memory and time for updating the bounding volumes when the objects deform. Hence, a particle-based collision detection method is enhanced to reduce the checking for non-colliding primitives by adding movable particles on the object vertices corresponding to each particular area. The distance of corresponding particles are computed for selecting the closest vertices between each pair of objects. The experimental results show that the proposed method has less colliding checking time than using BVHs when using with the deformable objects. Moreover, the proposed primitive-checking method can be parallel processed on GPU increasing speed performance while accuracy is still preserved when the results are compared to the previous BVH method.

In many interactive computer graphics applications, users are represented as virtual characters called avatars. Collision detection is a pre-requisite in interactive computer graphics application so that appropriate response and realistic behaviour can be generated. However, it will not be easy to anticipate collisions since objects' motion are dependant on user interaction and avatar manipulation. Ideally, collision detection needs to be done efficiently, with accurate result in the shortest time possible. However, due to its computationally intensive nature, collision detection could cause a bottleneck to the system. A variety of techniques, data structures and algorithms were proposed to accelerate the collision detection process. Acceleration data structures are widely used not only to promote faster collision detection, but also in the field of ray tracing and deformable objects simulation. This paper discusses the use of bounding volume hierarchy as an acceleration data structure in collision detection for avatar in virtual environment, as well as similar methods used in interactive ray tracing and deformable objects simulation. Based on these findings, method for fast bounding volume hierarchy construction is proposed as a first step towards efficient avatar collision detection.

The two main objectives of virtual assembly are: (1) to train assembly-operators through virtual assembly models, and (2) to simultaneously evaluate products for ease-of-assembly. The focus of this paper is on developing computational techniques for virtual assembly of thin deformable beam and plate-like objects. To meet the objectives of virtual assembly, the underlying computational technique must: (1) be carried out at a high frame-rate (>20 frames/second), (2) be accurate (<5% error in deformation and force estimation), (3) be conducive to collision detection, and (4) support rapid design evaluations. We argue in this paper that popular computational techniques such as 3-D finite element analysis, boundary element analysis and classic beam/plate/shell analysis fail to meet these requirements. We therefore propose a new class of dual representation techniques for virtual assembly of thin solids, where the geometry is retained in its full 3-D form, while the underlying physics is dimensionally reduced, delivering: (1) high computational efficiency and accuracy (over 20 frames per second with <1% deformation error), and (2) direct CAD model processing, i.e., the CAD model is not geometrically simplified, and 3-D finite element mesh is not generated. In particular, a small-size stiffness matrix with about 300 degrees of freedom per deformable object is generated directly from a coarse surface triangulation, and its LU-decomposition is then exploited during real-time simulation. The accuracy and efficiency of the proposed method is established through numerical experiments and a case study.

A new collision detection method for CSG-represented objects in virtual manufacturing

Performing collision detection between convex objects in virtual environment simulation is one of vital problems in computer visualization research area. Given a set of two or more colliding objects, in order to determine the exact point of contact between object we need to undergo various high computation algorithm. In this paper, we describes our current work of determining the precise contact by measuring the distance between near colliding objects in order to maintain the accuracy and improve the speed of collision detection algorithm. Common method determine the distance by checking for vertices and edges point between objects in brute force condition. Compared to our method, by given set of objects in virtual environment world, we find the closest point between near colliding objects and bound the potential colliding area with an Axis-Aligned Bounding-Box. Then, we approximate the distance by measuring the distance of the box itself and hence recognize potential colliding area faster than the common method. Our method proven to most effective and efficient for narrow phase collision detection by removing unnecessary testing and reduced computational cost.

Nowadays robotic applications are widespread and most of the manipulation tasks are efficiently solved. However, Deformable-Objects (DOs) still represent a huge limitation for robots. The main difficulty in DOs manipulation is dealing with the shape and dynamics uncertainties, which prevents the use of model-based approaches (since they are excessively computationally complex) and makes sensory data difficult to interpret. This thesis reports the research activities aimed to address some applications in robotic manipulation and sensing of Deformable-Linear-Objects (DLOs), with particular focus to electric wires. In all the works, a significant effort was made in the study of an effective strategy for analyzing sensory signals with various machine learning algorithms. In the former part of the document, the main focus concerns the wire terminals,&#13;\ni.e. detection, grasping, and insertion. First, a pipeline that integrates vision and tactile sensing is developed, then further improvements are proposed for each module. &#13;\nA novel procedure is proposed to gather and label massive amounts of training images for object detection with minimal human intervention. Together with this strategy, we extend a generic object detector based on Convolutional-Neural-Networks for orientation prediction. &#13;\nThe insertion task is also extended by developing a closed-loop control capable to guide the insertion of a longer and curved segment of wire through a hole, where the contact forces are estimated by means of a Recurrent-Neural-Network. &#13;\nIn the latter part of the thesis, the interest shifts to the DLO shape. Robotic reshaping of a DLO is addressed by means of a sequence of pick-and-place primitives, while a decision making process driven by visual data learns the optimal grasping locations exploiting Deep Q-learning and finds the best releasing point. The success of the solution leverages on a reliable interpretation of the DLO shape. For this reason, further developments are made on the visual segmentation.

