Physical collision monitoring and feedback method, device and storage medium based on digital twin engine

Abstract

The present application discloses a physical collision monitoring and feedback method, device, and storage medium based on a digital twin engine, which relates to the field of data processing technology, including: performing preliminary collision detection on the model physical entity in the digital twin model based on the physical entity to be detected, and determining the preliminary collision object; traversing the mixed-level bounding box hierarchy tree of the preliminary collision object in the digital twin model, checking each node layer by layer whether it intersects with the bounding box of the physical entity to be detected, and determining the leaf nodes of the mixed-level bounding box hierarchy tree where the intersection occurs; for the leaf nodes that intersect with the bounding box of the physical entity to be detected, determining the collision detection result through geometric calculation and synchronizing it to the digital twin model in real time; and feeding back the collision detection result to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected. The present application achieves the technical effect of improving the immediacy of collision monitoring and feedback.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a physical collision monitoring and feedback method, device, and storage medium based on a digital twin engine. Background Art

[0002] Currently, in terms of collision monitoring and feedback of physical entities, traditional collision detection systems mainly rely on physical sensors to collect data in real time and combine them with algorithms for collision detection. However, due to the imperfect feedback mechanism of the current collision detection system, it is impossible to accurately feed back the collision detection results to the control system of the physical entity in real time, resulting in the control system being unable to respond to collision events in a timely manner.

[0003] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of this application is to provide a physical collision monitoring and feedback method, device and computer-readable storage medium based on a digital twin engine, aiming to solve the technical problem of how to improve the immediacy of physical collision monitoring and feedback.

[0005] To achieve the above objectives, this application proposes a physical collision monitoring and feedback method based on a digital twin engine. The physical collision monitoring and feedback method based on a digital twin engine includes:

[0006] Perform preliminary collision detection on the model physical entities in the digital twin model based on the physical entities to be detected, and determine the preliminary collision objects;

[0007] Traversing the mixed-level bounding box hierarchy tree of the preliminary collision object in the digital twin model, checking layer by layer whether each node intersects with the bounding box of the physical entity to be detected, and determining the leaf node of the mixed-level bounding box hierarchy tree where the intersection occurs;

[0008] For the leaf nodes that intersect with the bounding box of the physical entity to be detected, the collision detection result is determined by geometric calculation and synchronized to the digital twin model in real time;

[0009] Feedback the collision detection result to a control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected.

[0010] In one embodiment, the step of performing preliminary collision detection on the model physical entity in the digital twin model based on the physical entity to be detected and determining the preliminary collision object includes:

[0011] Using 3D modeling tools and physical simulation software, a digital twin model of the physical system where the model physical entity resides is constructed and integrated into a digital twin engine to simulate the overall operating state of the physical system;

[0012] The operating status data of the physical system is collected in real time, and the collected operating status data is transmitted to the digital twin model to ensure that the data in the digital twin model is synchronized with the operating status data in the physical system.

[0013] In one embodiment, before the step of traversing the hybrid hierarchical bounding box hierarchy tree of the preliminary collision object in the digital twin model, checking layer by layer whether each node intersects with the bounding box of the physical entity to be detected, and determining the leaf node of the hybrid hierarchical bounding box hierarchy tree where the intersection occurs, the method includes:

[0014] The hybrid hierarchical bounding box hierarchy tree is constructed according to the geometric characteristics of the physical entities of each model in the digital twin model.

[0015] In one embodiment, the step of constructing the hybrid hierarchical bounding box hierarchy tree according to the geometric characteristics of the physical entities of each model in the digital twin model includes:

[0016] Constructing the hybrid hierarchical bounding box hierarchy tree using a top-down approach, starting with the bounding box of the digital twin model as the root node of the hybrid hierarchical bounding box hierarchy tree;

[0017] Recursively divide the root node to form at least one child node, each of the child nodes representing a sub-area of the digital twin model;

[0018] According to the geometric characteristics of each physical entity in the sub-region, selecting a corresponding bounding box type to construct a bounding box for the sub-region corresponding to each child node;

[0019] If the complexity of the child node reaches a preset complexity threshold, it is determined that the construction of the hybrid hierarchical bounding box hierarchy tree is completed.

[0020] In one embodiment, the step of constructing the hybrid hierarchical bounding box hierarchy tree according to the geometric characteristics of the physical entities of each model in the digital twin model further includes:

[0021] A bounding box hierarchy tree is constructed using a bottom-up approach, starting from the basic geometric elements of the digital twin model, and constructing a bounding box for each of the basic geometric elements as a leaf node of the hybrid hierarchical bounding box hierarchy tree;

[0022] Recursively merge the adjacent leaf nodes into parent nodes, each parent node representing a sub-area of the digital twin model;

[0023] According to the geometric characteristics of each physical entity of the model in the sub-region, a corresponding bounding box type is selected to construct a bounding box for the sub-region corresponding to each parent node;

[0024] If the leaf nodes are merged into one root node, it is determined that the construction of the mixed hierarchical bounding box hierarchy tree is completed.

[0025] In one embodiment, for the leaf node that intersects with the bounding box of the physical entity to be detected, determining the collision detection result through geometric calculation and synchronizing it to the digital twin model in real time includes:

[0026] Extracting basic primitives from the intersecting leaf nodes and the physical entity to be detected;

[0027] Performing an intersection test on the basic graphic elements through an intersection test algorithm to determine whether the basic graphic elements intersect;

[0028] If the basic graphic elements intersect, determining the intersection point, intersection depth, and intersection normal of the basic graphic elements through geometric calculation as the geometric calculation result;

[0029] Based on the geometric calculation results, it is determined whether a collision occurs, the collision detection result is determined, and the collision detection result is synchronized to the digital twin model in real time.

[0030] In one embodiment, before the step of feeding back the collision detection result to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected, the step includes:

[0031] Select the corresponding control algorithm according to the system characteristics and control requirements, and tune the parameters of the control algorithm to obtain the best control effect;

[0032] Formulate a feedback control strategy based on the collision detection results and the control algorithm, and integrate it into the digital twin engine;

[0033] Combining the feedback control strategy with the control system of the physical entity to be detected to form a closed-loop control loop;

[0034] Based on the closed-loop control circuit, if a collision event is detected, the step of feeding back the collision detection result to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected is performed.

[0035] In one embodiment, the step of feeding back the collision detection result to a control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected includes:

[0036] determining collision event information and collision result information as collision related information based on the collision detection result;

[0037] Comparing and analyzing the collision-related information with the data in the digital twin model;

[0038] generating feedback content based on the results of the comparative analysis;

[0039] The feedback content is fed back to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a physical collision monitoring and feedback device based on a digital twin engine, the device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the physical collision monitoring and feedback method based on the digital twin engine as described above.

[0041] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the physical collision monitoring and feedback method based on the digital twin engine as described above are implemented.

