Continuous Collision Detection Research Articles

Design and development of a personalized virtual reality-based training system for vascular intervention surgery

Background and objectivesVirtual training has emerged as an exceptionally effective approach for training healthcare practitioners in the field of vascular intervention surgery. By providing a simulated environment and blood vessel model that enables repeated practice, virtual training facilitates the acquisition of surgical skills in a safe and efficient manner for trainees. However, the current state of research in this area is characterized by limitations in the fidelity of blood vessel and guidewire models, which restricts the effectiveness of training. Additionally, existing approaches lack the necessary real-time responsiveness and precision, while the blood vessel models suffer from incompleteness and a lack of scientific rigor. MethodsTo address these challenges, this paper integrates position-based dynamics (PBD) and its extensions, shape matching, and Cosserat elastic rods. By combining these approaches within a unified particle framework, accurate and realistic deformation simulation of personalized blood vessel and guidewire models is achieved, thereby enhancing the training experience. Furthermore, a multi-level progressive continuous collision detection method, leveraging spatial hashing, is proposed to improve the accuracy and efficiency of collision detection. ResultsOur proposed blood vessel model demonstrated acceptable performance with the reduced deformation simulation response times of 7 ms, improving the real-time capability at least of 43.75 %. Experimental validation confirmed that the guidewire model proposed in this paper can dynamically adjust the density of its elastic rods to alter the degree of bending and torsion. It also exhibited a deformation process comparable to that of real guidewires, with an average response time of 6 ms. In the interaction of blood vessel and guidewire models, the simulator blood vessel model used for coronary vascular intervention training exhibited an average response time of 15.42 ms, with a frame rate of approximately 64 FPS. ConclusionsThe method presented in this paper achieves deformation simulation of both vascular and guidewire models, demonstrating sufficient real-time performance and accuracy. The interaction efficiency between vascular and guidewire models is enhanced through the unified simulation framework and collision detection. Furthermore, it can be integrated with virtual training scenarios within the system, making it suitable for developing more advanced vascular interventional surgery training systems.

ARGo: augmented reality-based mobile Go stone collision game

In this study, we present a mobile Go stone collision game based on augmented reality, which we call ARGo, inspired by the traditional Korean board game, Alkkagi. ARGo aims to resolve two main issues: (1) the portability and space constraints of the original Alkkagi and (2) the limited sense of reality due to the touchscreen-based interface of the existing mobile Alkkagi games. To improve a sense of the reality of the game, ARGo provides a gameplay interface similar to the original Alkkagi by recognizing the user‘s hand motion based on AR. Additionally, it provides a customization mechanism for each user to improve the recognition of the hand motion and the strength of the attack considering each user‘s characteristics. Finally, we make the following three main contributions. First, we employ the automata theory to design the game and collision scenarios between stones. Consequently, we can clearly define the complicated states incurred by AR-based motion recognition and collisions between virtual objects. Second, we propose a collision equation based on Continuous Collision Detection tailored to ARGo, i.e., Go stones and their collisions. Through experimental studies, we demonstrate that the collision equation enables the simulation of the exact collision effects. Third, through user experience studies, we verify the effectiveness of ARGo by showing the effects of the functions implemented in ARGo and its superiority over the existing mobile game Alkkagi Mania.

Deep Neural Network-Based Cloth Collision Detection Algorithm

The quality of collision detection algorithm directly affects the performance of the whole simulation system. To address the low efficiency and low accuracy in detecting the collisions of flexible cloths in virtual environments, this paper proposes an oriented bounding box (OBB) algorithm with a simplified model, tree structure for a root-node double bounding box, and continuous collision detection algorithm incorporating an OpenNN-based neural network optimization. First, for objects interacting with the cloths with more complex modeling, the model is simplified with a surface simplification algorithm based on the quadric error metrics, and the simplified model is used to construct an OBB. Second, a bounding box technique commonly used for collision detection is improved, and a root-node double bounding box algorithm is proposed to reduce the construction time for the bounding box. Finally, neural networks are used to optimize the continuous collision detection algorithm, as neural networks can efficiently process large amounts of data and remove disjoint collision pairs. An experiment shows that the construction of an OBB using the simplified model is almost identical to that of the original model, but the taken to construct the OBB is reduced by a factor of approximately 2.7. For the same cloth, it takes 5.51%–11.32% less time to run the root-node double bounding box algorithm than the traditional-hybrid bounding box algorithm. With an average removal rate nearly identical to that of the traditional filtering method, the elapsed time is reduced by 7%–11% by using the continuous collision detection algorithm based on an OpenNN neural network optimization. The simulation results are realistic and in line with the requirements for real-time cloth simulations.

