Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.

A self-organization formation configuration based assignment probability and collision detection

The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.

Collision detection of virtual plant based on bounding volume hierarchy: A case study on virtual wheat

Visualization of simulated crop growth and development is of significant interest to crop research and production. This study aims to address the phenomenon of organs cross-drawing by developing a method of collision detection for improving vivid 3D visualizations of virtual wheat crops. First, the triangular data of leaves are generated with the tessellation of non-uniform rational B-splines surfaces. Second, the bounding volumes（BVs） and bounding volume hierarchies（BVHs） of leaves are constructed based on the leaf morphological characteristics and the collision detection of two leaves are performed using the Separating Axis Theorem. Third, the detecting effect of the above method is compared with the methods of traditional BVHs, Axis-Aligned Bounding Box（AABB） tree, and Oriented Bounding Box（OBB） tree. Finally, the BVs of other organs（ear, stem, and leaf sheath） in virtual wheat plant are constructed based on their geometric morphology, and the collision detections are conducted at the organ, individual and population scales. The results indicate that the collision detection method developed in this study can accurately detect collisions between organs, especially at the plant canopy level with high collision frequency. This collision detection-based virtual crop visualization method could reduce the phenomenon of organs cross-drawing effectively and enhance the reality of visualizations.

Using LBG quantization for particle-based collision detection algorithm

Most collision detection algorithms can be efficiently used only with solid and rigid objects, for instance, Hierarchical methods which must have their bounding representation recalculated every time deformation occurs. An alternative algorithm using particle-based method is then proposed which can detect the collision among non-rigid deformable polygonal models. However, the original particle-based collision detection algorithm might not be sufficient enough in some situations due to the improper particle dispersion. Therefore, this research presents an improved algorithm which provides a particle to detect in each separated area so that particles always covered all over the object. The surface partitioning can be efficiently performed by using LBG quantization since it can classify object vertices into several groups base on a number of factors as required. A particle is then assigned to move between vertices in a group by the attractive forces received from other particles on neighbouring objects. Collision is detected when the distance between a pair of corresponding particles becomes very small. Lastly, the proposed algo- rithm has been implemented to show that collision detection can be conducted in real-time.

A collision detection approach in virtual environment of micromanipulation robot

Operators suffer much diffieulty in manipulating miero-size objects without the assistance of friendly interfaces due to the scaling effects in micro worht. The paper presented a general framework for mieromanipulation robot hased on virtual reality technology. With the framework we brought forward a FDH （Fixed Direction Hulls） based hounding box method to handle the eollision ,teteetion of the peg-in-hole mieroassembly. The eollision response model for the collision between micro needle and hole was presented. The virtual three and corresponding displacement were calculated with the model of bending deformation and pressing ,teformation. Experiments verify the validity of collision response model.

Simulating unmanned aerial vehicle flight control and collision detection

An unmanned aerial vehicle(UAV)is a small,fast aircraft with many useful features.It is widely used in military reconnaissance,aerial photography,searches,and other fields;it also has very good practical-application and development prospects.Since the UAV’s flight orientation is easily changeable,its orientation and flight path are difficult to control,leading to its high damage rate.Therefore,UAV flight-control technology has become the focus of attention.This study focuses on simulating a UAV’s flight and orientation control,and detecting collisions between a UAV and objects in a complex virtual environment.The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment.A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper,to improve the system performance and accelerate the collision-detection process.This provides a practical method for future studies on UAV flight position and orientation control,collision detection,etc.

Collision-aware interactive simulation using graph neural networks

Deep simulations have gained widespread attention owing to their excellent acceleration performances.However,these methods cannot provide effective collision detection and response strategies.We propose a deep interac-tive physical simulation framework that can effectively address tool-object collisions.The framework can predict the dynamic information by considering the collision state.In particular,the graph neural network is chosen as the base model,and a collision-aware recursive regression module is introduced to update the network parameters recursively using interpenetration distances calculated from the vertex-face and edge-edge tests.Additionally,a novel self-supervised collision term is introduced to provide a more compact collision response.This study extensively evaluates the proposed method and shows that it effectively reduces interpenetration artifacts while ensuring high simulation efficiency.

