Collision Detection Method Research Articles

Simulation of the human TMJ behavior based on interdependent joints topology

The temporomandibular joint (TMJ) is one of the most important and complex joints of the body and its pathologies affect a great percentage of the human population. The simulation of the TMJ behavior during opening, closing and chewing movements can be very useful to the understanding of this articulation by physicians, helping them to prevent or fix problems due to accidents or diseases. This work proposes a model to simulate the human TMJ behavior based on the concept of two interdependent joints. The model was conceived using multimodal information acquired from CT and MRI images of a live person, as well as motion data acquired from this same person with a magnetic motion capture device. Simulation of movement of other TMJs, based on different morphology of bones and teeth, is obtained by adapting the regular captured motion data through collision detection and treatment methods. The proposed model was evaluated through image registration techniques by comparing our simulated results with real, captured motion data. We also validate the model showing how it can be used to predict TMJ behavior in the presence of different – normal or abnormal – bones and teeth morphologies.

A Hierarchical Grid Based Framework for Fast Collision Detection

AbstractWe present a novel hierarchical grid based method for fast collision detection (CD) for deformable models on GPU architecture. A two‐level grid is employed to accommodate the non‐uniform distribution of practical scene geometry. A bottom‐to‐top method is implemented to assign the triangles into the hierarchical grid without any iteration while a deferred scheme is introduced to efficiently update the data structure. To address the issue of load balancing, which greatly influences the performance in SIMD parallelism, a propagation scheme which utilizes a parallel scan and a segmented scan is presented, distributing workloads evenly across all concurrent threads. The proposed method supports both discrete collision detection (DCD) and continuous collision detection (CCD) with self‐collision. Some typical benchmarks are tested to verify the effectiveness of our method. The results highlight our speedups over prior algorithms on different commodity GPUs.

Collision detection based on topology hierarchy graph

To improve real-time and accurate performance of collision detection in virtual environment,a collision detection method based on topology hierarchy graph was proposed.Firstly,the original model was separated into convex set using the relationship of topology,and combining the merit of convex set and Oriented Bounding Box(OBB),a topology hierarchy graph for model was constructed,which effectively eliminated non-intersected bounding box and enhanced detection accuracy.By using intelligent search algorithm-improved A* algorithm to search for Potential Collision Sets(PCS),thus the speed and accuracy of collision detection were improved.The experimental results show that the algorithm has higher accuracy and efficiency for real-time collision detection in virtual environment.

Current based compliance control method for minimizing an impact force at collision of service robot arm

A motion of a robot manipulator under environment for human and robot to coexist should be able to quickly sense external force and react for minimizing a damage due to physical contacts. In the absence of sensing external force, relative motions between robot and human are not predictable and unexpected collisions may occur at some position during motion of the robot arm. This paper proposes a real-time collision detection method and a compliance control based on detecting abnormal current value to minimize an impact force at the moment of collision between service robot arm and unknown obstacle. In the introduced method, the extra sensors such as the Force/Toque sensor or the visual sensor to detect the collision are not necessary. Instead of these sensors, the collision detection and the safety motion are achieved by a simple method based on the current characteristics in according to operating of each joint motor of robot manipulator. In order to evaluate the performance for minimizing an impact force, the proposed method is applied to the developed light weight robot arm for a service robot.

修正深度剥離を用いた高速衝突判定手法

We propose a fast collision detection method that uses graphics hardware and includes self-collision and self-collision and deformable objects as its targets. The method uses a layered depth image (LDI), which is generated by depth peeling, and transform feedback. We modify the depth peeling method so that it can peel object surfaces exactly and uses LDI representations for fast collision detection. In addition, transform feedback makes the collision detection process very fast since there is no need to read back from the GPU to the CPU. The proposed method was implemented in a PC having an NVIDIA GeForce 9800 GT graphics card and applied to two objects consisting of 10,000 triangles in total at an image-space resolution of 400 × 400 pixels. As a result, the collision detection time was about 24 ms with 96% detection.

