Unmanned search and rescue system construction method based on simulation platform

Abstract

The invention belongs to the technical field of unmanned aerial vehicle simulation, and particularly relates to an unmanned search and rescue system construction method based on a simulation platform, and the method comprises the steps: 1, carrying out the personalized modeling of a search and rescue unmanned aerial vehicle; 2, creating behavior logic of the search and rescue unmanned aerial vehicle model; step 3, performing function division on each part of the actual unmanned aerial vehicle, determining the influence of each part on the action, obtaining a performance parameter corresponding to each part, and mapping the performance parameter with each part corresponding to the search and rescue unmanned aerial vehicle model; 4, constructing unmanned control equipment capable of transmitting data with the search and rescue unmanned aerial vehicle model in real time; 5, creating a simulation map for the search and rescue unmanned aerial vehicle model and the unmanned control equipment; and step 6, establishing a carrier, and completing aggregation or deaggregation of the search and rescue unmanned aerial vehicle model and the carrier. According to the method, comprehensive simulation of multi-dimensional factors such as a search and rescue unmanned aerial vehicle model and ground equipment is realized, and guiding significance is provided in the aspects of multi-task cooperation, flight optimization and the like.

Description

Technical Field

[0001] The present invention belongs to the technical field of UAV simulation, and particularly relates to a method for constructing an unmanned search and rescue system based on a simulation platform. Background Art

[0002] In the field of UAV search and rescue, simulation technology not only has high theoretical value but also has important application significance. In the field of emergency rescue, it can identify potential risks in advance, optimize flight paths, and evaluate the durability and anti-interference ability of UAVs in a complex simulation environment, which has irreplaceable practical value. This simulation technology can provide real-time flight data and strategic suggestions for operators, improve the safety, efficiency and response ability of UAV systems in actual operations, and truly promote the wide application and development of UAV industry technology.

[0003] At present, the vast majority of UAV simulation platforms mainly focus on the simulation of single flight tasks, and the simulation of comprehensive factors such as the dynamic cooperation of various equipment carriers and the real-time communication between ground equipment and UAVs is relatively weak. Therefore, the existing UAV search and rescue system simulation technology has the following deficiencies:

[0004] (1) The aggregation and disaggregation problems of UAVs and ground UAV carriers have not been effectively simulated; (2) The operation simulation of unmanned operation equipment and UAVs has insufficient accuracy and it is difficult to provide real-time feedback and task adjustment; (3) Problems such as the difficulty of simulating finding the wounded are large.

[0005] In view of this, the present invention is specifically proposed. Summary of the Invention

[0006] The purpose of the present invention is to overcome the above-mentioned deficiencies of the existing technology and propose a method for constructing an unmanned search and rescue system based on a simulation platform, which realizes the comprehensive simulation of multi-dimensional factors such as search and rescue UAVs and ground equipment.

[0007] In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0008] The present invention provides a method for constructing an unmanned search and rescue system based on a simulation platform, including the following steps:

[0009] Step 1, perform personalized modeling on the search and rescue UAV;

[0010] Step 2, create the behavior logic of the search and rescue UAV model;

[0011] Step 3, divide the functions of each component of the actual UAV, determine the influence of each component on the action, obtain the corresponding performance parameters of each component, and map the performance parameters to the corresponding components of the search and rescue UAV model;

[0012] Step 4: Construct an unmanned control device capable of transmitting data in real time to the search and rescue drone model, and the unmanned control device can control the behavior of the search and rescue drone model;

[0013] Step 5: Creating a simulation map for the search and rescue drone model and unmanned equipment;

[0014] Step 6: Establish a vehicle. The search and rescue drone model and the vehicle can be bound to establish a parent-child relationship, or the parent-child relationship can be released to complete the aggregation or deaggregation of the search and rescue drone model and the vehicle.

[0015] Furthermore, in step 1, the modeling process of the search and rescue drone model is as follows:

[0016] Step 1.1: Based on the engineering drawings or photos of the actual drone, create a three-dimensional model of each component of the search and rescue drone on the simulation platform, and create a texture for each of the three-dimensional models;

[0017] Step 1.2: Combine the 3D models with the textures to form a search and rescue drone model.

[0018] The search and rescue drone model is also provided with a virtual camera and a network communication interface.

[0019] Furthermore, the search and rescue drone model is provided with a sensor system and a GPS system, which can identify the location of the injured in real time through an image processing algorithm.

[0020] Furthermore, the search and rescue drone module also includes a collision detection module.

