Fast Continuous Collision Detection Research Articles

Medial IPC

We propose a framework of efficient nonlinear deformable simulation with both fast continuous collision detection and robust collision resolution. We name this new framework Medial IPC as it integrates the merits from medial elastics, for an efficient and versatile reduced simulation, as well as incremental potential contact, for a robust collision and contact resolution. We leverage medial axis transform to construct a kinematic subspace. Instead of resorting to projective dynamics, we use classic hyperelastics to embrace real-world nonlinear materials. A novel reduced continuous collision detection algorithm is presented based on the medial mesh. Thanks to unique geometric properties of medial axis and medial primitives, we derive closed-form formulations for identifying between-primitive collision within the reduced medial space. In the meantime, the implicit barrier energy that generates necessary repulsion forces for collision resolution is also formulated with the medial coordinate. In other words, Medial IPC exploits a universal reduced coordinate for simulation, continuous self-/collision detection, and IPC-based collision resolution. Continuous collision detection also allows more aggressive time stepping. In addition, we carefully implement our system with a heterogeneous CPU-GPU deployment such that massively parallelizable computations are carried out on the GPU while few sequential computations are on the CPU. Such implementation also frees us from generating training poses for selecting Cubature points and pre-computing their weights. We have tested our method on complicated deformable models and collision-rich simulation scenarios. Due to the reduced nature of our system, the computation is faster than fullspace IPC or other fullspace methods using continuous collision detection by at least one order. The simulation remains high-quality as the medial subspace captures intriguing and local deformations with sufficient realism.

6-DoF Haptic Rendering Using Continuous Collision Detection between Points and Signed Distance Fields.

We present an algorithm for fast continuous collision detection between points and signed distance fields, and demonstrate how to robustly use it for 6-DoF haptic rendering of contact between objects with complex geometry. Continuous collision detection is often needed in computer animation, haptics, and virtual reality applications, but has so far only been investigated for polygon (triangular) geometry representations. We demonstrate how to robustly and continuously detect intersections between points and level sets of the signed distance field. We suggest using an octree subdivision of the distance field for fast traversal of distance field cells. We also give a method to resolve continuous collisions between point clouds organized into a tree hierarchy and a signed distance field, enabling rendering of contact between rigid objects with complex geometry. We investigate and compare two 6-DoF haptic rendering methods now applicable to point-versus-distance field contact for the first time: continuous integration of penalty forces, and a constraint-based method. An experimental comparison to discrete collision detection demonstrates that the continuous method is more robust and can correctly resolve collisions even under high velocities and during complex contact.

MCCD: Multi-core collision detection between deformable models using front-based decomposition

We present a novel parallel algorithm for fast continuous collision detection (CCD) between deformable models using multi-core processors. We use a hierarchical representation to accelerate these queries and present an incremental algorithm that exploits temporal coherence between successive frames. Our formulation distributes the computation among multiple cores by using fine-grained front-based decomposition. We also present efficient techniques to reduce the number of elementary tests and analyze the scalability of our approach. We have implemented the parallel algorithm on eight core and 16 core PCs, and observe up to 7× and 13× speedups respectively, on complex benchmarks.

Continuous collision detection for articulated models using Taylor models and temporal culling

We present a fast continuous collision detection (CCD) algorithm for articulated models using Taylor models and temporal culling. Our algorithm is a generalization of conservative advancement (CA) from convex models [Mirtich 1996] to articulated models with non-convex links. Given the initial and final configurations of a moving articulated model, our algorithm creates a continuous motion with constant translational and rotational velocities for each link, and checks for interferences between the articulated model under continuous motion and other models in the environment and for self-collisions. If collisions occur, our algorithm reports the first time of contact (TOC) as well as collision witness features . We have implemented our CCD algorithm and applied it to several challenging scenarios including locomotion generation, articulated-body dynamics and character motion planning. Our algorithm can perform CCDs including self-collision detection for articulated models consisting of many links and tens of thousands of triangles in 1.22 ms on average running on a 3.6 GHz Pentium 4 PC. This is an improvement on the performance of prior algorithms of more than an order of magnitude.