[0042] The present application provides a physical collision monitoring and feedback method based on a digital twin engine. The present application performs preliminary collision detection on the model physical entity in the digital twin model based on the physical entity to be detected, and determines the preliminary collision object; based on the preliminary collision object, traverses the mixed hierarchical bounding box hierarchy tree of the preliminary collision object in the digital twin model, checks each node layer by layer to see if it intersects with the bounding box of the physical entity to be detected, and determines the leaf node of the mixed hierarchical bounding box hierarchy tree where the intersection occurs; for the leaf node that intersects with the bounding box of the physical entity to be detected, the collision detection result is determined by geometric calculation and synchronized to the digital twin model in real time; the collision detection result is fed back to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected. The present application screens out physical entities that may collide through preliminary collision detection, avoids detailed detection of all physical entities, and improves the efficiency of collision detection. By constructing a mixed hierarchical bounding box hierarchy tree, the complex physical entity model is simplified into a series of bounding boxes, so that collision detection can be carried out step by step at different levels, thereby improving the detection speed while ensuring accuracy. Once a collision is detected, the specific location and situation of the collision are determined through geometric calculations and synchronized to the digital twin model in real time, ensuring that the state in the virtual environment is consistent with the physical entity for further decision-making. The collision detection results are promptly fed back to the control system of the physical entity to adjust the operating state of the physical entity based on the collision situation. This application achieves the technical effect of improving the accuracy of physical collision monitoring and feedback. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0045] Figure 1 A flowchart illustrating the first embodiment of the physical collision monitoring and feedback method based on a digital twin engine of this application is provided;

[0046] Figure 2 A flow chart illustrating the second embodiment of the physical collision monitoring and feedback method based on a digital twin engine of this application;

[0047] Figure 3 A flowchart illustrating the third embodiment of the physical collision monitoring and feedback method based on a digital twin engine of this application is provided;

[0048] Figure 4 A flowchart illustrating a fourth embodiment of a physical collision monitoring and feedback method based on a digital twin engine of this application is provided;

[0049] Figure 5 A schematic diagram of the overall process of the physical collision monitoring and feedback method based on the digital twin engine provided in this application;

[0050] Figure 6 This is a schematic diagram of the device structure of the hardware operating environment involved in the physical collision monitoring and feedback method based on the digital twin engine in the embodiment of the present application.

[0051] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0053] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0054] The main solutions of the embodiments of this application are:

[0055] Currently, in terms of collision monitoring and feedback of physical entities, traditional collision detection systems mainly rely on physical sensors to collect data in real time and combine them with algorithms for collision detection. However, due to the imperfect feedback mechanism of the current collision detection system, it is impossible to accurately feed back the collision detection results to the control system of the physical entity in real time, resulting in the control system being unable to respond to collision events in a timely manner.

[0056] This application uses preliminary collision detection to screen out physical entities that may collide, avoiding detailed detection of all physical entities and improving the efficiency of collision detection. By constructing a mixed-level bounding box hierarchy tree, the complex physical entity model is simplified into a series of bounding boxes, so that collision detection can be carried out step by step at different levels, thereby improving the detection speed while ensuring accuracy. Once a collision is detected, the specific location and situation of the collision are determined through geometric calculations and synchronized to the digital twin model in real time, ensuring that the state in the virtual environment is consistent with the physical entity for further decision-making, and the collision detection results are promptly fed back to the control system of the physical entity to adjust the operating state of the physical entity according to the collision situation.

[0057] It should be noted that the execution entity of this embodiment can be a physical collision monitoring and feedback system based on a digital twin engine, or a computing service device with data processing, network communication, and program execution capabilities, such as a tablet computer, personal computer, or mobile phone, or a control device for a physical collision monitoring and feedback system based on a digital twin engine that can implement the above functions. This embodiment does not specifically limit this. The following uses a physical collision monitoring and feedback system based on a digital twin engine as an example to illustrate this embodiment and the following embodiments.

[0058] Example 1

[0059] Based on this, this application proposes a physical collision monitoring and feedback method based on a digital twin engine in the first embodiment, please refer to Figure 1 , the physical collision monitoring and feedback method based on the digital twin engine includes:

[0060] Step S10: Perform preliminary collision detection on the model physical entity in the digital twin model based on the physical entity to be detected to determine the preliminary collision object.

[0061] Using digital twin technology, the behavior of the physical entity to be detected in the virtual environment is simulated, and through preliminary collision detection, objects that may collide with the physical entity to be detected are quickly screened out, reducing the computational burden of subsequent fine detection and improving the efficiency of overall collision detection.

[0062] In this embodiment, the physical entities to be detected are objects that actually exist in the physical world and whose collision risks are to be monitored in the digital twin model, including drones and robots. The modeled physical entities in the digital twin model are objects in the real physical world, represented in the virtual environment by the digital twin model. Preliminary collision detection uses a collider to quickly determine which physical entities are likely to collide. This process is based on simple geometric shapes and boundary conditions, does not involve complex physical calculations, and has low computational cost, but relatively low accuracy.

[0063] Optionally, the triggering conditions for performing preliminary collision detection include but are not limited to the following:

[0064] Preliminary collision detection is triggered periodically according to preset time intervals.

[0065] According to the position relationship trigger, when the physical entity to be detected enters the preset area of the digital twin model, preliminary collision detection is triggered; or, when the relative distance between the physical entity to be detected and the model physical entity in the digital twin model is less than the distance threshold, preliminary collision detection is triggered.

[0066] The preliminary collision detection is triggered by user interface operation or input command.

[0067] As an optional implementation method, a collision detector is configured for the model physical entity in the digital twin model, the motion trajectory of the physical entity to be detected is simulated through the digital twin model, and the collision detector is used to perform preliminary collision detection on the physical entity to be detected and other physical entities in the digital twin model, and the colliding object pairs are recorded as preliminary collision physical entities.

[0068] It's important to note that collision detectors are components used in VR engines to detect collisions. They define the collision boundaries of objects and are used to quickly detect potential collisions between them. Collider types include cube colliders, sphere colliders, and capsule colliders. VR engines are used to create and manage objects and interactions within virtual environments. They include built-in physics engines that simulate movement and collisions in the physical world, including Unity3D and Unreal Engine.

[0069] Optionally, configure a collider for the model physics entity in the virtual reality engine, set the shape and size of the collider to match the actual shape and bounds of the model physics entity, ensure that the collider is correctly associated with the model physics entity, and can respond to collision events.

[0070] Step S20, traverse the mixed hierarchical bounding box hierarchy tree of the preliminary collision object in the digital twin model, check each node layer by layer whether it intersects with the bounding box of the physical entity to be detected, and determine the leaf node of the mixed hierarchical bounding box hierarchy tree where the intersection occurs.

[0071] Based on the initial collision detection, the accuracy and efficiency of collision detection are further improved. Through the step-by-step detection of the hierarchical tree structure, areas where collisions are unlikely to occur can be quickly eliminated, and resources can be concentrated on more refined collision detection, thereby reducing computing costs and improving the real-time performance and accuracy of the system.

[0072] In this embodiment, the preliminary collision object is a model physical entity that may collide with the physical entity to be detected, which is quickly screened out by the built-in collider of the virtual reality engine during the preliminary collision detection. The hybrid hierarchical bounding box hierarchical tree is a hierarchical tree structure that combines multiple bounding box types for efficient collision detection. Each node of the hierarchical tree contains a bounding box, and the hierarchical tree can be constructed by recursive partitioning or merging methods. The root node is the top-level node of the hierarchical tree, which contains the bounding box of the entire digital twin model. The collision detection of the root node can quickly exclude a large range of non-collision areas. The leaf node is the bottom-level node of the hierarchical tree, which contains the bounding box of the smallest unit of the digital twin model. The collision detection of the leaf node can perform more refined collision detection. Intersection is when two bounding boxes overlap or touch in space, which means that the physical entities they represent may have collided. Step-by-step detection is a process that starts from the root node and gradually detects each node downward to determine whether the nodes intersect.

