Hierarchical External Dynamics Simulation Method and System for Multi-Body Heterogeneity

Abstract

The present invention discloses a hierarchical external dynamics simulation method and system for multi-body heterogeneity, the method comprising the following steps: (1) starting a simulation engine and obtaining a simulation map, rendering a scene, and rendering an unmanned system object 1-N at a specified position on the scene map; (2) obtaining a specified unmanned system dynamics model according to the type of the unmanned system, and instantiating the dynamics model and running the simulation; (3) in the current frame of the simulation, the unmanned system dynamics model obtains dynamics parameter configurations in four ways according to its own type; (4) the simulation engine calculates the next frame state of the unmanned system and updates the unmanned system state. The present invention accelerates the iteration and optimization process of the simulation model and improves development efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned system dynamics simulation, and in particular to a hierarchical external dynamics simulation method and system for multi-body heterogeneity. Background Art

[0002] The rapid development of computer technology, particularly the significant increase in computing power and storage capacity, has made high-precision simulation of complex physical systems possible. Efficient numerical calculation methods and advanced algorithms provide strong support for unmanned system dynamics simulation. Currently, an increasing number of simulation engines and software are capable of fine-grained, high-fidelity unmanned system dynamics simulation, comprehensively simulating the motion patterns and performance of complex systems, providing accurate and reliable support for product design and scientific research.

[0003] However, existing technologies typically use built-in models or code integration to perform dynamic simulations. These solutions have the following drawbacks: first, they are inflexible, with fixed dynamic models and difficulty adjusting model parameters; second, the simulation process is rigid and difficult to adapt to the changing needs of unmanned systems; and finally, integration is difficult, requiring familiarity with the internal logic of the simulation engine to integrate or modify the dynamic model. Summary of the Invention

[0004] In order to solve the above-mentioned problems in the prior art, the present invention proposes a hierarchical external dynamics simulation method and system for multi-body heterogeneity, which controls the setting of the dynamic model through parameter configuration items or files independent of the simulation engine, reduces the intrusion into the simulation engine code, and significantly improves the flexibility and adaptability of multi-body heterogeneous dynamics simulation; and solves the problems existing in the background technology.

[0005] The hierarchical external dynamics simulation method for multi-body heterogeneity of the present invention comprises the following steps:

[0006] (1) The simulation engine starts and obtains the simulation map, renders the scene, and renders the unmanned system objects 1-N at the specified location on the scene map;

[0007] (2) Obtain the specified unmanned system dynamics model according to the type of unmanned system, instantiate the dynamics model and simulate it;

[0008] (3) In the current frame of the simulation, the unmanned system dynamics model obtains the dynamics parameter configuration according to its own type through any of the following methods:

[0009] Method 1: The unmanned system dynamics model is configured according to its own type through the default parameters in the dynamics model;

[0010] Method 2: The unmanned system dynamics model is configured based on its own type using the preset dynamic parameters in the simulation engine;

[0011] Method 3: The unmanned system dynamics model obtains dynamics startup parameters from an external parameter list based on its own type when the simulation engine is running;

[0012] Method 4: The unmanned system dynamics model obtains an external dynamics parameter configuration file based on its own type;

[0013] (4) The simulation engine calculates the next frame state of the unmanned system and updates the state of the unmanned system.

[0014] Furthermore, in step (1), the unmanned system includes a land unmanned system, an air unmanned system, and a marine unmanned system.

[0015] Furthermore, in step (2), the unmanned system dynamics model and the unmanned system virtual model have a one-to-one correspondence, and the correspondence is determined by the type of the unmanned system.

[0016] Furthermore, in step (3), the dynamic parameter configuration includes multiple priority configuration modes including preset parameters, startup parameters and external parameter files.

[0017] Furthermore, in step (3), the priorities of the kinetic parameter configuration methods 1, 2, 3 and 4 are increased in sequence.

[0018] Furthermore, in step (3), the simulation engine includes simulation engine programs such as Unreal Engine 4 and Unity.

[0019] The hierarchical external dynamics simulation system for multi-body heterogeneity of the present invention comprises:

[0020] Simulation engine module: used to render and run simulation scenes, unmanned system virtual models and dynamic models, etc., to realize the simulation of the virtual world;

[0021] Simulation scene module: used to run the virtual world in the simulation engine based on the scenario, including scene map, dynamic and static elements, weather and lighting, etc.

