Collision Detection Algorithm Research Articles

Dynamics simulation-based packing of irregular 3D objects

The 3D packing problem has a wide range of applications. However, the complex geometry of irregular objects leads to a sharp increase in the number of placement combinations, making it a challenging problem. In this paper, we propose a packing pipeline based on rigid body dynamics simulation to deal with two types of 3D packing problems. One is the variant bin packing problem, which involves placing more objects into a container of given dimensions to maximize space utilization. The other is the open dimension problem, where the goal is to minimize the container that can accommodate all objects. We first use heuristic placement strategies and a fast collision detection algorithm to efficiently obtain initial packing results. Then, we simulate the shaking of the container according to the dynamic principle. Combined with the vacant space filling operation, shaking the container drives the movement of objects in the container to make the arrangement of objects more compact. For the open dimension packing, the container height is optimized by adjusting the constraints of simulation in the basic pipeline. Experimental results show that our method has advantages over existing methods in both speed and packing density.

Novel Probabilistic Collision Detection for Manipulator Motion Planning Using HNSW

Collision detection is very important for robot motion planning. The existing accurate collision detection algorithms regard the evaluation of each node as a discrete event, ignoring the correlation between nodes, resulting in low efficiency. In this paper, we propose a novel approach that transforms collision detection into a binary classification problem. In particular, the proposed method searches the k-nearest neighbor (KNN) of the new node and estimates its collision probability by the prior node. We perform the hierarchical navigable small world (HNSW) method to query the nearest neighbor data and store the detected nodes to build the database incrementally. In addition, this research develops a KNN query technique tailored for linear data, incorporating threshold segmentation to facilitate collision detection along continuous paths. Moreover, it refines the distance function of the collision classifier to enhance the precision of probability estimations. Simulation results demonstrate the effectiveness of the proposed method.

АНАЛІЗ АЛГОРИТМІВ ВИЯВЛЕННЯ ЗІТКНЕНЬ У ТРИВИМІРНИХ ВІРТУАЛЬНИХ СЕРЕДОВИЩАХ

The problem addressed in this paper concerns the real-time detection of collisions in virtual environments, which can consume a significant portion of computational re-sources, particularly in complex simulations with numerous objects. Ensuring a minimum frame rate of 30 FPS is crucial for user-friendly simulations. The focus is on the narrow phase of collision detection, where objects in close proximity are examined for potential collisions. This paper proposes a collision detection algorithm leveraging Directed Bounding Parallels (AABB) R-tree structure and Oriented Bounding Parallelepiped Inter-section (OAABB) method to address this phase efficiently. Experimental results demon-strate the effectiveness of the algorithm in detecting intersections with high interaction rates. Various publicly available toolkits exist for narrow phase collision detection, em-ploying different bounding volume hierarchies and constraint volumes. Comparing these approaches is challenging due to performance variations influenced by factors such as object shapes, contact types, and model sizes. Nonetheless, these algorithms are crucial for accurately detecting collisions in virtual environments and gaming applications. Bounding Volume Hierarchies (BVH), commonly used for collision detection, organ-ize object geometry and improve performance by reducing test pair numbers through vol-ume constraints. The proposed algorithm utilizes R-tree hierarchies of directed bounding parallelepipeds and OAABB to enhance collision detection efficiency by minimizing up-date and intersect operations. The choice of constraint volume type impacts collision de-tection performance, with oriented parallelepipeds offering faster intersections. To expedite collision detection, each feature is represented by an R-tree data struc-ture in its local coordinate system. Hierarchical trees are constructed by grouping adja-cent surfaces, with leaves indicating surface geometry. Additionally, R-trees are em-ployed to spatially organize triangles within surfaces to quickly discard non-intersecting triangles. The algorithm leverages OAABB, a concept involving the common volume between two oriented bounding parallelepipeds, to filter out primitives that cannot intersect. Tra-versal algorithms are utilized to reduce the number of node visits, addressing inefficien-cies observed in traditional schemes. OAABB contributes significantly to reducing volume refresh operations. Experimental evaluations demonstrate the proposed algorithm's efficacy in real-world industrial applications, achieving interactive performance. Comparisons with al-ternative methods highlight the algorithm's effectiveness in collision detection. Overall, the proposed approach offers a robust solution to the narrow phase collision detection problem in virtual environments.