[0073] As an optional implementation, construct the bounding box of the physical entity to be detected, and obtain the mixed-level bounding box hierarchy tree corresponding to the preliminary collision object. Starting from the root node, traverse each node of the hierarchy tree to determine whether the root node of the mixed-level bounding box hierarchy tree intersects with the bounding box of the physical entity to be detected. If the root node does not intersect, then the preliminary collision object cannot collide and can be directly excluded. If the root node intersects, recursively detect its child nodes. For each child node, determine whether it intersects with the bounding box of the physical entity to be detected. If a child node does not intersect, then its child node does not need to be detected. For the intersecting leaf nodes, further more refined collision detection is performed.

[0074] As an optional implementation method for obtaining a mixed hierarchical bounding box hierarchy tree, a corresponding mixed hierarchical bounding box hierarchy tree is constructed based on the preliminary collision object. Starting from the bounding box of the entire model, as the root node of the hierarchy tree, the root node is divided into multiple child nodes, each child node represents a sub-area of the model. According to the geometric characteristics of the object, the bounding box type is selected to construct a bounding box for each child node. When the complexity of the child node is lower than the complexity threshold, the recursive division is stopped. The adjacent leaf nodes are merged into a parent node, and a bounding box is constructed for the parent node based on the geometric characteristics of the object. Through recursive division and merging, a complete hierarchical tree structure is constructed.

[0075] As another optional implementation of obtaining the mixed-level bounding box hierarchy tree, the corresponding constructed mixed-level bounding box hierarchy tree is directly obtained based on the preliminary collision object.

[0076] Step S30: For the leaf node that intersects with the bounding box of the physical entity to be detected, the collision detection result is determined through geometric calculation and synchronized to the digital twin model in real time.

[0077] For leaf nodes that intersect with the bounding box of the physical entity to be detected, precise geometric calculations are performed to determine the specific collision information. This information is synchronized to the digital twin model in real time to ensure that the virtual model is consistent with the state of the physical entity, thereby improving the system's response speed.

[0078] In this embodiment, geometric calculation is to calculate the specific intersection between two geometric shapes through mathematical methods to determine whether a collision occurs and the specific information of the collision, including the collision position, collision force, collision normal, etc. The collision detection result is obtained through geometric calculation on whether a collision occurs between physical entities and the specific circumstances of the collision, which may include detailed information such as collision time, collision position, collision object, collision depth, collision normal, collision speed, collision force, etc. The digital twin model is an accurate representation of a physical entity in a virtual space, including geometric shape, physical properties, dynamic parameters, etc., which is used to simulate the behavior and state of the physical entity. Real-time synchronization refers to the immediate update of the collision detection results to the digital twin model to ensure that the state between the model and the physical entity remains consistent.

[0079] As an optional implementation, while traversing the hybrid bounding box hierarchy tree, a more refined geometric calculation is performed on leaf nodes that intersect with the bounding box of the physical entity to be detected. Primitives are extracted from the intersecting leaf nodes and an intersection check is performed on these primitives to determine the specific intersection between the primitives. Based on the results of the geometric calculation, a collision is determined and a collision detection result is output.

[0080] As an optional implementation method of the intersection test, triangular faces are extracted from the intersecting leaf nodes, and the triangular faces of the physical entity to be detected are extracted to perform intersection detection on the two triangular faces. If the two intersect, the intersection point, intersection depth, intersection normal and other information are calculated to further determine the collision position, collision force, collision normal and other information of the collision detection result.

[0081] As an alternative implementation for intersection detection between two triangles, for each triangle, the cross product of the normal and the edge is selected as the separating axis, and the vertices of the two triangles are projected onto each separating axis. If the projections do not overlap on any separating axis, the two triangles do not intersect; if the projections overlap on all separating axes, the two triangles intersect.

[0082] As another optional implementation of intersection detection of two triangles, for the two triangles, their Minkowski sum is calculated, and it is determined whether the Minkowski sum contains the origin. If it does, the two triangles intersect.

[0083] As an optional implementation of the intersection test, extract the triangles from the intersecting leaf nodes, extract the HOLE bounding box of the physical entity to be detected, and obtain the polygonal boundary of the HOLE bounding box. Determine whether each edge of the triangle intersects with each edge of the polygon, and determine whether each vertex of the triangle is inside the polygon. If any edge of the triangle intersects with the edge of the polygon, or any vertex of the triangle is inside the polygon, the triangle intersects with the HOLE bounding box. If the two intersect, calculate the intersection point, intersection depth, intersection normal and other information to further determine the collision position, collision force, collision normal and other information of the collision detection result.

[0084] Optionally, step S30 includes:

[0085] Step S31: extracting basic primitives from the intersecting leaf nodes and the physical entity to be detected.

[0086] It should be noted that the leaf node is the lowest node in the hierarchical tree and contains the bounding box of the smallest unit of the model. The basic primitive is the smallest unit that constitutes the geometric shape of the physical entity, including triangles, line segments, points, etc.

[0087] Exemplarily, triangular facets are extracted from the intersecting leaf nodes, and the HOLE bounding volume of the physical entity to be detected is extracted.

[0088] Step S32: performing an intersection test on the basic graphic elements through an intersection test algorithm to determine whether the basic graphic elements intersect.

[0089] It should be noted that the intersection test algorithm is an algorithm used to determine whether two geometric shapes intersect, including the separating axis theorem, Minkowski sum, geometric projection method, etc.

[0090] As an optional implementation, for two primitives, the cross product of the normal and the edge is selected as the separating axis, and the vertices of the two primitives are projected onto each separating axis. If the projections do not overlap on one of the separating axes, the two primitives do not intersect; if the projections overlap on all separating axes, the two primitives intersect.

[0091] As another optional implementation, for two basic primitives, their Minkowski sum is calculated, and it is determined whether the Minkowski sum contains the origin. If the origin is contained, the two basic primitives intersect.

[0092] As another optional implementation, for two primitives, multiple projection axes are selected that include the cross product of normals and edges, and the vertices of the geometric shapes of the two primitives are projected onto each projection axis. If the projections of the geometric shapes on one of the projection axes do not overlap, the two primitives do not intersect; if the projections of the geometric shapes on all projection axes overlap, the two primitives intersect.

[0093] Step S33: If the basic graphic elements intersect, the intersection point, intersection depth and intersection normal of the basic graphic elements are determined by geometric calculation as the geometric calculation result.

[0094] It's important to note that geometric calculations use mathematical methods to determine the specific intersection between two geometric shapes, including the intersection point, intersection depth, and intersection normal. The intersection point is the point of intersection or contact between two primitives when they intersect, and is used to determine the location of the collision. The intersection depth is the degree of penetration or overlap between the two intersecting primitives at the intersection point, which is used to calculate the force and depth of the collision. The intersection normal is a vector perpendicular to the intersection plane at the intersection point, which is used to determine the direction and angle of the collision.

