Interactive motion generated data distributed processing method, device, equipment and medium

Abstract

The present invention provides a method, device, equipment and medium for distributed processing of interactive motion generated data. The method for distributed processing of interactive motion generated data includes: obtaining environmental interactive motion data of a virtual character and sending it to a first computing module to obtain motion task data; packaging the motion task data in a first set format and sending it to a second computing module to obtain motion trajectory data; packaging the motion trajectory data in a second set format and sending it to the first computing module; the first computing module controls the interactive motion based on the received packaged data, which is packaged in the second set format. By distributing the data calculations of different functions in path planning to different computing modules and enabling different computing modules to work together, the computing power of different types of computing modules can be effectively utilized to achieve the purpose of improving computing power.

Description

Technical Field

[0001] The present invention belongs to the technical field of virtual environment, and in particular, relates to a distributed processing method, device, equipment and medium for interactive motion generated data. Background Art

[0002] Path planning refers to planning a motion path from a given starting point to a target point in a virtual environment with obstacles, so that the moving object can safely bypass all obstacles without collision during the movement. This involves a large amount of data calculation, which leads to the problem of insufficient computing power. Summary of the invention

[0003] In view of the problems existing in the prior art, the present invention provides a method, device, equipment and medium for distributed processing of interactive motion generated data, which at least partially solves the problem of insufficient computing power existing in the prior art.

[0004] In a first aspect, an embodiment of the present disclosure provides a distributed processing method for interactive motion generated data, comprising:

[0005] The acquired environment interactive motion data of the virtual character is sent to the first computing module to obtain motion task data;

[0006] Packaging the motion task data in a first set format and sending the result to a second calculation module to obtain motion trajectory data;

[0007] Packaging the motion trajectory data in a second set format and sending the result to the first computing module;

[0008] The first calculation module controls the interactive movement based on the received encapsulated data, where the encapsulated data is encapsulated according to a second set format.

[0009] Optionally, the motion task data includes a motion path, surrounding environment voxel data and a motion instruction description.

[0010] Optionally, the motion trajectory data includes a virtual character motion data frame sequence and a motion completion mark.

[0011] Optionally, the step of acquiring the environment interactive motion data of the virtual character and sending it to the first computing module to obtain motion task data includes:

[0012] The first calculation module calculates the motion planning path of the virtual character in response to the motion instruction of the virtual character;

[0013] Calculate the expected path point position of the virtual character within a specified time period based on the motion planning path;

[0014] Obtaining the expected path points and the intermediate interpolation points based on the obtained starting point and expected path point positions of the virtual character;

[0015] According to the starting point, expected path point and intermediate interpolation point of the virtual character, the surrounding voxel data of the starting point, the expected path point and the intermediate interpolation point are calculated.

[0016] Optionally, the first computing module controls the interactive motion based on the received encapsulation data, including:

[0017] Decapsulating the encapsulated data to obtain a virtual character motion data frame sequence and a motion completion mark;

[0018] The virtual character motion data frame sequence is queued and pushed into the action frame queue, and the virtual character is controlled in real time to complete the motion data frames in the queue.

[0019] Optionally, the first computing module controls the interactive motion based on the received encapsulation data, further comprising:

[0020] Determine the true or false value of the movement completion flag;

[0021] If the movement completion flag is true, then the execution process of this round ends;

[0022] If the motion completion flag is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory.

[0023] In a second aspect, the embodiment of the present disclosure further provides a distributed processing device for interactive motion generated data, including:

[0024] A first calculation module is used to calculate motion task data based on the acquired environment interactive motion data of the virtual character, and to send the motion task data after packaging it in a first set format, and to receive data packaged in a second set format, and to control the interactive motion based on the received data packaged in the second set format;

[0025] The second calculation module is used to calculate the motion trajectory data based on the received data packaged in the first set format, and package the motion trajectory data in the second set format before sending.

[0026] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0027] at least one processor; and,

[0028] a memory communicatively connected to the at least one processor; wherein,

[0029] 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 distributed processing method for interactive motion generated data as described in any one of the first aspects.

[0030] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute any of the methods for distributed processing of interactive motion generated data described in the first aspect.

[0031] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the distributed processing method for interactive motion generated data as described in any one of the first aspects.

[0032] The present invention provides a distributed processing method, device, equipment and medium for interactive motion generated data, wherein the distributed processing method for interactive motion generated data distributes the data calculation of different functions in path planning to different computing modules, and enables different computing modules to collaborate, effectively utilizing the computing power of different types of computing modules, thereby achieving the purpose of improving computing power.