[0021] Furthermore, in step 2, the behavioral logic includes setting interface parameters, and the interface parameters include thrust, brake idle speed, speed, battery capacity, anti-rollover force coefficient, engine redline idle speed, engine speed, torque, control surface and direction control.

[0022] Furthermore, in step 4, the construction process of the unmanned device is as follows:

[0023] Step 4.1: 3D model the unmanned vehicle and create a texture.

[0024] Step 4.2: Build a network communication interface on the unmanned control device that can communicate with the search and rescue drone model.

[0025] Furthermore, the virtual camera is connected to the unmanned control device to obtain the dynamics of the unmanned rescue aircraft and display it on the unmanned control device.

[0026] Furthermore, the creation process of the simulation map is as follows:

[0027] Step 5.1. Create a map camera, fix its height and direction to a top-down perspective, and synchronize the two-dimensional plane coordinates of the map camera with the world coordinates of the search and rescue drone model;

[0028] Step 5.2: delivering the rendering output of the map camera to the UI control interface of the unmanned device to obtain a simulated map;

[0029] Wherein, an icon or direction indication of the search and rescue drone is superimposed on the simulated map.

[0030] Furthermore, in step 6, the aggregation process of the search and rescue drone model and the vehicle is as follows:

[0031] When the search and rescue drone model is parked on the vehicle, a parent-child relationship is established between the search and rescue drone model and the vehicle so that the two are consistent in spatial coordinates, thus completing the fusion;

[0032] The decomposition process of the search and rescue drone model and the vehicle is as follows:

[0033] When the search and rescue drone model needs to take off, the parent-child relationship between the search and rescue drone model and the vehicle is removed, and the disaggregation is completed.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1) The present invention provides a method for constructing an unmanned search and rescue system based on a simulation platform. By creating a personalized search and rescue drone model, unmanned operating equipment, a simulation map, and components such as a sensor system, a GPS system, and a virtual camera set on the search and rescue drone model on the simulation platform, the method realizes a comprehensive simulation of multi-dimensional factors such as the search and rescue drone model and ground equipment, provides guidance in terms of multi-task collaboration and flight optimization, and solves the problem in the existing technology that it is impossible to effectively simulate the aggregation and deaggregation of search and rescue drones and ground carrying vehicles, as well as the problem of insufficient accuracy in the operation simulation of unmanned operating equipment and drones.

[0036] 2) By setting up a sensor system and a GPS system on the unmanned sensor model, the present invention can realize real-time identification of the location of the wounded and guide the unmanned rescue aircraft to accurately reach the target location for rescue, thus solving the problem of difficulty in simulating the search for the wounded. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are incorporated in and constitute a part of this specification and, together with the description, serve to explain the principles of the invention.

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following briefly introduces the accompanying drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0039] Figure 1 It is a schematic flowchart of the method for constructing an unmanned search and rescue system based on a simulation platform according to the present invention;

[0040] Figure 2 It is a schematic three-dimensional modeling combined structure diagram of each component of the search and rescue UAV model constructed in this embodiment;

[0041] Figure 3 It is a schematic structure diagram of the search and rescue UAV model constructed in this embodiment;

[0042] Figure 4 It is a schematic diagram of the unmanned operation device in this embodiment (where the performance parameters are on the left, the simulated map is in the middle, and the perspectives of the search and rescue UAV and the search perspective are on the right);

[0043] Figure 5 It is a schematic diagram of data transmission between the unmanned operation device and the search and rescue UAV model in this embodiment;

[0044] Figure 6 It is a schematic diagram of the presentation of the search and rescue UAV model and its position in the simulated map in this embodiment;

[0045] Figure 7 It is a schematic diagram of the aggregation of the vehicle and the search and rescue UAV model in this embodiment;

[0046] Figure 8 It is a schematic diagram of the disaggregation of the vehicle and the search and rescue UAV model in this embodiment;

[0047] Figure 9 It is a schematic thermal imaging diagram of the unmanned search and rescue system constructed in this embodiment. Specific embodiments

[0048] Here, the exemplary embodiments will be described in detail. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present invention. On the contrary, they are only examples consistent with some aspects of the present invention detailed in the appended claims.