[0095] Exemplarily, the coordinates of the intersection point are calculated by a mathematical method of linear interpolation, the intersection depth is calculated using a vector projection method, and the intersection normal is calculated using a vector cross product method.

[0096] Step S34: determine whether a collision occurs based on the geometric calculation result, determine the collision detection result, and synchronize the collision detection result to the digital twin model in real time.

[0097] For example, based on the geometric calculation results, a collision is determined between two primitives. If the intersection point, intersection depth, and intersection normal are all valid, a collision is considered to have occurred. Collision detection results are generated and synchronized to the digital twin model in real time, ensuring that the virtual model and the physical entity are consistent.

[0098] Optionally, generating collision detection results includes using the system's time function to obtain the current time as the collision time; determining the specific location where the collision occurred based on the coordinates of the intersection point determined in the geometric calculation as the collision location; recording the identification of the objects involved in the collision as the collision objects; determining the collision depth based on the calculated depth of the intersection of the two objects; determining the collision normal based on the calculated intersection normal; obtaining the velocity from the physical component of the object as the collision velocity; and calculating the collision force based on the mass and velocity of the collision object.

[0099] Step S40 : Feedback the collision detection result to the control system of the physical entity to be detected, so as to adjust the operating state of the physical entity to be detected.

[0100] Through real-time collision detection and feedback, the control system can timely adjust the operating status of the physical entity to be detected to ensure that the physical entity to be detected can safely and effectively avoid collisions during operation, thereby preventing potential damage, injury or accidents.

[0101] In this embodiment, the physical entity to be detected refers to an object that exists in the real world and has a physical form and mobility, including robots, autonomous vehicles, robotic arms, drones, etc. The control system is responsible for monitoring and controlling the behavior of the physical entity to be detected. It includes sensors, actuators, and controllers, and regulates the movement and state of the physical entity to be detected according to preset logic or algorithms. The operating state is the current state of the physical entity to be detected, including position, velocity, acceleration, and force.

[0102] As an optional implementation, after the collision detection algorithm is triggered, the interface of the control system is directly called to transmit the collision detection result.

[0103] As another optional implementation, the collision detection result is converted into a data packet and sent to a server of the control system through a network.

[0104] Optionally, after receiving the data packet, the server of the control system parses the data and calls corresponding control logic.

[0105] Furthermore, the operating state of the physical entity to be detected is adjusted according to the collision detection result through the control system of the physical entity to be detected.

[0106] Optionally, through the control system of the physical entity to be detected, the speed of the object is adjusted according to the collision force; the direction of the object is adjusted according to the collision normal; and a reverse force is applied at the collision point according to the collision force.

[0107] Exemplarily, through the control system of the physical entity to be detected, the speed of the object is reduced according to the collision force, and a vector proportional to the collision force is subtracted from the speed vector of the object; the speed vector of the object is reflected according to the collision normal, the reflection vector of the speed vector on the collision normal is calculated, and the speed of the object is set to the reflection vector; a force opposite to the collision force is applied at the collision point, and a reverse force is applied at the collision point using the force application function of the physics engine.

[0108] Optionally, step S40 includes:

[0109] Step S41 : determining collision event information and collision result information as collision related information according to the collision detection result.

[0110] The purpose of collecting relevant information about collision events is to fully understand the details of the collision, including the time, location, objects involved, depth, normal direction, speed and force of the collision, so as to evaluate the impact of the collision on the state of the physical entity and help subsequent decision-making and control adjustments.

[0111] In this embodiment, the collision detection result is the output of the collision detection algorithm, including whether a collision occurred and related information. A collision event is a detected collision between two or more physical entities. Collision event information includes the time of collision, location in physical space, physical properties of both colliding entities, such as mass, velocity, and acceleration, and the severity of the collision. Collision result information is the state change of the physical entities after the collision, such as the degree of damage and change in motion state.

[0112] Exemplarily, based on the collision detection results, relevant information of the collision event in the collision detection results is collected, including the specific time of the collision obtained using the system's time function; the specific location of the collision obtained through the intersection point; the identification of the objects involved in the collision; the depth of the collision obtained based on the depth of the intersection, and then the severity of the collision; the normal direction of the collision point obtained through vector calculation; the speed of the object at the time of collision obtained from the physical component; the force of the collision calculated based on the mass and speed of the object, etc.

[0113] Step S42: Compare and analyze the collision-related information with the data in the digital twin model.

[0114] Compare and analyze the collected collision information with the data in the digital twin model, evaluate the impact of the collision on the state of the physical entity, and determine whether the collision will cause damage to the physical entity, performance degradation or other adverse effects, thereby providing a basis for subsequent control adjustments.

[0115] It should be noted that comparative analysis is to compare actual collision information with expected data in the model to analyze the differences.

[0116] As an optional implementation method, relevant data such as expected position, speed, and force are extracted from the digital twin model, the collected collision information is compared with the data in the model, and the impact of the collision on the state of the physical entity is evaluated based on the comparison results.

[0117] Exemplarily, the actual collision information is compared with the data in the digital twin model, including comparing the actual collision position with the expected position in the digital twin model to evaluate the position deviation; comparing the actual collision speed with the expected speed in the digital twin model to evaluate the speed change; comparing the actual collision force with the expected force in the digital twin model to evaluate the force difference; comparing the actual collision depth with the expected depth in the digital twin model to evaluate the depth difference; comparing the actual collision normal with the expected normal in the digital twin model to evaluate the direction change.

[0118] Exemplarily, the specific impact of the collision on the state of the physical entity is evaluated, including: if the collision force exceeds a force threshold or the collision depth exceeds a depth threshold, it indicates that the surface or internal structure of the physical entity is damaged; if the collision causes a significant slowdown in speed or an increase in position deviation, the performance of the physical entity is degraded; based on the collision position and normal direction, the safety impact of the collision on the operator or the surrounding environment is evaluated.

[0119] Step S43: generating feedback content based on the result of the comparative analysis.

[0120] In this embodiment, the feedback content is specific information generated based on the comparative analysis results, including collision event information, collision result information, warnings and optimization suggestions, etc. The collision event information includes the time of the collision, the position in the physical space, the physical properties of the colliding parties such as mass, speed, acceleration, and the severity of the collision. The collision result information is the state change of the physical entity after the collision, including the degree of damage, change in motion state, etc., as well as the impact of the state change on the overall performance or safety of the system. Warnings and optimization suggestions are warning information provided to users or systems based on the collision monitoring results, as well as suggestions such as optimizing the physical entity design, operation strategy or maintenance plan, in order to reduce the occurrence of future collision events or reduce their impact.

[0121] Exemplarily, based on the evaluation result, a control instruction for adjusting the speed, direction or force is generated, and the control instruction is formatted into an instruction that can be executed by the control system of the physical entity to be detected.

[0122] Step S44: Feedback the feedback content to the control system of the physical entity to be detected, so as to adjust the operating state of the physical entity to be detected.

[0123] In this embodiment, the control system of the physical entity to be detected is a system for controlling the behavior of the physical entity to be detected, and includes a sensor, an actuator, and a controller.