[0022] Unmanned system virtual models: used to simulate unmanned systems running in scenarios, including unmanned vehicles, drones, or unmanned ships;

[0023] Unmanned system dynamics model: a simulation model for the kinematics and dynamics of unmanned systems during movement;

[0024] Dynamics preset parameter module: used to predefine the configuration parameters of the dynamics model based on different unmanned system types and models;

[0025] Dynamic startup parameter module: used to pass the operating parameters when the simulation engine starts. The operating parameters are passed separately for different unmanned system types;

[0026] Dynamic parameter file module: used for unmanned system dynamic parameter configuration files independent of the simulation engine, defined and stored separately for different unmanned system types.

[0027] An electronic device described in the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is loaded into the processor, any one of the hierarchical external dynamics simulation methods for multi-body heterogeneity is implemented.

[0028] The present invention provides a storage medium storing a computer program, wherein the computer program, when executed by a processor, implements any one of the multi-body heterogeneous hierarchical external dynamics simulation methods.

[0029] Beneficial effects: Compared with the prior art, the present invention has the following advantages: the present invention moves the parameters of the dynamic model from the inside of the model to the external configuration file, avoiding frequent modification and recompilation of the core code of the simulation engine, reducing the invasiveness of the code, and making the update and maintenance of the model easier. The present invention can handle a variety of different types of unmanned systems (such as drones, unmanned vehicles, unmanned ships, etc.) and supports the simultaneous simulation of these heterogeneous unmanned systems. By providing a unified interface and parameterization method, the differences between the dynamic models of different unmanned systems are reduced, and the simulation process is simplified. The present invention provides a variety of parameter configuration modes such as preset parameters, startup parameters and parameter files, and users can choose the most appropriate parameter configuration method according to different needs and scenarios. This flexible parameter configuration mode reduces the user's workload in debugging and integrating dynamic models, reduces the cost of debugging and integration, accelerates the iteration and optimization process of the simulation model, and improves development efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is a flow chart of the present invention;

[0031] Figure 2 This is the architecture diagram of the hierarchical external dynamics simulation system of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further explained below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments are only used to illustrate and explain the present invention, and do not limit the scope of implementation of the present invention.

[0033] like Figure 1 As shown, the embodiment of the present invention provides a hierarchical external dynamics simulation method for multi-body heterogeneity, comprising the following steps:

[0034] Step 1: The simulation engine starts and obtains the simulation map, renders the scene, and renders the unmanned system objects 1-N at the specified location on the scene map.

[0035] In the present invention, simulating unmanned systems and dynamic models relies on the operation of a simulation engine, such as Unreal Engine 4 or Unity. The simulation engine is started and begins rendering the simulation scene. Based on the simulation scene's configuration information, a simulation map is acquired and rendered. Based on the simulation map, lighting, weather, and dynamic and static elements are rendered to form a simulation of the underlying world. Simultaneously, a virtual model of the unmanned system is instantiated and rendered at a specified location within the simulation map. The scenario configuration can include different types and quantities of unmanned systems, but this is not limited by the present invention.

[0036] The unmanned systems and intelligent unmanned systems mentioned in this invention can be divided into the following types according to their spatial scope and application fields:

[0037] a. Land unmanned systems: These systems primarily operate on land, including but not limited to reconnaissance unmanned vehicles, transport unmanned vehicles, combat unmanned vehicles, obstacle clearance unmanned vehicles, bomb disposal unmanned vehicles, and unmanned vehicle formation and command systems;

[0038] b. Aerial unmanned systems: Aerial unmanned systems mainly include single drone platforms and drone clusters;

[0039] c. Marine unmanned systems: Marine unmanned systems include two categories: surface unmanned systems and underwater unmanned systems.

[0040] Different types of unmanned systems result in different parameters in the dynamics model. These include physical differences such as mass, size, and shape, as well as variations in motion characteristics such as maximum speed, acceleration, and turning radius. To accurately simulate and control different types of unmanned systems, the parameters of the dynamics model must be customized and optimized for each system's characteristics.

[0041] In one embodiment, launching the simulation engine involves multiple steps. First, ensuring the compatibility of all software and system environments, such as using specific versions of Visual Studio and Python, and a version of Carla compatible with UE4, is required. The launch process begins by configuring environment variables to ensure all necessary dependencies and paths are correctly set. Next, a series of build commands, such as make setup, are executed through command-line tools, cloning the latest asset repository, overwriting the existing content. Subsequently, the library files are compiled, a solution file (.sln) is generated, and the source code is compiled using an IDE such as Visual Studio.

[0042] Step 2: Obtain the specified unmanned system dynamics model according to the unmanned system type, instantiate the dynamics model and run the simulation.