A Linear and Angular Momentum Conserving Hybrid Particle/Grid Iteration for Volumetric Elastic Contact

We present a momentum conserving hybrid particle/grid iteration for resolving volumetric elastic collision. Our hybrid method uses implicit time stepping with a Lagrangian finite element discretization of the volumetric elastic material together with impulse-based collision-correcting momentum updates designed to exactly conserve linear and angular momentum. We use a two-step process for collisions: first we use a novel grid-based approach that leverages the favorable collision resolution properties of Particle-In-Cell (PIC) techniques, then we finalize with a classical collision impulse strategy utilizing continuous collision detection. Our PIC approach uses Affine-Particle-In-Cell momentum transfers as collision preventing impulses together with novel perfectly momentum conserving boundary resampling and downsampling operators that prevent artifacts in portions of the boundary where the grid resolution is of disparate resolution. We combine this with a momentum conserving augury iteration to remove numerical cohesion and model sliding friction. Our collision strategy has the same continuous collision detection as traditional approaches, however our hybrid particle/grid iteration drastically reduces the number of iterations required. Lastly, we develop a novel symmetric positive semi-definite Rayleigh damping model that increases the convexity of the nonlinear systems associated with implicit time stepping. We demonstrate the robustness and efficiency of our approach in a number of collision intensive examples.

The interactive medical simulation toolkit (iMSTK): an open source platform for surgical simulation

Introduction: Human error is one of the leading causes of medical error. It is estimated that human error leads to between 250,000 and 440,000 deaths each year. Medical simulation has been shown to improve the skills and confidence of clinicians and reduce medical errors. Surgical simulation is critical for training surgeons in complicated procedures and can be particularly effective in skill retention.Methods: The interactive Medical Simulation Toolkit (iMSTK) is an open source platform with position-based dynamics, continuous collision detection, smooth particle hydrodynamics, integrated haptics, and compatibility with Unity and Unreal, among others. iMSTK provides a wide range of real-time simulation capabilities with a flexible open-source license (Apache 2.0) that encourages adoption across the research and commercial simulation communities. iMSTK uses extended position-based dynamics and an established collision and constraint implementations to model biological tissues and their interactions with medical tools and other tissues.Results: The platform demonstrates performance, that is, compatible with real-time simulation that incorporates both visualization and haptics. iMSTK has been used in a variety of virtual simulations, including for laparoscopic hiatal hernia surgery, laparoscopic cholecystectomy, osteotomy procedures, and kidney biopsy procedures.Discussion: iMSTK currently supports building simulations for a wide range of surgical scenarios. Future work includes expanding Unity support to make it easier to use and improving the speed of the computation to allow for larger scenes and finer meshes for larger surgical procedures.

A Generalized Continuous Collision Detection Framework of Polynomial Trajectory for Mobile Robots in Cluttered Environments

In this letter, we introduce a generalized continuous collision detection (CCD) framework for the mobile robot along the polynomial trajectory in cluttered environments including various static obstacle models. Specifically, we find that the collision conditions between robots and obstacles could be transformed into a set of polynomial inequalities, whose roots can be efficiently solved by the proposed solver. In addition, we test different types of mobile robots with various kinematic and dynamic constraints in our generalized CCD framework and validate that it allows the provable collision checking and can compute the exact time of impact. Furthermore, we combine our architecture with the path planner in the navigation system. Benefiting from our CCD method, the mobile robot is able to work safely in some challenging scenarios.