[0124] As an optional implementation, the interface of the control system is directly called to transmit the control instruction.

[0125] As another optional implementation, the feedback content is converted into a data packet and sent to a server of the control system through a network.

[0126] This embodiment provides a physical collision monitoring and feedback method based on a digital twin engine. This embodiment first screens out physical entities that may collide through preliminary collision detection, avoiding detailed detection of all physical entities and improving the efficiency of collision detection. By constructing a mixed-level bounding box hierarchy tree, the complex physical entity model is simplified into a series of bounding boxes, so that collision detection can be carried out step by step at different levels, thereby improving the detection speed while ensuring accuracy. Once a collision is detected, the specific location and situation of the collision are determined through geometric calculations and synchronized to the digital twin model in real time, ensuring that the state in the virtual environment is consistent with the physical entity for further decision-making, and the collision detection results are promptly fed back to the control system of the physical entity to adjust the operating state of the physical entity according to the collision situation.

[0127] Based on Example 1, Example 2 of this application proposes a physical collision monitoring and feedback method based on a digital twin engine, referring to Figure 2 , before step S10, including:

[0128] Step S50: construct the digital twin model of the physical system where the model physical entity is located through three-dimensional modeling tools and physical simulation software, and integrate it into the digital twin engine to simulate the overall operating status of the physical system.

[0129] Building a digital twin model of a physical system is used to simulate the overall operating state of the physical system, including the movement, force, position change, etc. of the model's physical entities, so as to analyze the physical system in a virtual environment and thus improve the system's performance.

[0130] It should be noted that 3D modeling tools are software tools used to create 3D models, including AutoCAD, SolidWorks, Blender, etc., which can accurately represent the geometry and structure of physical entities. Physical simulation software is software used to simulate the behavior of physical systems, including ANSYS, ABAQUS, ADAMS, etc., which can simulate the mechanical, thermal, fluid dynamics and other characteristics of physical entities. Digital twin models are accurate representations of physical entities in virtual space, including geometric shapes, physical properties, dynamic parameters, etc., used to simulate the behavior and state of physical entities. Digital twin engines are platforms for managing and running digital twin models, including model integration, simulation, analysis and other functions. Digital twin engines include digital twin models, real-time data acquisition systems, collision monitoring algorithms and feedback control strategies.

[0131] As an optional implementation, select a 3D modeling tool and physical simulation software based on the complexity and requirements of the physical system. Use the 3D modeling tool to create a 3D model of the physical entity based on its geometry, structural details, and other characteristics. In the physical simulation software, set the physical properties and dynamic parameters for the model. Import the created 3D model and the set physical properties and dynamic parameters into the digital twin engine.

[0132] Optionally, the model is integrated and configured in the digital twin engine to ensure that the interfaces and data formats between the sub-models are consistent, and to achieve interaction and association between the sub-models in the digital twin engine.

[0133] Step S60: collect the operating status data of the physical system in real time, and transmit the collected operating status data to the digital twin model to ensure that the data in the digital twin model is synchronized with the operating status data in the physical system.

[0134] The operating status data of the physical system is collected in real time and transmitted to the digital twin model to maintain the consistency between the virtual model and the actual physical system status. The digital twin model can reflect the operating status of the physical system in real time, provide accurate data support for system monitoring, analysis and control, and improve the system's response speed.

[0135] It should be noted that operating status data describes the operating conditions of a physical system, including position, velocity, acceleration, force, temperature, etc. Data synchronization involves updating the operating status data of the actual physical system to the digital twin model in real time to ensure that the model is consistent with the actual system status.

[0136] Optionally, select sensors based on the characteristics and requirements of the physical system, including position sensors, force sensors, acceleration sensors, and temperature sensors. Deploy sensors at key locations within the physical system to comprehensively collect data on the system's operating status. These include mechanical component connection points, stress points, and key points along the motion trajectory.

[0137] As an optional implementation, data acquisition equipment is used to collect sensor data in real time and preprocess the collected data. The collected operational status data is transmitted to the digital twin model through a data interface using data transmission protocols such as TCP / IP, UDP, and Modbus. The operational status data is synchronized and updated in real time within the digital twin model to ensure that the model is consistent with the actual physical system state.

[0138] This embodiment provides a physical collision monitoring and feedback method based on a digital twin engine. This embodiment first uses a digital twin model to reflect the state of the physical system in real time, facilitating the timely detection of faults and issues, allowing for the implementation of appropriate optimization measures. Through simulation analysis using the digital twin model, potential future collisions of the physical system can be predicted. Based on the prediction results, the physical system's operational strategy can be optimized to improve system efficiency and performance.

[0139] Based on Example 1, Example 3 of this application proposes a physical collision monitoring and feedback method based on a digital twin engine, referring to Figure 3 , before step S20, including:

[0140] Step S70: construct the hybrid hierarchical bounding box hierarchy tree according to the geometric characteristics of the physical entities of each model in the digital twin model.

[0141] By decomposing the geometric characteristics of the model's physical entities into bounding boxes at different levels, the possible intersecting areas can be quickly screened out during the collision detection process, reducing unnecessary calculations and thus improving the real-time performance and accuracy of the system.

[0142] In this embodiment, the digital twin model is an accurate representation of a physical entity in virtual space, including its geometry, physical properties, and dynamic parameters, used to simulate the behavior and state of the physical entity. Geometric properties are the geometric and structural characteristics of the model's physical entity, including size, shape, and surface features. A hybrid hierarchical bounding box tree is a hierarchical tree structure that combines multiple bounding box types for efficient collision detection. Each node in the tree contains a bounding box, and the tree can be constructed through recursive partitioning or merging to improve collision detection efficiency.

[0143] As an optional implementation, the geometric data of the model physical entity is extracted from the digital twin model, and the appropriate bounding box type is selected according to the geometric characteristics of the model physical entity, and a hybrid hierarchical bounding box hierarchy tree is constructed using a top-down method or a bottom-up method.

[0144] In this embodiment, bounding box types include AABB (axis-aligned bounding box), OBB (directional bounding box), and k-DOPs (k-discrete directional bounding box). Axis-aligned bounding boxes are rectangular boxes aligned with the coordinate axes. They are computationally simple but less compact. Directional bounding boxes are rectangular boxes that can be oriented in any direction. They are more compact but computationally complex. k-discrete directional bounding boxes are bounding boxes defined by projections in multiple directions, achieving a balance between compactness and computational cost.

[0145] Optionally, step S70 includes:

[0146] Step A10: construct the hybrid hierarchical bounding box hierarchy tree using a top-down approach, starting with the bounding box of the digital twin model as the root node of the hybrid hierarchical bounding box hierarchy tree.

[0147] For example, since the axis-aligned bounding box has low computational cost and is suitable for quickly screening large-scale collisions, the axis-aligned bounding box is used as the root node.

[0148] Step A20: recursively divide the root node into at least one child node, each of which represents a sub-area of the digital twin model.

[0149] It's important to note that child nodes are nodes formed by recursively dividing the root node. Child nodes can be further divided into smaller subnodes. These subnodes form a clear hierarchy within the tree. The root node is at the top of the tree, while the leaf nodes are at the bottom. Each node is connected to its child nodes via pointers, forming a top-down tree structure.