A virtual environment for complex products collaborative assembly operation simulation

As complex products such as automobiles and ships are usually developed at geographically dispersed locations, it brings the difficulty for component model verification and assembly process evaluation. To cope with this challenge, a relatively comprehensive system scheme which supports complex product real-time collaborative interactive assembly is proposed. To get high performance, the technologies such as parallel rendering for complex scene based on pc-cluster, high-efficient collision detection method, the mechanism of event synchronization based on HLA/RTI (High level Architecture/Run-time Infrastructure) are applied. A prototype system named Distributed Parallel Virtual Assembly Environment (DPVAE) is developed. With DPVAE, users at different location can do assembly operation collaboratively by hand or by tool, to conduct the component model verification and assembly process evaluation at the same time. Through a case study of RA750 car assembly, the validity of system functions has been demonstrated successfully.

Accelerating Pollard’s Rho Algorithm on Finite Fields

Most generic and memory-efficient algorithms for solving the discrete logarithm problem construct a certain random graph consisting of group element nodes and return the solution when a collision is found among the graph nodes. In this work, we develop a technique for traveling through the random graph without fully computing each node and also provide an extension to the distinguished point collision detection method that is suitable for this new situation. Concrete constructions of this technique for multiplicative subgroups of the finite fields are given. Our implementations confirm that the proposed technique provides practical speedup over existing algorithms.

Collision detection and response method for markerless camera-based games using motion boundary estimation

Markerless camera-based games are more immersive and compelling than other types of games. However, it is difficult to select the proper methods for body segmentation and motion detection, because they should be fast processed for real-time responses. Therefore, collision detection and response between virtual objects (VOs) and human bodies are estimated using collision regions. In this paper, we propose a novel collision detection and response method capable of overcoming many disadvantages of previous markerless games. The proposed method is based on frame difference processing, and estimates motion boundaries (MBs); therefore, the method is fast processed. The MBs, which consist of vertices having motion vectors (MVs), are valid boundaries that can detect collisions with VOs. To estimate MVs and MBs, fast polygonal approximation and vertex matching are applied. Thus, MBs can be fast estimated, collisions can be correctly detected, and VOs respond to moving bodies instead of collision regions. The experimental results of the collision detection and response between human and VOs show that the proposed method properly estimates MBs and guarantees precise collision responses. Therefore, the proposed method can be used in camera-based games requiring high performance.

SU‐GG‐T‐532: A Method for Dose Calculation and Collision Detection in Gamma Plan Pre‐Planning Mode

Purpose: The latest version of the Gamma Plan treatment planning system allows for treatment “pre‐planning” using an image set with no headframe. However, in pre‐planning mode the user is not able to define the Gamma Knife coordinate system, so collision checks and dose time calculations cannot be performed. This restriction is particularly limiting when pre‐planning head and neck cases or cases for lesions located in the posterior fossa. We have developed a simple method to establish the Gamma Knife coordinate system and to therefore run collision checks and dose time calculations. Method and Materials: An image set of the Gamma Knife headframe and fiducial box is imported into Gamma Plan and opened in treatment mode. An MR or CT patient image set without a headframe is imported into the same treatment planning window. The two image sets are then co‐registered and fused. The resulting composite images may then be used to plan a treatment with the full Gamma Plan functionality, including collision monitoring and dose time calculations. Results: The headframe image set was successfully co‐registered and fused to patient image sets and used for treatment planning. The fused image set was then able to be checked for collisions and dose delivery times were able to be calculated. Conclusion: We have developed a simple method that allows for the Gamma Knife coordinate system to be established in Gamma Plan pre‐planning mode. This technique lets the user check for collisions and calculate dose times prior to headframe placement. It also may serve as an aid for determination of headframe placement on treatment day. The main limitation of this method is that it does not allow for gamma angles not equal to 90. Supported in part by NCI T‐32 CA113267.