[0033] The use of the first set format and the second set format to encapsulate data reduces the frequency of information communication between different computing modules. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0035] Figure 1 A flowchart of a distributed processing method for interactive motion generated data provided by an embodiment of the present disclosure;

[0036] Figure 2 A principle block diagram of a distributed processing device for interactive motion generated data provided by an embodiment of the present disclosure;

[0037] Figure 3 A functional block diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0039] It should be clear that the following embodiments of the present disclosure are described by specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0040] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0041] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The illustrations only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0042] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0043] Virtual environment path planning has practical application scenarios in many fields:

[0044] Robotic Systems: In the field of robotics, path planning techniques are used to achieve autonomous collision-free actions for robots, including ground vehicles and micro aerial vehicles (MAVs). These systems are used in indoor environments and need to optimize resources such as flight time, navigation control, etc.

[0045] Obstacle avoidance flight of UAVs: In the field of UAVs, path planning technology is used for obstacle avoidance and penetration flight to complete specific tasks, such as cruise missiles avoiding radar searches, preventing rebound attacks, and completing penetration and blasting missions.

[0046] GPS navigation and GIS system: In daily life, path planning technology is applied to GPS navigation and road planning based on GIS system, as well as urban road network planning and navigation.

[0047] Logistics Management: In the field of decision management, path planning technology is used in vehicle routing problems (VRP) in logistics management and similar resource management resource allocation problems.

[0048] Communication technology: In the field of communication technology, path planning technology is applied to routing problems.

[0049] Collaborative interaction in virtual geographic environments: In virtual geographic environments (VGEs), path planning techniques are used to support multi-user communication and interaction.

[0050] Digital railway route selection and design: In the railway field, path planning technology is used in the digital railway route selection and design system, providing technical support for route selection engineers to simulate on-site real-life analysis in an indoor three-dimensional environment and realize three-dimensional physical line design.

[0051] Highway survey and design: In the field of highway survey and design, path planning technology is used to build a virtual model platform for mountain roads and environments, realizing the intelligent and rapid construction of three-dimensional highway simulation models.

[0052] Path planning in virtual environments is a complex problem that involves multiple technical challenges and solutions. Key technologies include:

[0053] Environmental modeling: In a virtual environment, path planning requires effective modeling of the environment. Traditional path planning usually uses distance as a reference standard, but as requirements increase, the criteria become more diverse, such as minimum energy, minimum time, etc. In addition, the way environmental information is expressed also greatly affects the efficiency of path search.

[0054] Dynamic environment adaptability: Path planning in virtual environments needs to be able to adapt to dynamically changing environments, including the movement of obstacles and changes in environmental properties.

[0055] Algorithm efficiency: In a virtual environment, the path planning algorithm needs to efficiently process large-scale data and real-time updated environmental information.

[0056] Existing technical solutions:

[0057] Path planning based on deep reinforcement learning: Deep reinforcement learning algorithms, such as the SAC algorithm, have been successfully applied to challenging sequential decision-making and control tasks. The SAC algorithm improves sample efficiency and asymptotic performance by simultaneously maximizing expected reward and entropy.

[0058] Improved artificial potential field method: The artificial potential field method is widely used in unmanned vehicle path planning due to its excellent real-time obstacle avoidance capability. In view of the defects of the traditional artificial potential field method, such as unreachable targets and local minimum problems, researchers have proposed various improvement measures, such as improving the repulsion function by adding a distance factor between the target point and the unmanned vehicle, and constructing a virtual target point by drawing a tangent line outside the collision range of the obstacle.

[0059] Path planning technology based on virtual scenes: Researchers proposed a method based on quadtree structure and grid to represent virtual environment, and proposed a path planning method based on individual parameters and obstacle classification for indoor scenes. Path planning for outdoor scenes involves the influence of terrain factors, extracting and simplifying ground attribute information, designing influencing factors, and applying them to the heuristic algorithm to improve the evaluation function of the traditional A* algorithm.

[0060] GAN connects real and virtual environments: A navigation dataset is generated through a virtual simulator and a generative adversarial network to connect virtual and real environments in an end-to-end approach. This approach can improve the limitations of implementation in embedded devices and display the paths generated by the proposed system by applying an augmented reality visualizer.

[0061] Recent Research: Deep Learning and Reinforcement Learning: Recent research advances include path planning methods based on deep learning and reinforcement learning, which optimize path planning by learning environmental features and agent behaviors.