[0150] For example, the middle layer may use k-discrete directional bounding boxes, and the bottom layer may use directional bounding boxes.

[0151] Step A30 : selecting a corresponding bounding box type according to the geometric characteristics of each model physical entity in the sub-region to construct a bounding box for the sub-region corresponding to each child node.

[0152] In this embodiment, for different sub-regions corresponding to different nodes, a suitable bounding box is constructed for each sub-region through a hybrid hierarchical bounding box algorithm, and the corresponding bounding box type is selected according to the geometric characteristics of the model physical entity in each sub-region.

[0153] Step A40: If the complexity of the child node reaches a preset complexity threshold, it is determined that the construction of the hybrid hierarchical bounding box hierarchy tree is completed.

[0154] It should be noted that the preset complexity threshold is a complexity standard set in advance based on system performance requirements and collision detection accuracy requirements. It is the complexity of the virtual model corresponding to the physical entity of the model in the entire digital twin model.

[0155] Optionally, the number of geometric elements contained in the child node and the complexity of the geometric shape are calculated to determine the complexity of the child node.

[0156] Optionally, step S70 further includes:

[0157] Step B10, using a bottom-up approach to construct a bounding box hierarchy tree, starting from the basic geometric elements of the digital twin model, constructing a bounding box for each of the basic geometric elements as a leaf node of the hybrid hierarchical bounding box hierarchy tree.

[0158] For example, all basic geometric elements are extracted from the digital twin model, and a bounding box is constructed for each basic geometric element. For a point, a tiny bounding box centered on the point can be constructed; for an edge, a slender bounding box encompassing the entire edge can be constructed; for a triangular face, a planar bounding box encompassing the entire face can be constructed. The bounding box of each basic geometric element is used as a leaf node in a hybrid hierarchical bounding box hierarchy tree. The leaf node is the starting point for the hierarchical tree construction, and the subsequent hierarchical structure is integrated based on these leaf nodes.

[0159] Step B20: recursively merge the adjacent leaf nodes into parent nodes, each of which represents a sub-area of the digital twin model.

[0160] Exemplarily, based on the spatial position and shape characteristics of the geometric elements, a merging strategy for adjacent leaf nodes is determined, and leaf nodes with similar spatial positions and shapes are merged into one parent node.

[0161] Step B30 : selecting a corresponding bounding box type according to the geometric characteristics of each model physical entity in the sub-region to construct a bounding box for the sub-region corresponding to each parent node.

[0162] For example, the geometric properties of the physical entity are analyzed. For regular-shaped objects, an axis-aligned bounding box is selected; for irregular-shaped objects, an oriented bounding box or a k-discrete oriented bounding box is selected. The selected bounding box type is used to construct a bounding box for the parent node.

[0163] Step B40: If the leaf nodes are merged into one root node, it is determined that the construction of the mixed hierarchical bounding box hierarchy tree is completed.

[0164] Exemplarily, during the hierarchical tree construction process, the merging status of all leaf nodes is continuously checked. When all leaf nodes are merged into one root node, it is confirmed that the construction of the hierarchical tree is completed.

[0165] Optionally, the constructed hierarchical tree is optimized, including adjusting the node division method, optimizing the calculation of the bounding box, etc., to improve the performance and efficiency of the hierarchical tree.

[0166] This embodiment provides a physical collision monitoring and feedback method based on a digital twin engine. This embodiment decomposes the geometric characteristics of the physical entity into bounding boxes of different levels and constructs a mixed-level bounding box hierarchy tree. The hierarchy tree can efficiently handle collision detection problems, simplify the collision detection process, and improve the efficiency and accuracy of collision detection.

[0167] Based on Example 1, Example 4 of this application proposes a physical collision monitoring and feedback method based on a digital twin engine, referring to Figure 4 , before step S40, including:

[0168] Step S80 , selecting a corresponding control algorithm according to the characteristics of the physical entity to be detected and the control requirements, and optimizing the parameters of the control algorithm to obtain the best control effect.

[0169] Select appropriate control algorithms and perform parameter tuning to ensure that the system can respond quickly and accurately based on collision detection results, thereby effectively adjusting the operating status of physical entities, avoiding or mitigating the impact of collisions, and improving system safety and stability.

[0170] It should be noted that the characteristics of the physical entity to be detected are its inherent properties and behavioral characteristics, including inertia, damping, and nonlinearity. The control algorithm is the algorithm used to control the behavior of the physical entity to be detected, and includes PID (proportional-integral-derivative control), sliding mode control, and fuzzy control.

[0171] As an optional implementation, PID control parameter tuning can be performed using the control law "u(t) = Kp[e(t) + 1 / Ti∫e(t)dt + Td*de(t) / dt]," where Kp is the proportional coefficient, Ti is the integral time constant, and Td is the differential time constant. The appropriate equilibrium point can be found by gradually increasing the proportional coefficient and observing the system response; gradually decreasing the integral time constant and observing the system response; and gradually increasing the differential time constant and observing the system response. The proportional coefficient adjusts the response speed to deviations. A larger proportional coefficient results in a faster system response, but an excessively large proportional coefficient can cause system oscillation. The integral time constant eliminates static errors in the system. A smaller integral time constant strengthens the integral effect, but an excessively small integral time constant can cause system overshoot. The differential time constant predicts the deviation's changing trend and enables proactive control. A larger differential time constant results in a faster system response to deviation changes, but an excessively large differential time constant can lead to system instability.

[0172] For example, according to the system response curve, first set a smaller Kp value, gradually increase it until the system oscillates, and then slightly reduce the Kp value to allow the system to reach a stable state; after the proportional coefficient is determined, gradually reduce the Ti value and observe the system response until a suitable balance point is found; after the proportional and integral coefficients are determined, gradually increase the Td value and observe the system response until the system is neither too sensitive nor too slow.

[0173] Optionally, for a linear, time-invariant controlled object, the Ziegler-Nichols method is used to determine the parameters of the PID controller by analyzing the step response of the controlled object.

[0174] Optionally, for nonlinear, time-varying controlled objects, the Cohen-Coon method based on the process response curve is used to tune the PID parameters.

[0175] Optionally, for PID parameter optimization of a complex system, a genetic algorithm is used to search for the optimal solution of the PID parameters by simulating the biological evolution process.

[0176] As another optional implementation, the sliding mode is designed by tuning the PID control parameters to meet the arrival conditions, existence conditions and stability conditions; the control gain is adjusted according to the system characteristics and control requirements to obtain the best control effect; and methods such as filter design and inverter linearization are used to reduce the jitter phenomenon in the sliding mode control.

[0177] Step S90: formulate a feedback control strategy based on the collision detection results and the control algorithm, and integrate it into the digital twin engine.

[0178] Develop a feedback control strategy and integrate it into the digital twin engine, implement the control logic for the physical entity to be detected in the digital twin engine, and ensure that when a collision event is detected, the corresponding control instructions can be quickly generated according to the control algorithm and collision detection results to adjust the operating status of the physical entity.

[0179] It should be noted that the feedback control strategy is based on the control logic and rules formulated based on the collision detection results, which are used to adjust the operating status of the system.