CSMA/CN+: Improving the Performance of Collision Notification for Wireless LANs

In CSMA/CN, whenever inferring that a receiving frame gets corrupted, the receiver sends back its signature as a collision notification(CN) to the sender. Upon detecting an arrival of the CN, the sender will abort the ongoing transmission immediately. However, in low signal-to-interference-plus-noise ratio(SINR), the false alarm of the CN occurs frequently, which might force a sender not to transmit any frame at all. To overcome this drawback, this paper proposes CSMA/CN+ to enhance the performance of CSMA/CN. In CSMA/CN+, we introduce an additional signature. The receiver, adapting to channel conditions and self-signal suppression capability, prudently determines whether to send back zero, one, or two signatures to the sender. In this way, we can reduce or exclude false alarms and therefore improve the system performance. In this paper, we first present the design of CSMA/CN+. We then apply the design in a wireless LAN, and theoretically analyze the detection performance of the notification and the system throughput. Extensive simulations verify that CSMA/CN+ can remarkably improve the system throughput of CSMA/CN and our analysis is very accurate.

A Linear Algorithm for Collision Detection of 3-Dimensional Convex Polytopes

Given two disjoint 3-dimensional convex polytopes P and Q and a straight direction along Which P moves in translation, this paper presents a linear algorithm for determining Whether P collides with Q, and the possible collision positions on P and Q. This result is achieved by using the hierarchicat representation of polytopes, of which the preprocessing time is linear with space.

COLLISION DETECTION AMONG MOVING OBJECTSIN MACHINING PROCESS SIMULATION

This paper describes an algorithm of collision detection between moving objects in machin-ing process simulation. Graphical simulation of machining has been recognized to be useful for NCprogram verification , since the programmer of the machining operator can easily find some faults inthe NC program visually. But it is difficult to visually detect collisions arnong moving objects such ascutting tools , workpieces and fixtures, a data structure to represent moving objects and an algorithmof collision detection between moving objects are proposed. A moving object can be represented by ahierarchical sphere octree and its motion can be described by a quadratic function of time. A collisionoccurs in the case that the distance between any two sphere centers in the respective two moving ob-jects is equal to the sum of the radii of these two spheres, and the radii of these two spheres are lessthan a given precision. By solving the equations that satisfy the conditions of collision between thespheres recursively , we obtain the time and the position of the collision between these two moving ob-Jects.

Ultrasonic Sensor-Based Embedded System for Vehicular Collusion Detection and Alert

The efficacy of an automated collision detection system is contingent upon the caliber and volume of data at its disposal. In the event that the data is deficient, incongruous, or erroneous, it has the potential to generate erroneous positive or negative outcomes, thereby compromising the system’s credibility. The occurrence of false positives is observed when the system erroneously identifies genuine activity as collusion. The phenomenon of false negatives arises when the system is unable to identify instances of genuine collusion. Collusion detection systems are required to handle substantial volumes of data in real time, capable of analyzing relationships between different objects. The intricate nature of collusion can pose difficulties in devising and executing efficient systems for its detection. The present study proposes an automated anti-collision system that utilizes sensor devices to detect objects and activate an alert mechanism in the event that the vehicle approaches the object in close proximity. The study introduces a novel methodology for mitigating vehicular accidents by implementing a combined system that integrates collision detection and alert mechanisms. The proposed system comprises an ultrasonic sensor, a microprocessor, and an alarm system. The sensor transmits a signal to the microcontroller, which in turn sends a signal to the warning unit. The warning unit is designed to prevent potential accidents by emitting an audible warning signal through a buzzer. Additionally, the distance information is displayed on an LCD screen. The Proteus Design Suite is utilized for simulation purposes, while Arduino.cc is employed for implementation.