Virtual reality applications such as computer games form a large portion of the computing industry. The increasing expectations for immersive and interactive entertainment require fast graphics rendering with a lot of details and high-fidelity physics simulation. Interference and collision detection between general polygonal models, including all those tasks in the simulated motion of solids which cannot penetrate one another, has been widely explored. The most recent works have been focused on increasing the number of collision queries per second to an interactive rate, assuming that the computing resources such as memory, CPU capacity, and network bandwidth are sufficient all the time. However, the performance of a collision detection algorithm may vary in real environments where the available computing resources are not sufficient or are dynamic at runtime. Such an unstable performance directly affects the interactive rate of many applications, which is not acceptable. This drawback has been noticed extensively by practitioners. Little research work has been introduced to systematically solve this problem. One way out of this problem is to use a technique to dynamically adjust the cost of the collision detection (CD) task according to the measurements of available resources. In this dissertation, a solution to the problem is proposed. The problem is analyzed under three different physical environments: single low end computer, clustered multiple-machine setting, and distributed environment. An extensive comparative study of several methods is done in the context of polygonal models. A new approach, "multi-resolution collision detection", is proposed. It performs time-critical and exact interference detection on continuous level of detail (LOD) representations of arbitrary triangle meshes undergoing rigid body motion. The goal of this work is to extend the bounding volume hierarchy (BVH) based collision detection approach from static to dynamic in order to adapt the cost of collision detection to the available resource in either centralized or distributed environments. Several adaptive mesh refinement criteria based on viewing distance, application context, and movement velocity are proposed. Global and local mesh refinement algorithms and a BVH CD algorithm are introduced. They are computationally simple and achieve reliable real-time performance. The complexity of the proposed algorithms is analyzed and proved. Measurements are taken to compare with the analytical results and strong agreements are achieved. The major application areas considered are distributed virtual environments (DVEs) and interactive haptic applications.

This paper presents a control method using an adjusting output-limiter for stable haptic rendering in a virtual environment. In a simulation of force-reflecting interaction with deformable objects in a virtual environment, a quick computation of the accurate impedance of deformable objects is rare. This is particularly true when physics-based models, such as tensor-mass models or mass-spring models, are used. The problem is aggravated if the simulation involves changes in the geometry and/or impedance of the deformation model, such as cutting or suturing. The proposed control method guarantees stable haptic interactions with deformable objects of unknown and/or varying impedance. The method is based on the time-domain passivity theorem and the two-port network model. The controller adjusts the maximum permissible force to guarantee the passivity of the haptic system at every sampling instant. The controller notes only the magnitude of the reflective force, and does not depend on properties of the employed force model. This allows the proposed control method applicable to haptic systems involving deformable objects with unknown, nonlinear, and/or time-varying impedance. Designs of the controllers are presented for impedance-type and admittance-type haptic systems. The method is also extended for multiple degrees-of-freedom.

The paper presents an approach to the detection of deformable objects in single images. To this end we propose a robust match metric that preserves the relative edge point neighborhood, but allows significant shape changes. Similar metrics have been used for the detection of rigid objects (Olson and Huttenlocher, 1997; Steger, 2002). To the best of our knowledge this adaptation to deformable objects is new. In addition, we present a fast algorithm for model deformation. In contrast to the widely used thin-plate spline (Bookstein, 1989; Donato and Belongie, 2002), it is efficient even for several thousand points. For arbitrary deformations, a forward-backward interpolation scheme is utilized. It is based on harmonic inpainting, i.e. it regularizes the displacement in order to obtain smooth deformations. Similar to optical flow, we obtain a dense deformation field, though the template contains only a sparse set of model points. Using a coarse-to-fine representation for the distortion of the template further increases efficiency. We show in a number of experiments that the presented approach in not only fast, but also very robust in detecting deformable objects.