Dynamic Collision Detection with Optimum Discrete Interval

An improved algorithm, dynamic collision detection with optimum discrete interval is presented to improve the efficiency of dynamic collision detection. The algorithm based on the minimum distance between two objects with relative movement to determine the next discrete position, on which collision or interference is free. The method using the minimum distance as discrete interval to determine the next interference-free position makes each interval longest under the constraint of safety so that the reliability between the moving object-pair is ensured while the efficiency is improved. The practical demonstration has proved that the improved algorithm is capable of high performance than that of the collision detection method with even discrete interval. This algorithm has been successfully used in a verification system of inspection process by secondary development of Pro/Engineer.

Dynamic clothing collision resolution using PSO

This paper presents a novel stochastic method for dynamic clothing simulation and collision detection by using a Particle Swarm Optimisation (PSO) algorithm. Firstly, we convert the collision detection problem to a multi-objective dynamic environment optimisation problem. Then, we use a density-based clustering PSO to find optimal or near-optimal solutions. During the searching process, we also put forward a restrictive fly algorithm to prevent particles from flying out of the solution space. Experimental results demonstrate that PSO has good performances in our optimisation problem. Besides, with active pair searching and Bounding Volume Hierarchies (BVHs), our method can achieve high detection ratio and balanced performances at interactive rates.

Proximity queries using separating bounding volumes

This paper presents a fast method for collision detection and proximity queries for 3D models using Separating Bounding Volumes (SBVs). In order to achieve real-time performance for complex, non-convex models, we propose an algorithm to speed-up the computation of SBVs by using the support vector machines and a robust scheme to conduct penetration search under the framework of SBVs. The SBVs-based proximity queries require no specific knowledge of the object's geometry or topology. The examples indicate that this method, the meaningful local penetration information can be computed for complex models within a few milliseconds.

Prism-based Mesh Culling Method for Effective Continuous Collision Detection

Prism-based Mesh Culling Method for Effective Continuous Collision Detection

HPCCD: Hybrid Parallel Continuous Collision Detection using CPUs and GPUs

AbstractWe present a novel, hybrid parallel continuous collision detection (HPCCD) method that exploits the availability of multi‐core CPU and GPU architectures. HPCCD is based on a bounding volume hierarchy (BVH) and selectively performs lazy reconstructions. Our method works with a wide variety of deforming models and supports self‐collision detection. HPCCD takes advantage of hybrid multi‐core architectures – using the general‐purpose CPUs to perform the BVH traversal and culling while GPUs are used to perform elementary tests that reduce to solving cubic equations. We propose a novel task decomposition method that leads to a lock‐free parallel algorithm in the main loop of our BVH‐based collision detection to create a highly scalable algorithm. By exploiting the availability of hybrid, multi‐core CPU and GPU architectures, our proposed method achieves more than an order of magnitude improvement in performance using four CPU‐cores and two GPUs, compared to using a single CPU‐core. This improvement results in an interactive performance, up to 148 fps, for various deforming benchmarks consisting of tens or hundreds of thousand triangles.

Shape from silhouette using topology-adaptive mesh deformation

We present a computationally efficient and robust shape from silhouette method based on topology-adaptive mesh deformation, which can produce accurate, smooth, and topologically consistent 3D mesh models of complex real objects. The deformation scheme is based on the conventional snake model coupled with local mesh transform operations that control the resolution and uniformity of the deformable mesh. Based on minimum and maximum edge length constraints imposed on the mesh, we describe a fast collision detection method which is crucial for computational efficiency of the reconstruction process. The topology of the deformable mesh, which is initially zero genus, can be modified whenever necessary by merging operations in a controlled and robust manner by exploiting the topology information available in the silhouette images. The performance of the proposed shape from silhouette technique is demonstrated on several real objects.

A rapid path planner for autonomous ground vehicle using section collision detection

Rapid path planner plays an important role in autonomous ground vehicle (AGV) operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree (RRT) can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and efficient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 m×170 m area with moderate obstacle complexity.