AN ALGORITHM OF DISTANCE CALCULATION BETWEEN A BOUNDING SPHERE AND A BOUNDING CSG PRIMITIVE

A simple method for calculating distance between a solid sphere and a constructive solid geometry (CSG) so lid primitive (including block, cone, cylinder, sphere, wedge and torus) is derived to support the collision detection algorithm. By decomposing the whole space into relative positions and geometric features of the sphere and the primitive considered, closed form distance formula are got. These calculations are very useful in the real time collision detection in which primitives are used as bounding volumes of complex objects.

Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

As computer graphics technology continues to advance,Collision Detection(CD)has emerged as a critical element in fields such as virtual reality,computer graphics,and interactive simulations.CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments,particularly within complex scenarios like virtual assembly,where both high precision and real-time responsiveness are imperative.Despite ongoing developments,current CD techniques often fall short in meeting these stringent requirements,resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems.To address these limitations,this study introduces a novel algorithm that leverages the capabilities of a Backpropagation Neural Network(BPNN)to optimize the structural composition of the Hybrid Bounding Volume Tree(HBVT).Through this optimization,the research proposes a refined Hybrid Hierarchical Bounding Box(HHBB)framework,which is specifically designed to enhance the computational efficiency and precision of CD processes.The HHBB framework strategically reduces the complexity of collision detection computations,thereby enabling more rapid and accurate responses to collision events.Extensive experimental validation within virtual assembly environments reveals that the proposed algorithm markedly improves the performance of CD,particularly in handling complex models.The optimized HBVT architecture not only accelerates the speed of collision detection but also significantly diminishes error rates,presenting a robust and scalable solution for real-time applications in intricate virtual systems.These findings suggest that the proposed approach offers a substantial advancement in CD technology,with broad implications for its application in virtual reality,computer graphics,and related fields.

CAD Model-Based Intelligent Inspection Planning for Coordinate Measuring Machines

As the market competition among enterprises grows intensively and the demand for high quality products increases rapidly, product quality inspection and control has become one of the most important issues of manufacturing, and improving the efficiency and accuracy of inspection is also one of problems which enterprises must solve. It is particularly important to establish rational inspection planning for parts before inspecting product quality correctly. The traditional inspection methods have been difficult to satisfy the requirements on the speed and accuracy of modern manufacturing, so CAD-based computer-aided inspection planning （CAIP） system with the coordinate measuring machines （CMM） came into being. In this paper, an algorithm for adaptive sampling and collision-free inspection path generation is proposed, aiming at the CAD model-based inspection planning for coordinate measuring machines （CMM）. Firstly, using the method of step adaptive subdivision and iteration , the sampling points for the specified number with even distribution will be generated automatically. Then, it generates the initial path by planning the inspection sequence of measurement points according to the values of each point＇s weight sum of parameters, and detects collision by constructing section lines between the probe swept-volume surfaces and the part surfaces, with axis-aligned bounding box （AABB） filtering to improve the detection efficiency. For collided path segments, it implements collision avoidance firstly aiming at the possible outer-circle features, and then at other collisions, for which the obstacle-avoiding movements are planned with the heuristic rules, and combined with a designed expanded AABB to set the obstacle-avoiding points. The computer experimental results show that the presented algorithm can plan sampling points＇ locations with strong adaptability for different complexity of general surfaces, and generate efficient optimum path in a short time and avoid collision effectively.