[0049] Please refer to Figures 1 to 9 , the present invention provides a method for constructing an unmanned search and rescue system based on a simulation platform, including the following steps:

[0050] Step 1: Perform personalized modeling on the search and rescue UAV;

[0051] Step 2: Create the behavior logic of the search and rescue drone model;

[0052] Step 3: Functionally divide the components of the actual drone, determine the impact of each component on the action, obtain the performance parameters corresponding to each component, and map the performance parameters to the components corresponding to the search and rescue drone model;

[0053] Step 4: Construct an unmanned control device capable of transmitting data in real time to the search and rescue drone model, and the unmanned control device can control the behavior of the search and rescue drone model;

[0054] Step 5: Creating a simulation map for the search and rescue drone model and unmanned equipment;

[0055] Step 6: Establish a vehicle. The search and rescue drone model and the vehicle can be bound to establish a parent-child relationship, or the parent-child relationship can be released to complete the aggregation or deaggregation of the search and rescue drone model and the vehicle.

[0056] like Figure 2 and 3 As shown, in step 1, the modeling process of the search and rescue drone model is as follows:

[0057] Step 1.1: Based on the actual UAV engineering drawings or photos, create a 3D model of each UAV component on the simulation platform, and create a texture for each 3D model;

[0058] Step 1.2: Combine the 3D models with the textures to form a search and rescue drone model.

[0059] Among them, the search and rescue drone model is also provided with a virtual camera and a network communication interface (a network communication interface that meets the UDP or TCP protocol).

[0060] like Figure 4 and 5 As shown, in step 4, the construction process of the unmanned control device is as follows:

[0061] Step 4.1: 3D model the unmanned vehicle and create a texture.

[0062] Step 4.2: Build a network communication interface on the unmanned control device that can communicate with the search and rescue drone model (a network communication interface that complies with the UDP or TCP protocol).

[0063] Specifically, a communication link is established, and the real-time data transmission between the unmanned device and the search and rescue UAV is made low-latency by using the communication protocol to achieve efficient data exchange. The search and rescue UAV drops packets to the unmanned device, which responds to the real-time control and feedback of the search and rescue UAV. Moreover, the unmanned device sends data files (control instructions and status information) to the search and rescue UAV to ensure that every time the state of the search and rescue UAV changes, it can be quickly transmitted back to the unmanned device.

[0064] Combined with the actual UAV, in this embodiment, the interface display of the unmanned device includes status information, capacitance, target, position, azimuth, speed, and altitude, etc. The search and rescue UAV includes a sensor and flight control unit and a power system and energy module. The sensor and flight control unit includes lidar / vision / infrared thermal imager / flight control computer; the power system and energy module includes an electric motor, battery capacity, thrust, torque scheduling. Here, it is the same as the structure and application of the actual UAV and control terminal, so it will not be elaborated.

[0065] Further, the virtual camera is connected to the unmanned device and is used to obtain the dynamics of the unmanned rescue aircraft and display them.

[0066] In this embodiment, in order to simulate the first-person perspective of the search and rescue UAV, we need to mount the virtual camera on the search and rescue UAV to synchronize the virtual camera with the search and rescue UAV and capture the perspective of the search and rescue UAV. The first-person perspective video of the search and rescue UAV is transmitted to the unmanned device for display and is displayed through the UI.

[0067] Further, in step 2, the behavior logic includes setting interface parameters, and the interface parameters include thrust, brake idle speed, speed, battery capacity, rollover resistance coefficient, engine redline idle speed, engine speed, torque, control surface, and direction control.

[0068] Specifically, in order to implement the motion logic (behavior logic) of the search and rescue UAV model, it is first necessary to define the interface parameters of the UAV, simulate its motion behavior and energy consumption. Thrust: Represents the driving force generated by the engine of the search and rescue UAV (i.e., the search and rescue UAV model), which is usually directly related to the lift and acceleration of the search and rescue UAV; Brake idle speed: The idle speed value when the brake is in the lowest state, which is related to the response of the braking system; Speed: The flight speed of the search and rescue UAV at any given moment; Battery capacity: Refers to the energy reserve of the search and rescue UAV battery, which affects the flight time and control ability of the search and rescue UAV; Anti-roll force coefficient: Describes the stability of the search and rescue UAV during sharp turns or high-speed flights; Engine redline idle speed: Refers to the maximum safe speed limit of the engine, exceeding which will cause damage; Engine speed: Refers to the rotational speed of the engine, which directly affects the thrust output of the search and rescue UAV; Torque: The rotational force provided by the engine, which affects the turning ability and roll response of the aircraft; Control surface: Used to adjust the flight attitude of the search and rescue UAV; Direction control: Controls the heading angle of the search and rescue UAV.

[0069] Among them, in step 3, the structural design of the search and rescue UAV is crucial for its mission execution. The design of each component directly affects its motion ability, flight stability, and mission execution effect. The following are the function divisions of some main components and their impacts on motion:

[0070] Propulsion system (thrust, engine speed, torque): Affects the acceleration, maximum speed, and climbing ability of the search and rescue UAV. Engine speed and torque directly affect thrust and flight speed.