Fast and Exact Root Parity for Continuous Collision Detection

AbstractWe introduce the first exact root parity counter for continuous collision detection (CCD). That is, our algorithm computes the parity (even or odd) of the number of roots of the cubic polynomial arising from a CCD query. We note that the parity is unable to differentiate between zero (no collisions) and the rare case of two roots (collisions).Our method does not have numerical parameters to tune, has a performance comparable to efficient approximate algorithms, and is exact. We test our approach on a large collection of synthetic tests and real simulations, and we demonstrate that it can be easily integrated into existing simulators.

Continuous collision detection with medial axis transform for rigid body simulation

Continuous collision detection with medial axis transform for rigid body simulation

Sum-of-squares geometry processing

Geometry processing presents a variety of difficult numerical problems, each seeming to require its own tailored solution. This breadth is largely due to the expansive list of geometric primitives , e.g., splines, triangles, and hexahedra, joined with an ever-expanding variety of objectives one might want to achieve with them. With the recent increase in attention toward higher-order surfaces , we can expect a variety of challenges porting existing solutions that work on triangle meshes to work on these more complex geometry types. In this paper, we present a framework for solving many core geometry processing problems on higher-order surfaces. We achieve this goal through sum-of-squares optimization, which transforms nonlinear polynomial optimization problems into sequences of convex problems whose complexity is captured by a single degree parameter. This allows us to solve a suite of problems on higher-order surfaces, such as continuous collision detection and closest point queries on curved patches, with only minor changes between formulations and geometries.

A Large-scale Benchmark and an Inclusion-based Algorithm for Continuous Collision Detection

We introduce a large-scale benchmark for continuous collision detection (CCD) algorithms, composed of queries manually constructed to highlight challenging degenerate cases and automatically generated using existing simulators to cover common cases. We use the benchmark to evaluate the accuracy, correctness, and efficiency of state-of-the-art continuous collision detection algorithms, both with and without minimal separation. We discover that, despite the widespread use of CCD algorithms, existing algorithms are (1) correct but impractically slow; (2) efficient but incorrect, introducing false negatives that will lead to interpenetration; or (3) correct but over conservative, reporting a large number of false positives that might lead to inaccuracies when integrated in a simulator. By combining the seminal interval root finding algorithm introduced by Snyder in 1992 with modern predicate design techniques, we propose a simple and efficient CCD algorithm. This algorithm is competitive with state-of-the-art methods in terms of runtime while conservatively reporting the time of impact and allowing explicit tradeoff between runtime efficiency and number of false positives reported.

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.

Codimensional incremental potential contact

We extend the incremental potential contact (IPC) model [Li et al. 2020a] for contacting elastodynamics to resolve systems composed of codimensional degrees-of-freedoms in arbitrary combination. This enables a unified, interpenetration-free, robust, and stable simulation framework that couples codimension-0,1,2, and 3 geometries seamlessly with frictional contact. Extending the IPC model to thin structures poses new challenges in computing strain, modeling thickness and determining collisions. To address these challenges we propose three corresponding contributions. First, we introduce a C 2 constitutive barrier model that directly enforces strain limiting as an energy potential while preserving rest state. This provides energetically-consistent strain limiting models (both isotropic and anisotropic) for cloth that enable strict satisfaction of strain-limit inequalities with direct coupling to both elastodynamics and contact via minimization of the incremental potential. Second, to capture the geometric thickness of codimensional domains we extend the IPC model to directly enforce distance offsets. Our treatment imposes a strict guarantee that mid-surfaces (respectively mid-lines) of shells (respectively rods) will not move closer than applied thickness values, even as these thicknesses become characteristically small. This enables us to account for thickness in the contact behavior of codimensional structures and so robustly capture challenging contacting geometries; a number of which, to our knowledge, have not been simulated before. Third, codimensional models, especially with modeled thickness, mandate strict accuracy requirements that pose a severe challenge to all existing continuous collision detection (CCD) methods. To address these limitations we develop a new, efficient, simple-to-implement additive CCD (ACCD) method that applies conservative advancement [Mirtich 1996; Zhang et al. 2006] to iteratively refine a lower bound for deforming primitives, converging to time of impact. In combination these contributions enable codimensional IPC (C-IPC). We perform extensive benchmark experiments to validate the efficacy of our method in capturing intricate behaviors of thin-structure contact and resulting bulk effects. In our experiments C-IPC obtains feasible, convergent, and so artifact-free solutions for all time steps, across all tested examples - producing robust simulations. We test C-IPC across extreme deformations, large time steps, and exceedingly close contact over all possible pairings of codimensional domains. Finally, with our strain-limit model, we confirm C-IPC guarantees non-intersection and strain-limit satisfaction for all reasonable (and well below - verified down to 0.1%) strain limits throughout all time steps.