[0043] After the unmanned system virtual model is rendered, the unmanned system dynamics model corresponding to the unmanned system type is found and instantiated based on the unmanned system type. Generally, there is a one-to-one correspondence between the unmanned system dynamics model and the unmanned system virtual model. This correspondence is determined by the unmanned system type, which is generally determined when the virtual model is defined.

[0044] In one embodiment, for different types of unmanned systems, it is first necessary to select an appropriate dynamics model based on their characteristics. For example, for an unmanned helicopter, a nonlinear flight dynamics model that meets real-time simulation requirements can be established. For a ground-based unmanned platform, a four-wheel independent drive model can be used, and the kinematic model can be simplified, considering only translation in the x and y directions and yaw in the z direction, while ignoring translation, pitch, and roll in the z direction. This model can more accurately simulate the movement of the ground-based unmanned platform on a flat surface.

[0045] After obtaining a suitable dynamics model, the model needs to be instantiated. This step involves setting the model's specific parameters, such as mass, size, and shape, according to the specifications of the actual unmanned system. For example, a vehicle dynamics model can be built within UE4 to provide a complete vehicle dynamics model and improve simulation accuracy. Instantiation also involves configuring the sensor and actuator models of the unmanned system. These models need to match the actual hardware to ensure that the simulation environment accurately reflects real-world physical phenomena.

[0046] Step 3: In the current frame of the simulation, the unmanned system dynamics model obtains the dynamics parameter configuration through any of the following methods according to its own type.

[0047] The unmanned system dynamics model defines the kinematics and dynamics of a given unmanned system, calculating the appropriate response in real time based on the system's current state and control commands. For example, if a ground-based unmanned system is traveling at 50 kilometers per hour and a 230-N torque is applied to the left turn, the system's expected attitude, roll, and speed will be determined. This response varies based on the system's inherent properties (such as weight, wheelbase, and wheel type) and environmental factors (such as ground surface properties). Therefore, all kinematic and dynamic system properties are unified into dynamics parameter configurations.

[0048] Method 1: The unmanned system dynamics model is configured according to its own type through the default parameters in the dynamics model.

[0049] The default dynamics model parameter configurations provided by the simulation engine are designed to allow the model to run without specific tuning. These parameters are typically derived from extensive experimental data and theoretical analysis and represent the average behavior of a class of unmanned systems in typical environments.

[0050] In one embodiment, the vehicle is configured as a heavy-duty, soft-suspension off-road vehicle, and its default dynamic parameters may be: Weight: The vehicle weight is 2420 kg. 0-60 mph: The acceleration time is approximately 8 seconds. Top Speed: The maximum speed is approximately 115 miles per hour.

[0051] Method 2: The unmanned system dynamics model is configured based on its own type using the preset dynamic parameters in the simulation engine.

[0052] While the simulation engine provides default dynamic model parameters, users can often adjust these parameters to meet specific application requirements. This flexibility allows users to simulate unmanned system behavior under specific conditions or fine-tune the model to improve simulation accuracy.

[0053] During the simulation engine operation, the preset dynamic parameter configuration, environmental condition factors and current unmanned system status data are input in real time at each frame and the next frame status of the unmanned system is calculated.

[0054] In the simulation engine, dynamic parameters are pre-set. These parameters define the physical behavior of unmanned systems (such as drones and autonomous vehicles), such as mass, velocity, acceleration, and steering angle. At the beginning of each frame (i.e., each time step in the simulation), the simulation engine reads these preset dynamic parameters to ensure that the unmanned system's motion conforms to physical laws and design requirements.

[0055] Environmental conditions include wind speed, direction, temperature, and humidity, all of which can affect the performance and behavior of unmanned systems. The simulation engine needs to acquire this environmental data in real time and use it as input to simulate real-world environmental impacts in the simulation.

[0056] The current state data of the unmanned system includes the system's current position, velocity, acceleration, attitude (for aerial unmanned systems), and other state information. This data is usually calculated by the simulation engine in the previous frame, or in actual applications, is transmitted in real time by the actual sensors of the unmanned system.

[0057] The simulation engine allows users to dynamically adjust dynamic parameters based on different application scenarios and requirements. For example, in the CARLA simulation platform, parameters can be applied to the vehicle in the next frame through the apply_physics_control method, providing flexible control over the vehicle performance simulation.

[0058] However, it should be noted that the preset dynamic parameter configurations stored in the simulation engine need to be set in advance before the simulation is run, and the parameter configurations cannot be modified during the simulation.

[0059] Method 3: The unmanned system dynamics model obtains dynamics startup parameters from an external parameter list based on its own type when the simulation engine is running.