A novel collision detection method based on current residuals for robots without joint torque sensors: A case study on UR10 robot

Existing model-based collision detection methods rely on accurate torque dynamic parameters identified using measured joint torques. However, for robots lacking joint torque sensors, only joint currents can be measured, and joint torques must be estimated through the linear relationship between joint currents and joint torque constants. This way can lead to cumulative identification errors in torque dynamic parameters, thereby diminishing the performance of model-based collision detection algorithms. To tackle this challenge, this article proposes an innovative collision detection method based on current residuals, which represent the disparities between measured joint currents and predicted joint currents computed by current dynamic parameters. Then, a dynamic threshold method for current residuals is designed to mitigate the impact of modeling errors at zero-speed direction changes on collision detection performance. Additionally, a suppression strategy based on online load identification and compensation is introduced to reduce the interference of non-collision load factors on collision detection signals. The proposed method mitigates the accumulation of errors on torque dynamic identification resulting from inaccuracies in joint torque constants, ultimately enhancing collision detection performance for robots without joint torque sensors. Extensive experiment results validate the correctness and effectiveness of this approach.

A Novel Method for Obtaining Analytical Parameters Based on Double-Flank Measurement.

Double-flank measurement is the most commonly used method for full inspection of mass-produced gears and has high measurement efficiency, but it cannot obtain the analytical parameters and is not helpful enough to evaluate the NVH performance of the gears. Based on the double-flank rolling tester with a new principle, a simulation method for double-flank measurement and a solving method for analytical parameters are proposed. Using the simulation method, the double-flank measurements without random error can be obtained through the collision detection algorithm. The solving method uses the iteration to obtain the minimum rolling length of each position of the tooth surface, then obtains the analytical parameters of the gear. In the experiments, the difference between the profile deviations obtained by the solving method and superimposed in the simulation method is less than 0.03 μm. The experiment results have verified the correctness of the simulation method and the solving method. These methods can greatly improve the value of double-flank measurement.

Adaptive collision detection algorithm design for six-axis industrial manipulator with accurate payload estimation

Adaptive collision detection algorithm design for six-axis industrial manipulator with accurate payload estimation

Experimental research based on robot-assisted surgery: Lower limb fracture reduction surgery planning navigation system.

Lower extremity fracture reduction surgery is a key step in the treatment of lower extremity fractures. How to ensure high precision of fracture reduction while reducing secondary trauma during reduction is a difficult problem in current surgery. First, segmentation and three-dimensional reconstruction are performed based on fracture computed tomography images. A cross-sectional point cloud extraction algorithm based on the normal filtering of the long axis of the bone is designed to obtain the cross-sectional point clouds of the distal bone and the proximal bone, and the optimal reset target pose of the broken bone is obtained by using the iterative closest point algorithm. Then, the optimal reset sequence of reset parameters was determined, combined with the broken bone collision detection algorithm, a surgical planning algorithm for lower limb fracture reset was proposed, which can effectively reduce the reset force while ensuring the accuracy of the reset process without collision. The average error of the reduction of the model bone was within 1.0 mm. The reduction operation using the planning and navigation system of lower extremity fracture reduction surgery can effectively reduce the reduction force. At the same time, it can better ensure the smooth change of the reduction force. Planning and navigation system of lower extremity fracture reduction surgery is feasible and effective.

Use of patellofemoral digital twins for patellar tracking and treatment prediction: comparison of 3D models and contact detection algorithms.

Introduction: Poor patellar tracking can result in painful contact pressures, patella subluxation, or dislocation. The use of musculoskeletal models and simulations in orthopedic surgeries allows for objective predictions of post-treatment function, empowering clinicians to explore diverse treatment options for patients. Although a promising approach for managing knee surgeries, the high computational cost of the Finite Element Method hampers its clinical usability. In anticipation of minimal elastic deformations in the involved bodies, the exploration of the Multibody Dynamics approach emerged as a viable solution, providing a computationally efficient methodology to address clinical concerns related to the knee joint. Methods: This work, with a focus on high-performance computing, achieved the simulation of the patellofemoral joint through rigid-body multibody dynamics formulations. A comparison was made between two collision detection algorithms employed in the simulation of contact between the patellar and femoral implants: a generic mesh-to-mesh collision detection algorithm, which identifies potential collisions between bodies by checking for proximity or overlap between their discretized mesh surface elements, and an analytical contact algorithm, which uses a mathematical model to provide closed-form solutions for specific contact problems, but cannot handle arbitrary geometries. In addition, different digital twins (3D model geometries) of the femoral implant were compared. Results: Computational efficiency was considered, and histories of position, orientation, and contact force of the patella during the motion were compared with experimental measurements obtained from a sensorized 3D-printed test bench under pathological and treatment scenarios. The best results were achieved through a purely analytical contact detection algorithm, allowing for clinical usability and optimization of clinical outcomes.