Adequate motion simulation and collision detection for soccer playing humanoid robots

In this paper a humanoid robot simulator based on the multi-robot simulation framework ( MuRoSimF) is presented. Among the unique features of this simulator is the scalability in the level of physical detail in both the robot’s motion and sensing systems. It facilitates the development of control software for humanoid robots which is demonstrated for several scenarios from the RoboCup Humanoid Robot League. Different requirements exist for a humanoid robot simulator. E.g., testing of algorithms for motion control and postural stability require high fidelity of physical motion properties whereas testing of behavior control and role distribution for a robot team requires only a moderate level of detail for real-time simulation of multiple robots. To meet such very different requirements often different simulators are used which makes it necessary to model a robot multiple times and to integrate different simulations with high-level robot control software. MuRoSimF provides the capability of exchanging the simulation algorithms used for each robot transparently, thus allowing a trade-off between computational performance and fidelity of the simulation. It is therefore possible to choose different simulation algorithms which are adequate for the needs of a given simulation experiment, for example, motion simulation of humanoid robots based on kinematical, simplified dynamics or full multi-body system dynamics algorithms. In this paper also the sensor simulation capabilities of MuRoSimF are revised. The methods for motion simulation and collision detection and handling are presented in detail including an algorithm which allows the real-time simulation of the full dynamics of a 21 DOF humanoid robot. Merits and drawbacks of the different algorithms are discussed in the light of different simulation purposes. The simulator performance is measured and illustrated in various examples, including comparison with experiments of a physical humanoid robot.

Collision detection strategies for virtual construction simulation

This research aims at developing a simple and efficient collision detection method to support the rendering of a virtual construction scenario in real time. To expedite the collision detection algorithm, we approximated construction machineries and structural elements on a construction site by using spheres and cylinders. By modeling the objects using outer boundaries, the computational cost for collision detection can be significantly reduced. Using the outer boundary also provides the benefit of ensuring a conservative result (i.e. towards the safer side). VC-COLLIDE, the collision detection algorithm developed in this research, has also been presented. VC-COLLIDE has been implemented and tested by using three typical construction scenarios: small building scenarios (683 objects), large building scenarios (2143 objects) and tall building scenarios (2612 objects). The test results indicate that VC-COLLIDE can complete all the collision checks within 1/20th of a second, the upper bound of real-time refresh time in the three testing environments. We also compared VC-COLLIDE with the collision detection function in Open Dynamic Engine (ODE), a widely used physics engine for real-time visualization. Because VC-COLLIDE is designed specifically for using in a virtual construction scenario, its computational performance is significantly better than ODE.

Fast collision detection methods for joint surfaces

In the recent years medical diagnosis and surgery planning often require the precise evaluation of joint movements. This has led to exploit reconstructed three-dimensional models of the joint tissues obtained from CT or MR Images (for bones, cartilages, etc.). In such context, efficiently and precisely detecting collisions among the virtual tissues is critical for guaranteeing the quality of any further analysis. The common methods of collision detection are usually designed for general purpose applications in computer graphics or CAD–CAM. Hence they face worst case scenarios when handling the quasi-perfect concavity–convexity matching of the articular surfaces. In this paper, we present two fast collision detection methods that take advantage of the relative proximity and the nature of the movement to discard unnecessary calculations. The proposed approaches also accurately provide the penetration depths along two functional directions, without any approximation. They are compared with other collision detection methods and tested in different biomedical scenarios related to the human hip joint.

HAND MANIPULATION TRAINING IN HAPTIC VIRTUAL ENVIRONMENTS

Continuing advances in virtual reality (VR) technology with respect to the new addition of force and touch feedbacks have enhanced VR realism and led to the development of many useful and accessible VR systems. One of the emerging research fields is in rehabilitation training. This paper introduces a virtual reality-based hand manipulation training system with three applications: virtual writing, virtual painting and virtual dialing. The system is mainly for training hand movement precision, speed, force, and direction control. A haptic device — PHANTOM Premium 1.0 is used to give the user immediate force feedbacks to feel immersed in the virtual environment during the training session. A new collision detection method is developed for accurate and rapid calculation of the interaction between the haptic and virtual environments. The implementation performances are calculated and given to the user in real time. The practicing results are also saved for evaluation and supervision by the specialist.