[0062] In the existing technology, path planning calculation has the following main problems:

[0063] Environmental modeling issues: In environmental modeling, there is a distinction between two-dimensional maps and three-dimensional maps. Three-dimensional maps are more complex in terms of computation and storage than two-dimensional maps, and most path planning algorithms are planned for two-dimensional planes. When faced with three-dimensional maps, the algorithm complexity and computation will increase significantly. For two-dimensional maps, the grid method is mainly used for construction, while the three-dimensional environment requires multiple two-dimensional planes to be superimposed in height and mapped to two dimensions.

[0064] Convergence speed and local optimal solution: Path planning algorithms face challenges in terms of convergence speed and avoiding falling into local optimal solutions. The usual solution is to improve the algorithm structure and increase the adaptability of algorithm parameters to reduce the probability of the algorithm falling into local optimal solutions. In addition, performance can also be optimized by combining different algorithms.

[0065] Adaptability to dynamic environments: Traditional path planning algorithms are mostly based on the establishment of a global map, which leads to the separation of perception and decision-making and is difficult to apply to unknown environments. Therefore, researchers have begun to focus on intelligent algorithms to improve their adaptability to dynamic environments.

[0066] Large-scale real-time path planning problem: In real-world scenarios, path planning technology needs to solve large-scale real-time path planning problems. Specific challenges include large road network scale, fast-changing road attributes, and high requirements for updating road condition information. These require algorithms to be not only efficient, but also able to handle large-scale and real-time problems.

[0067] Balance between algorithm accuracy and running time: Sampling-based path planning algorithms such as PRM and RRT have good scalability and robustness, but their accuracy is affected by sampling density. Increasing the sampling density can improve the accuracy of the path, but it will also increase the running time of the algorithm.

[0068] Execution efficiency in high-dimensional and complex environments: In high-dimensional and complex environments, the storage and search costs of nodes are relatively high, which may result in slow execution efficiency and long search time.

[0069] Design of multi-agent parallel path planning algorithm: With the development of multi-agent parallel collaboration applications, how to achieve collision-free path planning has become one of the research hotspots.

[0070] These issues point out the challenges faced by path planning technology in practical applications, which need to be solved through algorithm improvement, technological innovation and interdisciplinary research.

[0071] Path planning in a virtual character environment involves a lot of calculations, and the amount of data involved in the calculations is large, thus requiring a lot of computing resources.

[0072] For ease of understanding, Figure 1 As shown, this embodiment discloses a distributed processing method for interactive motion generated data, including:

[0073] Step S101: acquiring the environment interaction motion data of the virtual character and sending it to the first calculation module to obtain motion task data;

[0074] Optionally, the motion task data includes a motion path, surrounding environment voxel data and a motion instruction description.

[0075] Optionally, the step of acquiring the environment interactive motion data of the virtual character and sending it to the first computing module to obtain motion task data includes:

[0076] The first calculation module calculates the motion planning path of the virtual character in response to the motion instruction of the virtual character;

[0077] Calculate the expected path point position of the virtual character within a specified time period based on the motion planning path;

[0078] Obtaining the expected path points and the intermediate interpolation points based on the obtained starting point and expected path point positions of the virtual character;

[0079] According to the starting point, expected path point and intermediate interpolation point of the virtual character, the surrounding voxel data of the starting point, the expected path point and the intermediate interpolation point are calculated.

[0080] Step S102: Packaging the motion task data in a first setting format and sending it to a second calculation module to obtain motion trajectory data. The first setting format is shown in Table 1.

[0081] Optionally, the motion trajectory data includes a virtual character motion data frame sequence and a motion completion mark.

[0082] Table 1. Description of the first setting format

[0083]

[0084] Step S103: Packaging the motion trajectory data according to a second set format and sending it to the first calculation module;

[0085] Step S104: the first calculation module controls the interactive motion based on the received encapsulated data, the encapsulated data is encapsulated according to the second setting format, and the second setting format is shown in Table 2.

[0086] Table 2. Description of the second setting format

[0087]

[0088] Optionally, the first computing module controls the interactive motion based on the received encapsulation data, including:

[0089] Decapsulating the encapsulated data to obtain a virtual character motion data frame sequence and a motion completion mark;

[0090] The virtual character motion data frame sequence is queued and pushed into the action frame queue, and the virtual character is controlled in real time to complete the motion data frames in the queue.

[0091] Optionally, the first computing module controls the interactive motion based on the received encapsulation data, further comprising:

[0092] Determine the true or false value of the movement completion flag;

[0093] If the movement completion flag is true, then the execution process of this round ends;

[0094] If the motion completion flag is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory.