Continuous collision detection for articulated models using Taylor models and temporal culling

We present a fast continuous collision detection (CCD) algorithm for articulated models using Taylor models and temporal culling. Our algorithm is a generalization of conservative advancement (CA) from convex models [Mirtich 1996] to articulated models with non-convex links. Given the initial and final configurations of a moving articulated model, our algorithm creates a continuous motion with constant translational and rotational velocities for each link, and checks for interferences between the articulated model under continuous motion and other models in the environment and for self-collisions. If collisions occur, our algorithm reports the first time of contact (TOC) as well as collision witness features. We have implemented our CCD algorithm and applied it to several challenging scenarios including locomotion generation, articulated-body dynamics and character motion planning. Our algorithm can perform CCDs including self-collision detection for articulated models consisting of many links and tens of thousands of triangles in 1.22 ms on average running on a 3.6 GHz Pentium 4 PC. This is an improvement on the performance of prior algorithms of more than an order of magnitude.

Fast continuous collision detection among deformable models using graphics processors

We present an interactive algorithm to perform continuous collision detection between general deformable models using graphics processors (GPUs). We model the motion of each object in the environment as a continuous path and check for collisions along the paths. Our algorithm precomputes the chromatic decomposition for each object and uses visibility queries on GPUs to quickly compute potentially colliding sets of primitives. We introduce a primitive classification technique to perform efficient continuous self-collision. We have implemented our algorithm on a 3.0GHz Pentium IV PC with a NVIDIA 7800GPU, and we highlight its performance on complex simulations composed of several thousands of triangles. In practice, our algorithm is able to detect all contacts, including self-collisions, at image-space precision in tens of milli-seconds.

Fast Continuous Collision Detection for Articulated Models

We present a novel algorithm to perform continuous collision detection for articulated models. Given two discrete configurations of the links of an articulated model, we use an “arbitrary in-between motion” to interpolate its motion between two successive time steps and check the resulting trajectory for collisions. Our approach uses a three-stage pipeline: (1) dynamic bounding-volume hierarchy (D-BVH) culling based on interval arithmetic; (2) culling refinement using the swept volume of line swept spheres (LSS’) and graphics hardware accelerated queries; (3) exact contact computation using OBB trees and continuous collision detection between triangular primitives. The overall algorithm computes the time of collision and contact locations, and prevents any interpenetration between the articulated model and the environment. We have implemented the algorithm and tested its performance on a 2.4GHz Pentium PC with 1Gbyte of RAM and a NVIDIA GeForce FX 5800 graphics card. In practice, our algorithm is able to perform accurate and continuous collision detection between articulated models and modestly complex environments at nearly interactive rates.

Fast continuous collision detection and handling for desktop virtual prototyping

This paper presents an overview of our recent work on continuous collision detection methods and constraints handling for rigid polyhedral objects. We demonstrate that continuous collision detection algorithms are practical in interactive dynamics simulation of complex polyhedral rigid bodies and show how continuous collision detection and efficient constraint-based dynamics algorithms allow us to perform various virtual prototyping tasks intuitively, precisely and robustly on commodity desktop computers. Especially, we present two applications of our system to actual industrial cases. We note that both tasks are performed with a simple 2D mouse on a high-end computer.

Fast Continuous Collision Detection between Rigid Bodies

Fast Continuous Collision Detection between Rigid Bodies

Fast Continuous Collision Detection between Rigid Bodies

This paper introduces a fast continuous collision detection technique for polyhedral rigid bodies. As opposed to most collision detection techniques, the computation of the first contact time between two objects is inherently part of the algorithm. The method can thus robustly prevent objects interpenetrations or collisions misses, even when objects are thin or have large velocities. The method is valid for general objects (polygon soups), handles multiple moving objects and acyclic articulated bodies, and is efficient in low and high coherency situations. Moreover, the method can be used to speed up existent continuous collision detection methods for parametric or implicit rigid surfaces. The collision detection algorithms have been successfully coupled to a real-time dynamics simulator. Various experiments are conducted that show the method's ability to produce high-quality interaction (precise objects positioning for example) between models up to tens of thousands of triangles, which couldn't have been performed with previous continuous methods.