[0060] In this invention, to decouple the dynamics simulation model from the preset dynamics parameter configuration, a higher-priority external dynamics parameter configuration overrides the preset dynamics parameter configuration. When the simulation engine starts, startup parameters are optionally provided for a specific unmanned system type to flexibly configure the dynamics simulation model parameters for that system. In this case, the startup parameter configuration has higher priority, overriding the preset dynamics model parameters for that system. This allows for customizing the motion patterns of the unmanned system without modifying the dynamics simulation model or the preset dynamics parameter configuration.

[0061] At the same time, startup parameters have more fine-grained configuration properties, allowing you to flexibly choose which parameters can override preset parameters and which can remain preset. For example, if the preset dynamic parameters have four parameter configurations: A, B, C, and D, the startup parameters can choose to only overwrite the configurations of parameters A and B, or only overwrite the configurations of parameters B and C, while retaining the validity of the other parameter configurations. This step can effectively debug and customize the kinematics and dynamics of unmanned systems.

[0062] The dynamics parameters are not hard-coded within the dynamics model but are stored in a parameter list external to the simulation engine. This allows these parameters to be adjusted at any time without modifying the dynamics model code, thus increasing the flexibility and maintainability of the dynamics model. The simulation engine loads and applies these parameters before the simulation begins.

[0063] In one embodiment, the parameter list may be displayed in the following manner:

[0064]

[0065] It should be noted that the way the simulation engine obtains parameter configuration from the parameter list needs to be set in advance before the simulation runs, and the parameter configuration cannot be modified during the simulation run.

[0066] Method 4: The unmanned system dynamics model obtains an external dynamics parameter configuration file based on its own type.

[0067] More preferably, the present invention supports the highest priority external dynamic parameter configuration file to customize the kinematics and dynamics of the unmanned system, reducing the tediousness of manually entering specific startup parameters in method three, further reducing debugging and modification costs, and improving the flexibility of the overall system.

[0068] The external dynamics parameter configuration file has the highest priority, and its one-to-one correspondence with the unmanned system is specified by the simulation engine startup parameter configuration, which specifies the specific unmanned system type and the corresponding external dynamics parameter configuration file path.

[0069] When the simulation engine is running, it dynamically retrieves the corresponding dynamic parameters from an external parameter configuration file based on the type of unmanned system being used. At each simulation state, the simulation engine loads and applies these parameters to ensure accurate and real-time simulation. Therefore, using an external configuration file allows for convenient updating and optimization of dynamic parameters to improve simulation accuracy.

[0070] In one embodiment, the external dynamic parameter configuration file corresponding to the unmanned vehicle unmanned system model AJ-80 is the aj80.param file. When the simulation engine is started, a command such as --arg aj-80= / path / to / aj80.param is specified. The simulation engine dynamics module reads the parameter configuration from the specified file.

[0071] Similarly, the external dynamics parameter configuration file also has fine-grained configuration properties, which allows flexible selection of which parameters can override the preset parameters, which parameters are obtained from the startup parameters, and which parameters remain the preset parameters.

[0072] It should be emphasized again here that the priorities of the four methods of obtaining dynamic parameters are increasing in sequence, that is, the priority of method four is greater than that of method three, the priority of method three is greater than that of method two, and so on.

[0073] When both an external dynamics parameter configuration file and an external parameter list are obtained at the same time, the external dynamics parameter configuration file will overwrite the parameter configuration in the external parameter list, and you can flexibly choose which preset parameters to overwrite.

[0074] Step 4: The simulation engine calculates the next frame state of the unmanned system and updates the state of the unmanned system.

[0075] Based on the dynamic parameters, environmental conditions, and the state of the unmanned vehicle in the current frame, the simulation engine uses a physics engine (such as Niagara, the physics engine in UE4) to calculate the state of the unmanned vehicle in the next frame. This process involves solving physics equations, such as Newton's laws of motion, and possibly control algorithms to predict the position and velocity of the unmanned vehicle in the next frame.

[0076] Dynamic model parameters can be set not only at the start of a simulation but also updated in real time during the simulation itself, using external dynamic parameter configuration files. For example, parameters such as tire friction coefficient, vehicle mass, and air resistance can be adjusted to simulate different environmental conditions and operating scenarios.

[0077] After the calculation is complete, the simulation engine updates the state of the unmanned system, and this state information is used to calculate the next frame. In this way, each frame is updated based on the results of the previous frame, thus achieving continuous dynamic simulation.