[0095] In a specific implementation scenario, the first computing module is a CPU, and the second computing module is a GPU.

[0096] Task allocation between the CPU computing end and the GPU computing end: the CPU computing end is responsible for completing the virtual character environment perception, path planning and motion control computing tasks; the GPU computing end is responsible for completing the motion trajectory generation computing tasks.

[0097] Data format of information sent by the CPU computing end: The CPU computing end is responsible for completing real-time computing tasks such as virtual character environment perception, path planning, motion control, etc. The generated message data content is shown in Table 1.

[0098] Data format of information sent by GPU computing end: GPU computing end is responsible for completing the calculation task of generating the motion trajectory of the virtual character, and the content of the generated message data is shown in Table 2.

[0099] The collaboration process between the CPU computing end and the GPU computing end:

[0100] After receiving the movement instruction of the virtual character, the CPU computing end:

[0101] (1) Calculate the motion planning path of the virtual character;

[0102] (2) Based on the planned motion path, calculate the path point location that the virtual character is expected to move to within a specified time period;

[0103] (3) Calculate the surrounding voxel data of different points based on the starting point, expected path points, and intermediate interpolation points of the virtual character;

[0104] (4) Encapsulate the data calculated by (1)-(3) into the data format of Table 1 and send it to the GPU computing end;

[0105] (5) The GPU computing end generates the motion trajectory of the virtual character, encapsulates it into the data format of Table 2, and sends it to the CPU computing end.

[0106] (6) After receiving the data from step (5), the CPU computing end executes the following two computing tasks in parallel:

[0107] (6.1) Queue the virtual character motion data frame sequence into the action frame queue, and control the virtual character to complete the motion frames in the queue in real time;

[0108] (6.2) If the motion completion flag is true, the execution process of this round ends; if it is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory, and jump to the calculation step (1).

[0109] The distributed architecture of this implementation realizes the computing function of generating interactive motion of virtual characters in the environment. The virtual character's environmental perception, path planning, and motion control are CPU-intensive computing tasks, and motion trajectory generation is a GPU-intensive computing task. By deploying different functional modules on different computing nodes, the computing power of different types of computing nodes can be effectively utilized.

[0110] The distributed computing node message communication data protocol reduces the frequency of information communication between different computing nodes.

[0111] In another specific implementation scenario, the first computing module is a user terminal, which includes a mobile phone, a tablet or a computer, etc., and the second computing module is a server.

[0112] Task allocation between user terminal and server: the user terminal is responsible for completing the virtual character environment perception, path planning and motion control calculation tasks; the server is responsible for completing the motion trajectory generation calculation tasks.

[0113] Data format of information sent by user terminal: The user terminal is responsible for completing real-time computing tasks such as virtual character environment perception, path planning, motion control, etc. The generated message data content is shown in Table 1.

[0114] Data format of information sent by the server: The server is responsible for completing the calculation task of generating the motion trajectory of the virtual character, and the generated message data content is shown in Table 2.

[0115] The collaboration process between the user terminal and the server:

[0116] After receiving the movement instruction of the virtual character, the user terminal:

[0117] (1) Calculate the motion planning path of the virtual character;

[0118] (2) Based on the planned motion path, calculate the path point location that the virtual character is expected to move to within a specified time period;

[0119] (3) Calculate the surrounding voxel data of different points based on the starting point, expected path points, and intermediate interpolation points of the virtual character;

[0120] (4) Encapsulate the data calculated by (1)-(3) into the data format of Table 1 and send it to the server;

[0121] (5) The server generates the motion trajectory of the virtual character, encapsulates it into the data format of Table 2, and sends it to the user terminal.

[0122] (6) After receiving the data in step (5), the user terminal performs the following two computing tasks in parallel:

[0123] (6.1) Queue the virtual character motion data frame sequence into the action frame queue, and control the virtual character to complete the motion frames in the queue in real time;

[0124] (6.2) If the motion completion flag is true, the execution process of this round ends; if it is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory, and jump to the calculation step (1).

[0125] In another specific implementation scenario, the first computing module and the second computing module are different parts of the CPU, such as dividing the CPU into two parts, the first part of the CPU is the first computing module, and the second part of the CPU is the second computing module.

[0126] Task allocation between the first part of the CPU and the second part of the CPU: the first part of the CPU is responsible for completing the virtual character environment perception, path planning and motion control calculation tasks; the second part of the CPU is responsible for completing the motion trajectory generation calculation tasks.