[0180] As an optional implementation method, a specific feedback control strategy is formulated based on the collision detection results and control algorithm. If a collision event is detected, a corresponding speed adjustment, direction adjustment or force application control strategy is formulated according to the strength and direction of the collision. The feedback control strategy is integrated into the digital twin engine and combined with the digital twin model.

[0181] Optionally, configure the parameters and trigger conditions of the control strategy in the digital twin engine to ensure that the control strategy can be automatically executed based on real-time data and collision detection results.

[0182] Step S100 : combining the feedback control strategy with the control system of the physical entity to be detected to form a closed-loop control circuit.

[0183] It should be noted that the closed-loop control loop is a control system that combines a feedback control strategy with the control system of the physical entity to be detected, and can automatically adjust the control instructions according to the feedback information to form a closed control cycle.

[0184] For example, the feedback control strategy in the digital twin engine is connected to the control system of the physical entity to be detected through a data interface, and the parameters and trigger conditions of the control loop are configured in the control system of the physical entity to be detected to ensure that the control strategy can be based on real-time data and collision detection results.

[0185] Step S110 : Based on the closed-loop control circuit, if a collision event is detected, the step of feeding back the collision detection result to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected is executed.

[0186] For example, the operating status of the physical entity to be detected is monitored in real time in the digital twin model. When a collision event is detected, the feedback mechanism is triggered immediately, and the collision detection result is fed back to the control system of the physical entity to be detected through a closed-loop control loop. According to the feedback collision detection result and the preset feedback control strategy, the operating status of the physical entity to be detected is automatically adjusted.

[0187] Optionally, the operating status and control effect of the physical entity to be detected are continuously monitored, and the control strategy is optimized and adjusted according to the actual operating conditions to improve the response speed and stability of the system.

[0188] This embodiment provides a physical collision monitoring and feedback method based on a digital twin engine. This embodiment first maximizes the performance of the control system through parameter tuning, which helps to reduce the response time of the system and improve the stability and accuracy of the system. By combining the collision detection results with the control algorithm, the control strategy is adjusted in real time to deal with potential or existing collision events. The real-time feedback mechanism of the closed-loop control loop can significantly improve the response speed and accuracy of the control system. By feeding back the collision detection results to the control system of the physical entity to be detected, the operating state of the physical entity to be detected can be quickly adjusted to avoid or reduce the damage caused by the collision.

[0189] For example, to help understand the implementation process of the physical collision monitoring and feedback method based on the digital twin engine obtained by combining this embodiment with the above embodiment 1, please refer to Figure 5 , Figure 5 This paper provides a schematic diagram of the overall process of a physical collision monitoring and feedback method based on a digital twin engine. Specifically:

[0190] Utilize the Mesh components of virtual reality engines such as Unity3D to obtain the geometric information of all physical entities. Based on the obtained geometric information, build digital twin models of all physical entities in the digital twin engine, and ensure that the model physical entities in the digital twin model are highly consistent with the physical entities in terms of geometric dimensions, physical properties, etc., providing a basis for collision monitoring.

[0191] Furthermore, appropriate bounding box types are selected based on the shape and characteristics of the model's physical entities, such as axis-aligned bounding boxes (AABBs), directional bounding boxes (OBBs), and discrete directional bounding boxes (k-DOPs). A hybrid hierarchical bounding box tree is constructed using either a top-down or bottom-up approach, ensuring that each node accurately represents the geometric characteristics of the model's physical entities. The top-down approach starts with the entire set and recursively partitions it into child nodes; the bottom-up approach starts with basic geometric elements and recursively merges them into parent nodes. During the construction process, different bounding box types are appropriately combined based on the object's geometric characteristics and collision detection requirements.

[0192] Furthermore, a preliminary collision detection is performed on the physical entity to be detected through the collider of the virtual reality engine, and the model physical entities that may collide with it are quickly screened, and the physical entity to be detected and the model physical entity that collides with it are regarded as collision entities.

[0193] A more accurate collision detection is performed on the collision entities identified in the preliminary detection. The mixed-level bounding box hierarchy tree is traversed to determine whether the root node and leaf nodes intersect with the bounding box of the physical entity to be detected, and the detection is performed step by step. If they do not intersect, the two collision entities have not collided; otherwise, the precise detection phase begins.

[0194] Perform intersection detection of basic graphics elements on the intersecting leaf nodes, determine the collision detection results through geometric calculations, output the collision detection results, and synchronize them to the digital twin model in real time.

[0195] Optionally, after each detection, if it is determined that the collision entities do not collide, a model separation step is performed to prepare for the next collision detection.

[0196] Furthermore, after the collision results are output, a feedback control strategy is developed based on the collision detection results and control algorithm. This feedback control strategy is then integrated with the control system of the physical entity being detected to form a closed-loop control circuit. Through this closed-loop control circuit, if a collision event is detected, the collision detection results are fed back to the control system of the physical entity being detected to adjust its operating state.

[0197] In summary, the physical collision monitoring and feedback method based on the digital twin engine can realize real-time monitoring and accurate judgment of the collision status of the physical entity to be detected, and output the collision detection results to formulate and execute feedback control strategies, thereby improving the stability of the system.

[0198] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the physical collision monitoring and feedback method based on the digital twin engine of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0199] The present application provides a physical collision monitoring and feedback device based on a digital twin engine. The physical collision monitoring and feedback device based on a digital twin engine includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the physical collision monitoring and feedback method based on the digital twin engine in the above-mentioned embodiment one.

[0200] Reference below Figure 6 , which shows a schematic structural diagram of a physical collision monitoring and feedback device based on a digital twin engine suitable for implementing an embodiment of the present application. The physical collision monitoring and feedback device based on a digital twin engine in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, personal digital assistants (PDAs), tablet computers (PADs), portable multimedia players (PMPs), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The physical collision monitoring and feedback device based on the digital twin engine shown is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present application.

[0201] like Figure 6As shown, the physical collision monitoring and feedback device based on the digital twin engine may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the physical collision monitoring and feedback device based on the digital twin engine. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007, such as a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008, such as a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003, such as a magnetic tape, hard disk, etc.; and communication devices 1009. Communication devices 1009 can allow the digital twin engine-based physical collision monitoring and feedback device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a digital twin engine-based physical collision monitoring and feedback device with various systems, it should be understood that implementation or presence of all the illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0202] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0203] The digital twin engine-based physical collision monitoring and feedback device provided in this application adopts the digital twin engine-based physical collision monitoring and feedback method in the above-mentioned embodiment, which can solve the technical problem of how to improve the accuracy of physical collision monitoring and feedback. Compared with the prior art, the beneficial effects of the digital twin engine-based physical collision monitoring and feedback device provided in this application are the same as the beneficial effects of the digital twin engine-based physical collision monitoring and feedback method provided in the above-mentioned embodiment, and the other technical features of the digital twin engine-based physical collision monitoring and feedback device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0204] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0205] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0206] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon. The computer-readable program instructions are used to execute the physical collision monitoring and feedback method based on the digital twin engine in the above-mentioned embodiment.