Computational Path Planner for Product Assembly in Complex Environments

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree （RRT） algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Integrated Virtual Assembly Process Planning System

Assembly process planning（APP） for complicated products is a time-consuming and difficult work with conventional method. Virtual assembly process planning（VAPP） provides engineers a new and efficiency way. Previous studies in VAPP are almost isolated and dispersive, and have not established a whole understanding and discussed key realization techniques of VAPP from a systemic and integrated view. The integrated virtual assembly process planning（IVAPP） system is a new virtual reality based engineering application, which offers engineers an efficient, intuitive, immersive and integrated method for assembly process planning in a virtual environment. Based on analysis the information integration requirement of VAPP, the architecture of IVAPP is proposed. Through the integrated structure, IVAPP system can realize information integration and workflow controlling. In order to mode/the assembly process in IVAPP, a hierarchical assembly task list（HATL） is presented, in which different assembly tasks for assembling different components are organized into a hierarchical list. A process-oriented automatic geometrical constraint recognition algorithm（AGCR） is proposed, so that geometrical constraints between components can be automatically recognized during the process of interactive assembling. At the same time, a progressive hierarchical reasoning（PHR） model is discussed. AGCR and PHR will greatly reduce the interactive workload. A discrete control node model（DCNM） for cable harness assembly planning in IVAPP is detailed. DCNM converts a cable harness into continuous flexed line segments connected by a series of section center points, and designs can realize cable harness planning through controlling those control nodes. Mechanical assemblies （such as transmission case and engine of automobile） are used to illustrate the feasibility of the proposed method and algorithms. The application of IVAPP system reveals advantages over the traditional assembly process planning method in shortening the time-consumed in assembly planning and in minimizing the handling difficulty, excessive reorientation and dissimilarity of assembly operations.

Motion Planning Method for Obstacle Avoidance of 6-DOF Manipulator Based on Improved A* Algorithm

The conventional A* algorithm may suffer from the infinite loop and a large number of search data in the process of motion planning for manipulator. To solve the problem,an improved A* algorithm is proposed in this paper by the means of selecting middle points and applying variable step segments searching during the searching process. In addition,a new method is proposed for collision detection in the workspace. In this paper,the MOTOMAN MH6 manipulator with 6-DOF is applied for motion plan. The algorithm is based on the basis of the simplification for the manipulator and obstacles by cylinder enveloping. Based on the analysis of collision detection,the free space can be achieved which makes it possible for the entire body to avoid collisions with obstacles. Compared with the Conventional A*,the improved algorithm deals with less searching points and performs more efficiently. The simulation developed in VC + + with OpenGL and the actual system experiments prove effectiveness and feasibility of this improved method.

Realization Techniques of Virtual Assembly Process Planning System

The key realization techniques of virtual assembly process planning （VAPP） system are analyzed, including virtual assembly model, real-time collision detection, automatic constraint recognition algorithm, cable harness assembly process planning and visual assembly process plan at the workshop. A virtual assembly model based on hierarchical assembly task list （HATL） is put forward, in which assembly tasks are defined to express component assembling operations and are sequentially and hierarchically organized according to different subassemblies, which can perfectly model the construction process of product, And a multi-layer automatic geometry constraint recognition algorithm of how to identify assmbly constraint relations in the virtual environment is proposed, then a four-layer collision detection algorithm is discussed. A VAPP system is built and some simple mechanical assemblies are used to illustrate the feasibility of the proposed method and algorithms.

Research on Clothing Simulation Design Based on Three-Dimensional Image Analysis

Traditional clothing design models based on adaptive meshes cannot reflect.To solve this problem,a clothing simulation design model based on 3D image analysis technology is established.The model uses feature extraction and description of image evaluation parameters,and establishes the mapping relationship between image features and simulation results by using the optimal parameter values,thereby obtaining a three-dimensional image simulation analysis environment.On the basis of this model,by obtaining the response results of clothing collision detection and the results of local adaptive processing of clothing meshes,the cutting form and actual cutting effect of clothing are determined to construct a design model.The simulation results show that compared with traditional clothing design models,clothing simulation design based on 3D image analysis technology has a better effect,with the definition of fabric folds increasing by 40%.More striking contrast between light and dark,the resolution increasing by 30%,and clothing details getting a more real manifestation.