Fluid-cloth coupling algorithm based on PBD and CCD

In order to simulate the interaction between cloth and fluid, we use Smooth Particle Hydrodynamics (SPH) as a method in fluid simulation, we propose a Continuous collision detection (CCD) and position-based dynamics (PBD) collision constrained iterative flow coupling method. By analyzing the parallelism of the algorithm, we implement a low storage and load balanced fluid and cloth coupling algorithm parallel computing is used to accelerate the simulation. The experimental results show that our method realizes the bidirectional coupling of fluid and cloth, and improves the simulation performance.

Continuous Collision Detection of Pairs of Robot Motions Under Velocity Uncertainty

In automotive manufacturing, production systems typically involve multiple robots and, today, are being individualized by utilizing the concept of digital twins. Therefore, the robot programs need to be verified for each individual product. A crucial aspect is to avoid collisions between robots by velocity tuning: This involves an efficient analysis of pairs of robot paths and determining if swept volumes of (sub) paths are disjoint. In general, velocity uncertain motions require disjoint sweep volumes to be safe. We optimize a clearance lower bounding function to provide new sample points for clearance computations. Due to the computational cost of each distance query, our sampling strategy aims to maximize the information gained at each query. The algorithm terminates when robot paths are verified to be disjoint or a collision is detected. Our approach for disjoint paths is inspired by the technique for continuous collision detection known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">conservative advancement</i> . Our tests indicate that the proposed sampling method is reliable and computationally much faster than creating and intersecting octrees representing the swept volumes.

P-cloth

We present a novel parallel algorithm for cloth simulation that exploits multiple GPUs for fast computation and the handling of very high resolution meshes. To accelerate implicit integration, we describe new parallel algorithms for sparse matrix-vector multiplication (SpMV) and for dynamic matrix assembly on a multi-GPU workstation. Our algorithms use a novel work queue generation scheme for a fat-tree GPU interconnect topology. Furthermore, we present a novel collision handling scheme that uses spatial hashing for discrete and continuous collision detection along with a non-linear impact zone solver. Our parallel schemes can distribute the computation and storage overhead among multiple GPUs and enable us to perform almost interactive simulation on complex cloth meshes, which can hardly be handled on a single GPU due to memory limitations. We have evaluated the performance with two multi-GPU workstations (with 4 and 8 GPUs, respectively) on cloth meshes with 0.5 -- 1.65 M triangles. Our approach can reliably handle the collisions and generate vivid wrinkles and folds at 2 -- 5 fps, which is significantly faster than prior cloth simulation systems. We observe almost linear speedups with respect to the number of GPUs.

Research on anchor chain visualization for a ship anchoring simulation training system.

In the development of ship anchorage training systems, the problems of low efficiency and poor fidelity exist in the simulation of flexible anchor chains, and a position-based dynamics (PBD) method is proposed to express the chain movement. To satisfy the requirements of simulating anchoring manipulation, the PBD method modifies the position of anchor chain particles by controlling constraints. Using the original distance constraint and bending constraint of the PBD approach, two novel constraints, namely, the long-range attachment (LRA) constraint and pin constraint, are developed to simulate the bending and stretching of the anchor chain. Simulation of ordinary ropes can be achieved using distance and bending constraints. The developed LRA constraint is capable of preventing anchor chain particles from being overstretched. Adoption of the pin constraint is proposed to integrate two particles into one to be calculated as an attempt to simulate the connection between the chain and the anchor. The continuous collision detection (CCD) constraint method considering friction and viscosity is used to detect collisions in the ship anchoring training system. Collision detection covers chain collisions with other objects and chains. Finally, the PBD method is more efficient and robust than the Newton method. Since it has sufficient visual plausibility and can realize real-time visualization, the simulation system developed by the PBD method effective for training crew members.