Rancang Bangun Game 3D Edukasi Basic Web Development Menggunakan Unity 3D

The development of games is a media that is favored by the public which can have good or bad effects, where a game is basically made as for entertainment but there are also those who use games as educational media. This research was conducted to create a basic web development educational game packaged in the form of RPG (Role Playing Games) games with the result that providing basic web development education that can be played by all audience, where learning about web development is currently quite popular with some people. The game system design process is made using UML diagrams which will be applied to the unity 3D application and the assessment obtained through a questionnaire of 82% of respondents agreed that this game can be provide basic web development education. This game is also implemented using a finite state machine algorithm that controls enemy behavior in each state and collision detection for interaction with other objects. In this process create several interface designs and also for the finite state machine algorithm implemented to the enemy animator to control the state of enemy behavior, and the collision detection algorithm is applied to areas that have a collider to display the interface and also play background music.

Impact of algorithmic and data structure implementation to game development

Many game developers tend to build their proprietary game engines with various algorithmic and data structure implementations. This work discusses a game made using the Pygame library that utilizes a maze generation algorithm, collision detection algorithm, and 2d shadow drawing algorithm to analyze how programming implementation could impact the game's representation, optimization, and future development. In this paper, various algorithms and data structures are compared based on their characteristic and performance, which leads to an analysis of how the game would differ from its current state if alternative implementations are used. It also addresses the issues raised by algorithms and data structures based on their interdependence relationship.

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.

Construction and transformation method of 3D models based on the chain-type modular structure

This study proposes a method of constructing and transforming three-dimensional (3D) models that can convert a 3D model into a chain-type modular configuration and realize the mutual transformation between different configurations with a straight chain as the intermediate state through standard folding steps. A method for detailed representation of voxels is proposed. Based on detailed voxels, an accelerated generation algorithm for the connection forest, which can describe the possible chain configurations, is developed. The foldability verification of the configurations and the generation of the folding operations are realized according to the folding rules. A collision detection algorithm based on encoding and projection is also introduced to detect collisions in the process of folding sequence generation. In this work, an interactive platform is established for users to calculate the input model transformation through simple operations and obtain a simulation animation of the folding operations. The experimental cases prove the effectiveness of the method in constructing and transforming the chain-type modular configurations of the input 3D models.

Obstacle avoidance decision and trajectory tracking control of intelligent vehicle considering surrounding vehicles

To enhance the obstacle avoidance performance and trajectory tracking control stability of vehicles in emergency scenarios, and to solve the problem that the existing decision-making methods based on the minimum safe distance model cannot effectively make decisions in some scenarios, a novel lane-changing obstacle avoidance decision-making and control method is proposed. Initially, when emergency braking cannot avoid obstacles safely, the lane-changing trajectory is planned by quintic polynomial, and the minimum distance and collision detection (MDCD) algorithm is then employed to ascertain whether the lane-changing trajectory meets the safety conditions. Subsequently, a Linear Time-Varying Model Predictive Control (LTV MPC) trajectory tracking controller is designed based on the 7-DOF vehicle dynamics model. Finally, the effectiveness of the proposed method is verified through two representative scenarios. The simulation results indicate that the MDCD algorithm can ensure the safety and effectiveness of obstacle avoidance decisions in all emergency obstacle avoidance scenarios, and when tracking the emergency lane-changing trajectory in different typical scenarios, compared with the LTV MPC controller based on the single-track vehicle dynamics model (STVDM), the maximum tracking error can be reduced by 50.7% and 60.1%, respectively, while ensuring near-equivalent real-time performance operation.

Optimization of Digital Inheritance of Meishan Folk Woodcarving Skills in the Information Age

Abstract This study delves into the digital preservation of Meishan folk woodcarvings, emphasizing the use of virtual reality (VR) technology to enhance the transmission of this traditional art. Utilizing 3D modeling and VR platforms, the research scans and rebuilds wooden carvings for digital exhibition. The realism and interactivity of the virtual environment are improved through collision detection algorithms such as Orientation Bracketing Box (OBB) and Axial Bracketing Box (AABB), complemented by high-precision 3D models created with LIDAR scanning technology. Findings indicate that the VR system significantly enhances the efficiency and quality of digital preservation, offering a robust solution for safeguarding Meishan folk woodcarvings.

Interior Space Design and Modelling Methods for Smart Homes - Integrating BIM and VR Technologies

Abstract In this study, the integration of Building Information Modeling (BIM) and Virtual Reality (VR) technologies with performance analysis software facilitates the selection of optimal indoor space layouts for settlement buildings. This is achieved through the use of information modeling and visualization tools to assess various aspects such as sunlight exposure, lighting conditions, architectural parameters, and energy consumption across different building layouts. A virtual environment was created using BIM and VR, within which the collision detection algorithm was refined using a chime-playing test scenario to enhance the quality control of 3D models. At 5000 triangular slices, the detection algorithm optimized in this study demonstrated a real-time performance that is 19 milliseconds faster than that of the comparative algorithm. Furthermore, in scenarios involving micro-speed air exchange, an open window area of 30 square meters facilitated an air volume of 250,168, indicating both economic and practical benefits. The overall satisfaction with interior design and spatial arrangement achieved through BIM and VR integration consistently exceeds 80%, underscoring the synergistic potential and future-oriented trajectory of combining these technologies.