[0127] The data format of the information sent by the first part of the CPU: The first part of the CPU is responsible for completing real-time computing tasks such as virtual character environment perception, path planning, motion control, etc. The generated message data content is shown in Table 1.

[0128] The data format of the information sent by the second part of the CPU: The second part of the CPU is responsible for completing the calculation task of generating the motion trajectory of the virtual character, and the generated message data content is shown in Table 2.

[0129] The collaboration process between the first part of CPU and the second part of CPU:

[0130] After receiving the movement instructions of the virtual character, the first part of the CPU:

[0131] (1) Calculate the motion planning path of the virtual character;

[0132] (2) Based on the planned motion path, calculate the path point location that the virtual character is expected to move to within a specified time period;

[0133] (3) Calculate the surrounding voxel data of different points based on the starting point, expected path points, and intermediate interpolation points of the virtual character;

[0134] (4) Encapsulate the data calculated by (1)-(3) into the data format of Table 1 and send it to the second part of the CPU;

[0135] (5) The second part of the CPU generates the motion trajectory of the virtual character, encapsulates it into the data format of Table 2, and sends it to the first part of the CPU.

[0136] (6) After receiving the data from step (5), the first part of the CPU performs the following two computational tasks in parallel:

[0137] (6.1) Queue the virtual character motion data frame sequence into the action frame queue, and control the virtual character to complete the motion frames in the queue in real time;

[0138] (6.2) If the motion completion flag is true, the execution process of this round ends; if it is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory, and jump to the calculation step (1).

[0139] like Figure 2 As shown, this embodiment also discloses a distributed processing device for interactive motion generated data, including:

[0140] A first calculation module is used to calculate motion task data based on the acquired environment interactive motion data of the virtual character, and to send the motion task data after packaging it in a first set format, and to receive data packaged in a second set format, and to control the interactive motion based on the received data packaged in the second set format;

[0141] The second calculation module is used to calculate the motion trajectory data based on the received data packaged in the first set format, and package the motion trajectory data in the second set format before sending.

[0142] In a specific application scenario, the first computing module may be a CPU or a server, etc., and the second computing module may be a GPU or a user terminal, etc.

[0143] Optionally, the motion task data includes a motion path, surrounding environment voxel data and a motion instruction description.

[0144] Optionally, the motion trajectory data includes a virtual character motion data frame sequence and a motion completion mark.

[0145] Optionally, the step of acquiring the environment interactive motion data of the virtual character and sending it to the first computing module to obtain motion task data includes:

[0146] The first calculation module calculates the motion planning path of the virtual character in response to the motion instruction of the virtual character;

[0147] Calculate the expected path point position of the virtual character within a specified time period based on the motion planning path;

[0148] Obtaining the expected path points and the intermediate interpolation points based on the obtained starting point and expected path point positions of the virtual character;

[0149] According to the starting point, expected path point and intermediate interpolation point of the virtual character, the surrounding voxel data of the starting point, the expected path point and the intermediate interpolation point are calculated.

[0150] Optionally, the first computing module controls the interactive motion based on the received encapsulation data, including:

[0151] Decapsulating the encapsulated data to obtain a virtual character motion data frame sequence and a motion completion mark;

[0152] The virtual character motion data frame sequence is queued and pushed into the action frame queue, and the virtual character is controlled in real time to complete the motion data frames in the queue.

[0153] Optionally, the first computing module controls the interactive motion based on the received encapsulation data, further comprising:

[0154] Determine the true or false value of the movement completion flag;

[0155] If the movement completion flag is true, then the execution process of this round ends;

[0156] If the motion completion flag is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory.

[0157] The electronic device disclosed in this embodiment includes a memory and a processor. The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc.

[0158] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory, so that the electronic device performs all or part of the steps of the interactive motion generation data distributed processing method of each embodiment of the present disclosure.

[0159] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0160] like Figure 3The present invention provides a schematic diagram of the structure of an electronic device according to an embodiment of the present invention, which is suitable for implementing the electronic device in the embodiment of the present invention. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0161] like Figure 3 As shown, the electronic device may include a processing device (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage device into a random access memory (RAM). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM, and RAM are connected to each other through a bus. The input / output (I / O) interface is also connected to the bus.