Fast Simulation of Cloth-Rigid Body Based on PBD

Because the excellent performance of the position-based dynamics (PBD) method, the PBD gains popularity among cloth simulation and computer animation. Based on unified adaptive PBD, we apply collision constraints to cloth and rigid body models to speed up the process of collision detection between cloth and complex models, we conduct a bounding box high-level collision culling detection algorithm. Moreover,friction is calculated by the speed of the cloth to make the cloth simulation more realistic. Compared with continuous collision detection (CCD), our method improves the simulation speed several times.The experimental results demonstrate that we has the wide range of applicability and the the simulation effect is stable.

Automatic re-planning of lifting paths for robotized tower cranes in dynamic BIM environments

Computer-Aided Lift Planning (CALP) systems provide smart and optimal solutions for automatic crane lifting, supported by intelligent decision-making and planning algorithms along with computer graphics and simulations. Re-planning collision-free optimal lifting paths in near real-time is an essential feature for a robotized crane operating in a construction environment that is changing with time. The primary focus of the present research work is to develop a re-planning module for the CALP system designed at Nanyang Technological University. The CALP system employs GPU-based parallelization approach for discrete and continuous collision detection as well as for path planning. Building Information Modeling (BIM) is utilized in the system, and a Single-level Depth Map (SDM) representation is implemented to reduce the huge data set of BIM models for usage in discrete and continuous collision detection. The proposed re-planning module constitutes of a Decision Support System (DSS) and a Path Re-planner (PRP). A novel re-planning decision making algorithm using multi-level Oriented Bounding Boxes (OBBs) is formulated for the DSS. A path re-planning strategy via updating the start configuration for the local path is devised for the PRP. Two case studies are carried out with real-world models of a building and a specific tower crane to validate the effective performance of the re-planning module. The results show excellent decision accuracy and near real-time re-planning with high optimality.

Continuous Collision Detection for Virtual Proxy Haptic Rendering of Deformable Triangular Mesh Models.

Most haptic systems suffer from what is known as the "tunneling" problem, which arises when a virtual object moves or deforms largely towards a small virtual tool. This problem occurs because the displacement of the virtual object is not considered during collision detection and can be solved with Continuous Collision Detection (CCD). Originally, haptic rendering with CCD was proposed for applications with 6 Degrees-of-Freedom (DoF) only. However, 3-DoF is simple to use in, and sufficient for, many applications. In this paper, we focus on CCD with a 3-DoF point-object haptic rendering of dynamic and deformable objects. Since we use the virtual proxy method, we propose a triangle-proxy CCD approach with a complementary process called Proxy Pop-Out to solve this problem. The results show that we are able to solve the "tunneling" problem, even for a small proxy against thin and deformable objects with large motions. In addition, we present probing haptic interactions with deformable objects in a multi-rate haptic rendering system. By using Oriented Particles and Position Based Dynamics, our system is efficient and stable.

An enhanced sweep and prune algorithm for multi-body continuous collision detection

Multi-body collision detection is a key and important technology in societies of computer graphics, system simulation, virtual reality, etc. and has been widely used in various graphics applications. To deal with the collision detection problem in large-scale multi-body scenes, we in this paper proposed a robust and efficient algorithm based on the kinetic “sweep and prune” technique and the event-driven mechanism. Our algorithm first culls redundant detection calculations in finding object pairs that do not collide in the scene with very large number of moving objects and then automatically generates events to predict the object collisions, which probably take place in near future. All the events are pushed into an optimized priority queue to drive the proposed algorithm. By introducing a hybrid bounding box hierarchy in the event processing process, the algorithm can detect the positions where the object pairs collide. Based on our finding that event blocking is an important factor affecting the robustness of the algorithm, we further propose several techniques to alarm blockings to be occurred or relieve the system from blocking state. Experimental results show that our algorithm has good stability and robustness, and it can improve the operating efficiency of multi-body continuous collision detections in an efficient way.