A Collision Detection Algorithm Based on Sphere and EBB Mixed Hierarchical Bounding Boxes

A Collision Detection Algorithm Based on Sphere and EBB Mixed Hierarchical Bounding Boxes

Review of Mesoscale Geometric Models of Concrete Materials

Concrete can be regarded as a composite material comprising aggregates, cement mortar, and an interfacial transition zone (ITZ) at the mesoscale. The mechanical properties and durability of concrete are influenced by the properties of these three phases. The establishment of a mesoscale model of concrete and the execution of numerical simulations constitute an efficacious research method. It is an efficacious method to research concrete by establishing the mesoscale model of concrete and executing numerical simulations. By this method, the influence of an aggregate shape on concrete performance can be studied. This paper presents a systematic review of mesoscale modeling methods for concrete, with a focus on three aspects: the aggregate modeling method, the collision detection algorithm, and the particle-packing algorithm. The principal processes, advantages, and disadvantages of various methods are discussed for each aspect. The paper concludes by highlighting current challenges in the mesoscale modeling of concrete.

Developing a Method to Automatically Extract Road Boundary and Linear Road Markings from a Mobile Mapping System Point Cloud Using Oriented Bounding Box Collision-Detection Techniques

Advancements in data-acquisition technology have led to the increasing demand for high-precision road data for autonomous driving. Specifically, road boundaries and linear road markings, like edge and lane markings, provide fundamental guidance for various applications. Unfortunately, their extraction usually requires labor-intensive manual work, and the automatic extraction, which can be applied universally for diverse curved road types, presents a challenge. Given this context, this study proposes a method to automatically extract road boundaries and linear road markings by applying an oriented bounding box (OBB) collision-detection algorithm. The OBBs are generated from a reference line using the point cloud data’s position and intensity values. By applying the OBB collision-detection algorithm, road boundaries and linear road markings can be extracted efficiently and accurately in straight and curved roads by adjusting search length and width to detect OBB collision. This study assesses horizontal position accuracy using automatically extracted and manually digitized data to verify this method. The resulting RMSE for extracted road boundaries is +4.8 cm and +5.3 cm for linear road markings, indicating that high-accuracy road boundary and road marking extraction was possible. Therefore, our results demonstrate that the automatic extraction adjusting OBB detection parameters and integrating the OBB collision-detection algorithm enables efficient and precise extraction of road boundaries and linear road markings in various curving types of roads. Finally, this enhances its practicality and simplifies the implementation of the extraction process.

Development of UTM Monitoring System Based on Network Remote ID with Inverted Teardrop Detection Algorithm

The new regulation of Remote Identification (Remote ID) established by the FAA is predicted which will stimulate the application of Remote ID in UAS traffic management (UTM). Our research is aimed at the development of a UTM monitoring system based on the network Remote ID and the implementation of a new collision detection algorithm based on an inverted teardrop shape area and dynamic detection size. The newly introduced detection shape area in the UTM system could improve flight safety, increase airspace traffic, and provide a clear depiction of UAVs’ movement direction. The monitoring system consists of Remote ID hardware, a cloud database, and a web-based UTM application that runs on a personal laptop computer. A flight test was conducted involving a human pilot flying a quadcopter UAV to analyze the performance of the system and algorithm. The result found that the developed UTM monitoring system produces a reasonable average delay of around 0.94[Formula: see text]s with a standard deviation of 0.2[Formula: see text]s. The new detection algorithm shows a promising result that produces a larger buffer distance between UAVs compared to the circle shape algorithms.

Expanding an Education-based Collision Detection System Created on Virtual Reality and Augmented Reality

Virtually enhancing the real environment with augmented reality (AR) has lots of potential but is still in the early stages of research. The definition of appropriate user interfaces (UIs) is complicated by the absence of standards and the growing complexity of interaction opportunities. Several educators have discussed the advantages of XR for students as well as the use of AR and VR in the laboratory. Utilizing AR and VR to create immersive learning experiences is challenging since it takes time and effort to construct instructional AR and VR tools, apps, or educational settings. Because of this, even though these new technologies are said to help today’s students, their implementation in education may be postponed or stopped. In this research, the usage of XR technologies in education has been investigated through the examination of websites, technical papers, reports, and mobile app stores. This research study proposes a collision detection algorithm (CDA) utilizing machine learning. In order to aid in the identification of the meeting of two objects in the virtual environment, the collision detection method is employed in applications that support augmented reality and simulated reality technologies. In this study, mean, standard deviation and error parameters were utilized to analyze competitions that were related to augmented reality and virtual reality.