[0071] Battery and energy management: Battery capacity determines the continuous flight time of the UAV. Battery management needs to monitor the battery's power level and health status, and adjust the flight behavior according to mission requirements to ensure mission completion. During long flights or search processes, the balance between the battery's energy consumption and mission time must be considered.

[0072] Flight control system (control surface, direction control, anti-roll force coefficient): The control surface determines the maneuverability and stability of the search and rescue UAV. The anti-roll force coefficient determines the stability of the UAV during high-speed flights or sharp turns. During the mission, the search and rescue UAV may need to quickly turn or stop suddenly, and the flight control system needs to be able to handle these requirements.

[0073] Sensor system (refers to the thermal imaging sensor or thermal sensing camera): The sensors on the search and rescue UAV determine its environmental perception ability. During search and rescue missions, the sensor data helps the search and rescue UAV identify targets, avoid obstacles, and navigate to the designated location.

[0074] The GPS system helps the search and rescue UAV for precise positioning, while the sensors are used to detect obstacles and identify targets.

[0075] Furthermore, a sensing system and a GPS system are provided on the search and rescue UAV model, and the sensing system can be a thermal imaging sensor or a thermal sensing camera.

[0076] Specifically, mounting a thermal sensing camera on the search and rescue UAV in a simulated environment (simulation platform) mainly involves two aspects of implementation: one is the presentation of the thermal imaging effect itself, and the other is the linkage logic with the health value of the character (the wounded). Add a thermal sensing camera to the search and rescue UAV. Set a health point (HP) attribute on the character, and when the value is lower than 70%, trigger the "enhanced heat signal" or "visible heat source" effect through a script or event mechanism. According to the position and distance between the search and rescue UAV and the wounded in the virtual scene, determine whether the wounded is within the visible range of the thermal sensing camera. If the wounded is within the visible range and its "heat source" is activated, then a bright outline or hot spot will be displayed on the thermal imaging screen of the first-person or auxiliary monitor, facilitating the operator or automatic algorithm to quickly lock the target position. As Figure 9 shown.

[0077] Mounting a thermal sensing camera on the search and rescue UAV in a virtual environment requires technical implementation from two directions: "thermal imaging visual effect" and "linkage with character health value". First, an additional "thermal sensing camera" can be added to the search and rescue UAV in the game or simulation engine, and let it only render a specified layer or material. Create a custom shader to simulate the brightness of different temperature regions with a color gradient (such as a pseudo-color mapping of red-yellow-blue), replacing the visible light image of the ordinary camera; then render this camera to a viewport for the UAV control terminal to view the "thermal imaging" screen in real time in the UI. To make the thermal imaging have a reasonable distribution in the scene, a "heat source value" channel can be added to the material of the character or environmental object, and different pseudo-color brightness or contour strokes can be assigned according to the size of the heat source value in the post-processing stage, thus forming a thermal imaging effect.

[0078] In the character part, a health point (HP) attribute needs to be defined in its script or data structure, and when the value drops below 70%, trigger the "heat source enhancement" state of the character through an event mechanism. For example, the "heat source value" of the character object can be switched from the default or low-temperature state to a high-temperature state, or the custom "heat channel" of the character can be marked as 1 (activated) and 0 (not activated). In this way, when the thermal sensing camera renders, it will read the current high heat signal of the character, and thus more obvious, brighter or more prominent (white) areas will be presented on the screen.

[0079] To determine whether the search and rescue UAV can "see" this character in a high-heat state, it is also necessary to detect the spatial position and orientation relationship between the two in the script: if the character is within the visible cone of the camera (usually calculated through the viewing frustum or simplified viewing angle and distance), and there is no building or obstacle blocking, then the pseudo-color contour or hot spot mark of the character can be drawn in the thermal image.

[0080] As Figure 6 shown, the creation process of the simulated map is as follows:

[0081] Step 5.1: Create a map camera, fix its height and direction to a top-down view, and synchronize the two-dimensional plane coordinates of the map camera with the world coordinates of the search and rescue UAV model;

[0082] Step 5.2: Transfer the rendering output of the map camera to the UI control interface of the unmanned control device to obtain a simulated map;

[0083] Among them, the icon or direction indication of the search and rescue UAV is superimposed on the simulated map.