[0078] The embodiment of the present invention also provides a hierarchical external dynamics simulation system for multi-body heterogeneity, such as Figure 2 As shown, including:

[0079] Simulation engine module: used to render and run simulation scenes, unmanned system virtual models and dynamic models, etc., to realize the simulation of the virtual world;

[0080] Simulation scene module: used to run the virtual world in the simulation engine based on the scenario, including scene map, dynamic and static elements, weather and lighting, etc.

[0081] Unmanned system virtual models: used to simulate unmanned systems running in scenarios, including unmanned vehicles, drones, or unmanned ships;

[0082] Unmanned system dynamics model: a simulation model for the kinematics and dynamics of unmanned systems during movement;

[0083] Dynamics preset parameter module: used to predefine the configuration parameters of the dynamics model based on different unmanned system types and models;

[0084] Dynamic startup parameter module: used to pass the operating parameters when the simulation engine starts. The operating parameters are passed separately for different unmanned system types;

[0085] Dynamic parameter file module: used for unmanned system dynamic parameter configuration files independent of the simulation engine, defined and stored separately for different unmanned system types.

Claims

1. A hierarchical external dynamics simulation method for multi-body heterogeneity, characterized in that: The following steps are involved: (1) The simulation engine starts and obtains the simulation map, renders the scene, and renders unmanned system objects 1-N at the specified location on the scene map; unmanned systems include land unmanned systems, air unmanned systems, and marine unmanned systems; (2) Obtain the specified unmanned system dynamics model according to the unmanned system type, instantiate the dynamics model and simulate it; the unmanned system dynamics model and the unmanned system virtual model have a one-to-one correspondence, and the correspondence is determined by the unmanned system type; (3) In the current frame of the simulation, the unmanned system dynamics model obtains the dynamics parameter configuration according to its own type through any of the following methods: Method 1: The unmanned system dynamics model is configured according to its own type through the default parameters in the dynamics model; Method 2: The unmanned system dynamics model is configured from the preset dynamics parameters in the simulation engine according to its own type; the parameters are adjusted according to specific application requirements; the preset dynamics parameter configuration, environmental condition factors and current unmanned system status data are input in real time at each frame during the simulation engine operation and the next frame state of the unmanned system is calculated; Among them: In the simulation engine, the dynamics parameters are pre-set, and the parameters define the physical behavior of the unmanned system; at the beginning of each frame, that is, each time step in the simulation, the simulation engine will read the preset dynamic parameters; environmental condition factors include wind speed, wind direction, temperature, and humidity; the current unmanned system status data includes the current position, speed, acceleration, and attitude of the unmanned system; calculated by the simulation engine in the previous frame, or in actual applications, transmitted back in real time by the actual sensors of the unmanned system; the simulation engine allows users to dynamically adjust the dynamics parameters according to different application scenarios and requirements; the parameter configuration cannot be modified during the simulation operation; Method 3: The unmanned system dynamics model obtains dynamics startup parameters from an external parameter list based on its own type when the simulation engine is running; Method 4: The unmanned system dynamics model obtains an external dynamics parameter configuration file based on its own type. The priority of the four methods for obtaining dynamic parameters is ascending, that is, method 4 has a higher priority than method 3, method 3 has a higher priority than method 2, and so on. When both an external dynamics parameter configuration file and an external parameter list are obtained at the same time, the external dynamics parameter configuration file will overwrite the parameter configuration in the external parameter list, and the user can flexibly choose which preset parameters to overwrite. (4) The simulation engine calculates the next frame state of the unmanned system and updates the state of the unmanned system.

2. A simulation system for the multi-body heterogeneous hierarchical external dynamics simulation method according to claim 1, characterized in that: include: Simulation engine module: used to render and run simulation scenes, unmanned system virtual models and dynamic models to realize simulation of the virtual world; Simulation scenario module: A virtual world running in the simulation engine based on the scenario, including scene maps, dynamic and static elements, weather and lighting; Unmanned system virtual models: used to simulate unmanned systems running in scenarios, including unmanned vehicles, drones, or unmanned ships; Unmanned system dynamics model: a simulation model for the kinematics and dynamics of unmanned systems during movement; Dynamics preset parameter module: used to predefine the configuration parameters of the dynamics model based on different unmanned system types and models; Dynamics startup parameter module: used to pass operating parameters when the simulation engine starts. The operating parameters are passed separately for different unmanned system types. Dynamic parameter file module: used for unmanned system dynamic parameter configuration files independent of the simulation engine, defined and stored separately for different unmanned system types.

3. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is loaded into a processor, the multi-body heterogeneous hierarchical external dynamics simulation method according to claim 1 is implemented.

4. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the multi-body heterogeneous hierarchical external dynamics simulation method according to claim 1 is implemented.

Images