[0162] Typically, the following devices can be connected to the I / O interface: input devices such as sensors or visual information acquisition devices; output devices such as display screens; storage devices such as tapes, hard disks, etc.; and communication devices. The communication device allows the electronic device to communicate with other devices (such as edge computing devices) wirelessly or by wire to exchange data. Figure 3 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0163] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains 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 through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, all or part of the steps of the distributed processing method for interactive motion generation data of an embodiment of the present disclosure are executed.

[0164] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0165] The computer-readable storage medium disclosed in this embodiment stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the interactive motion generated data distributed processing method of each embodiment of the present disclosure are executed.

[0166] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0167] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0168] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0169] In the present disclosure, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The block diagrams of the devices, devices, equipment, and systems involved in the present disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0170] Additionally, as used herein, "or" used in a list of items beginning with "at least one" indicates a separate list, so that, for example, a list of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the example described is preferred or better than other examples.

[0171] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0172] Various changes, substitutions, and modifications of the techniques described herein may be made without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims of the present disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of events, means, methods, and actions described above. Currently existing or later to be developed processes, machines, manufactures, compositions of events, means, methods, or actions that perform substantially the same functions or achieve substantially the same results as the corresponding aspects described herein may be utilized. Thus, the appended claims include such processes, machines, manufactures, compositions of events, means, methods, or actions within their scope.

[0173] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0174] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A distributed processing method for interactive motion generated data, characterized in that: include: The acquired environment interactive motion data of the virtual character is sent to the first computing module to obtain motion task data; Packaging the motion task data in a first set format and sending the result to a second calculation module to obtain motion trajectory data; Packaging the motion trajectory data in a second set format and sending the result to the first computing module; The first computing module controls the interactive movement based on the received encapsulated data, where the encapsulated data is obtained by encapsulating according to a second set format; The step of acquiring the environment interactive motion data of the virtual character and sending it to the first computing module to obtain motion task data includes: The first calculation module calculates the motion planning path of the virtual character in response to the motion instruction of the virtual character; Calculate the expected path points to which the virtual character will move within a specified time period based on the motion planning path; Obtaining intermediate interpolation points based on the obtained starting point and expected path point of the virtual character; According to the starting point, expected path point and intermediate interpolation point of the virtual character, the surrounding voxel data of the starting point, the expected path point and the intermediate interpolation point are calculated.

2. The distributed processing method for interactive motion generated data according to claim 1, characterized in that: The motion task data includes a motion path, surrounding environment voxel data and a motion instruction description.

3. The distributed processing method for interactive motion generated data according to claim 1, characterized in that: The motion trajectory data includes a virtual character motion data frame sequence and a motion completion mark.

4. The distributed processing method for interactive motion generated data according to claim 1, characterized in that: The first computing module controls the interactive motion based on the received encapsulation data, including: Decapsulating the encapsulated data to obtain a virtual character motion data frame sequence and a motion completion mark; The virtual character motion data frame sequence is queued and pushed into the action frame queue, and the virtual character is controlled in real time to complete the motion data frames in the queue.

5. The distributed processing method for interactive motion generated data according to claim 4, characterized in that: The first computing module controls the interactive motion based on the received encapsulation data, and further includes: Determine the true or false value of the movement completion flag; If the movement completion flag is true, then the execution process of this round ends; If the motion completion flag is false, the starting point of the motion planning path is updated according to the last frame data of the motion trajectory.

6. A distributed processing device for interactive motion generated data, characterized in that: include: A first calculation module is used to calculate motion task data based on the acquired environment interactive motion data of the virtual character, and to send the motion task data after packaging it in a first set format, and to receive data packaged in a second set format, and to control the interactive motion based on the received data packaged in the second set format; a second calculation module, configured to receive data packaged in a first set format, calculate motion trajectory data based on the data packaged in the first set format, and package the motion trajectory data in a second set format before sending; The step of calculating the motion task data based on acquiring the environment interactive motion data of the virtual character includes: The first calculation module calculates the motion planning path of the virtual character in response to the motion instruction of the virtual character; Calculate the expected path points to which the virtual character will move within a specified time period based on the motion planning path; Obtaining intermediate interpolation points based on the obtained starting point and expected path point of the virtual character; According to the starting point, expected path point and intermediate interpolation point of the virtual character, the surrounding voxel data of the starting point, the expected path point and the intermediate interpolation point are calculated.

7. An electronic device, characterized in that: The electronic device comprises: 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 distributed processing method for interactive motion generated data described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, which are used to enable a computer to execute the distributed processing method for interactive motion generated data described in any one of claims 1-5.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the distributed processing method for interactive motion generated data described in any one of claims 1-5 is implemented.

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