[0207] The computer-readable storage medium provided herein may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including, but not limited to, wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0208] The above-mentioned computer-readable storage medium may be included in the physical collision monitoring and feedback device based on the digital twin engine; or it may exist independently without being assembled into the physical collision monitoring and feedback device based on the digital twin engine.

[0209] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by a physical collision monitoring and feedback device based on a digital twin engine, the physical collision monitoring and feedback device based on the digital twin engine can be written in one or more programming languages or a combination thereof to perform the operations of the present application. The programming languages include object-oriented programming languages such as Java, Smalltalk, and C++, as well as conventional procedural programming languages such as "C" or similar programming languages. The program code can be executed entirely on the user computer, partially on the user computer, as a standalone software package, partially on the user computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, via the Internet using an Internet service provider).

[0210] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0211] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0212] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned physical collision monitoring and feedback method based on a digital twin engine. This computer-readable storage medium addresses the technical problem of improving the accuracy of physical collision monitoring and feedback. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are similar to those of the physical collision monitoring and feedback method based on a digital twin engine provided in the aforementioned embodiments, and are not further elaborated here.

[0213] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A physical collision monitoring and feedback method based on a digital twin engine, characterized in that: The physical collision monitoring and feedback method based on the digital twin engine includes: Perform preliminary collision detection on the model physical entities in the digital twin model based on the physical entities to be detected, and determine the preliminary collision objects; Traversing the mixed-level bounding box hierarchy tree of the preliminary collision object in the digital twin model, checking layer by layer whether each node intersects with the bounding box of the physical entity to be detected, and determining the leaf node of the mixed-level bounding box hierarchy tree where the intersection occurs; For the leaf nodes that intersect with the bounding box of the physical entity to be detected, the collision detection result is determined by geometric calculation and synchronized to the digital twin model in real time; According to the characteristics of the physical entity to be detected and the control requirements, the corresponding control algorithm is selected, and the PID control parameters are tuned. By gradually increasing the proportional coefficient value, the system response is observed to find a suitable balance point; the integral time constant value is gradually reduced, the system response is observed to find a suitable balance point; by gradually increasing the differential time constant value, the system response is observed to find a suitable balance point; for linear, time-invariant controlled objects, the Ziegler-Nichols method is used to determine the parameters of the PID controller by analyzing the step response of the controlled object; for nonlinear, time-varying controlled objects, the Cohen-Coon method based on the process response curve is used to tune the PID parameters; for PID parameter optimization of complex systems, a genetic algorithm is used to search for the optimal solution of PID parameters by simulating the biological evolution process; Formulate a specific feedback control strategy based on the collision detection results and the control algorithm. If a collision event is detected, formulate a corresponding speed adjustment, direction adjustment, or force application control strategy based on the force and direction of the collision. Integrate the feedback control strategy into the digital twin engine and combine it with the digital twin model. Combining the feedback control strategy with the control system of the physical entity to be detected to form a closed-loop control loop; Based on the closed-loop control circuit, if a collision event is detected, the collision detection result is fed back to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected.

2. The physical collision monitoring and feedback method based on a digital twin engine according to claim 1, characterized in that: Before the step of performing preliminary collision detection on the model physical entity in the digital twin model based on the physical entity to be detected and determining the preliminary collision object, the method includes: Using 3D modeling tools and physical simulation software, a digital twin model of the physical system where the model physical entity resides is constructed and integrated into a digital twin engine to simulate the overall operating state of the physical system; The operating status data of the physical system is collected in real time, and the collected operating status data is transmitted to the digital twin model to ensure that the data in the digital twin model is synchronized with the operating status data in the physical system.

3. The physical collision monitoring and feedback method based on a digital twin engine according to claim 1, characterized in that: Before the step of traversing the mixed hierarchical bounding box hierarchy tree of the preliminary collision object in the digital twin model, checking layer by layer whether each node intersects with the bounding box of the physical entity to be detected, and determining the leaf node of the mixed hierarchical bounding box hierarchy tree where the intersection occurs, the method includes: The hybrid hierarchical bounding box hierarchy tree is constructed according to the geometric characteristics of the physical entities of each model in the digital twin model.

4. The physical collision monitoring and feedback method based on a digital twin engine according to claim 3, characterized in that: The step of constructing the hybrid hierarchical bounding box hierarchy tree according to the geometric characteristics of the physical entities of each model in the digital twin model includes: Constructing the hybrid hierarchical bounding box hierarchy tree using a top-down approach, starting with the bounding box of the digital twin model as the root node of the hybrid hierarchical bounding box hierarchy tree; Recursively divide the root node to form at least one child node, each of the child nodes representing a sub-area of the digital twin model; According to the geometric characteristics of each physical entity of the model in the sub-region, a corresponding bounding box type is selected to construct a bounding box for the sub-region corresponding to each child node; If the complexity of the child node reaches a preset complexity threshold, it is determined that the construction of the hybrid hierarchical bounding box hierarchy tree is completed.

5. The physical collision monitoring and feedback method based on a digital twin engine according to claim 3, characterized in that: The step of constructing the hybrid hierarchical bounding box hierarchy tree according to the geometric characteristics of the physical entities of each model in the digital twin model further includes: A bounding box hierarchy tree is constructed using a bottom-up approach, starting from the basic geometric elements of the digital twin model, and constructing a bounding box for each of the basic geometric elements as a leaf node of the hybrid hierarchical bounding box hierarchy tree; Recursively merge the adjacent leaf nodes into parent nodes, each parent node representing a sub-area of the digital twin model; According to the geometric characteristics of each physical entity of the model in the sub-region, a corresponding bounding box type is selected to construct a bounding box for the sub-region corresponding to each parent node; If the leaf nodes are merged into one root node, it is determined that the construction of the mixed hierarchical bounding box hierarchy tree is completed.

6. The physical collision monitoring and feedback method based on a digital twin engine according to claim 1, characterized in that: The step of determining the collision detection result of the leaf node that intersects with the bounding box of the physical entity to be detected by geometric calculation and synchronizing it to the digital twin model in real time includes: Extracting basic primitives from the intersecting leaf nodes and the physical entity to be detected; Performing an intersection test on the basic graphic elements through an intersection test algorithm to determine whether the basic graphic elements intersect; If the basic graphic elements intersect, determining the intersection point, intersection depth, and intersection normal of the basic graphic elements through geometric calculation as the geometric calculation result; Based on the geometric calculation results, it is determined whether a collision occurs, the collision detection result is determined, and the collision detection result is synchronized to the digital twin model in real time.

7. The physical collision monitoring and feedback method based on a digital twin engine according to claim 1, characterized in that: The step of feeding back the collision detection result to the control system of the physical entity to be detected so as to adjust the operating state of the physical entity to be detected includes: determining collision event information and collision result information as collision related information based on the collision detection result; Comparing and analyzing the collision-related information with the data in the digital twin model; generating feedback content based on the results of the comparative analysis; The feedback content is fed back to the control system of the physical entity to be detected to adjust the operating state of the physical entity to be detected.

8. A physical collision monitoring and feedback device based on a digital twin engine, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the physical collision monitoring and feedback method based on a digital twin engine as described in any one of claims 1 to 7.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the physical collision monitoring and feedback method based on the digital twin engine as described in any one of claims 1 to 7 are implemented.

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