[0084] Specifically, set a map camera on the simulation platform. This map camera will overlook the entire game scene from a high altitude and present the scene. The world coordinates of the search and rescue UAV need to be converted into the coordinate system of the simulated map, and the X and Z coordinates of the unmanned rescue aircraft are mapped to the X and Y coordinates of the simulated map. Update the position of the search and rescue UAV every frame and display it in real time on the simulated map. According to the real-time position of the search and rescue UAV, map it to the two-dimensional coordinate system of the simulated map and update the icon or mark displayed on the simulated map.

[0085] More specifically, the map camera adopts a top-down view, and adjusts the far plane clipping value so that it can capture a large enough range; for local maps or scenes that require precise local views, orthographic projection can be selected to keep the map in a "2D style" top-down effect.

[0086] When the search and rescue UAV moves in the three-dimensional space (X, Y, Z), the map Cam needs to perform planar following (usually ignoring the Z-axis change or keeping a fixed height on the Z-axis). If the environment is large, the map camera can follow the two-dimensional plane coordinates of the search and rescue UAV in the scene and maintain a certain "camera-target" offset appropriately, so that the aircraft is always at the center of the map view. Bind the rendering view to the rendering target, and create an image control or material panel (i.e., the UI control interface) on the UI to display the real-time image of the map camera. In this way, the "bird's-eye view" of the simulated map can be seen in the interface of the control device.

[0087] A simple indicator is often needed on the simulation map screen. Whether it is a 2D icon or a 3D arrow, the real-time position and orientation of the search and rescue drone must be indicated. By mapping the world coordinates of the search and rescue drone to the coordinates of the simulation map screen, and then rotating the icon according to the orientation of the search and rescue drone, the operator can quickly determine the heading and general movement trend of the search and rescue drone.

[0088] For remote ground stations or control terminals, it is necessary to obtain the real-time position and attitude data of the drone through network protocols (such as UDP / TCP). This data is input into the map following logic to synchronize the camera position and UI icons.

[0089] Keep the camera's X and Y coordinates aligned with the drone's X and Y coordinates, and keep Z fixed at a larger value (such as 1000 or 2000 in a 3D world) to ensure a bird's-eye view of the entire area. For orthographic projection mode, set the appropriate orthographic size to determine the map boundaries visible to the camera. When the drone flies outside the current map range, you can dynamically adjust the camera's position or orthographic size, or keep the camera locked to the drone.

[0090] Display the simulated map on the unmanned operation device to realize simulated drone operation.

[0091] Furthermore, the search and rescue drone module also includes a collision detection module.

[0092] Specifically, the collision detection module is used to monitor in real time whether the search and rescue drone has collided with or is nearing a collision with an obstacle, building, or other aircraft, and to obtain collision parameters (such as position, angle, and speed). Once a collision risk is detected, the module will issue a safety warning or avoidance command to the power and attitude control module of the search and rescue drone model, ensuring that the search and rescue drone can adjust its heading or attitude in time to avoid damage.

[0093] The collision detection module includes a collision layer, which is the physical boundary of the search and rescue drone and is used to handle collision interactions with the environment and other objects. The volume and shape of the search and rescue drone are defined to handle the collision response between the search and rescue drone and the environment. Simplified collision models (such as boxes and cylinders) are used instead of complex geometric models to reduce the computational burden of the physics engine. The collision layer ensures that the search and rescue drone behaves reasonably when interacting with other objects (such as collisions, weightlessness, rollovers, etc.). By defining and dividing the collision layer, computational efficiency can be optimized, computational redundancy can be reduced, and performance can be improved.

[0094] Specifically, collision layers define the collision properties of the search and rescue drone, determining which objects will collide with it or trigger events. By setting different collision layers, you can avoid unnecessary calculations and optimize performance.

[0095] The specific implementation steps of the collision layer are as follows:

[0096] 1) In the editor, open Edit > Project Settings > Tags and Layers, and add new layers (such as "Player", "Vehicle", "Terrain").

[0097] 2) Assign layers to game objects and set the Layer in the Inspector window.

[0098] 3) Set the collision rules: Set the collisions between different objects in Edit > Project Settings > Physics.

[0099] The collision layer should correspond one by one to the appearance of each component. The collision layer also determines its position in the three-dimensional coordinates. Since the components are displayed in three dimensions with a set volume, the vertices of each component are connected together to form the display volume of the component. Suppose the first component consists of four vertices, namely (X1, Y1, Z1), (X2, Y2, Z2), (X3, Y3, Z3), (X4, Y4, Z4), and the four vertices of the corresponding collision layer are respectively (X1, Y1, Z1), (X2, Y2, Z2), (X3, Y3, Z3), (X4, Y4, Z4). And so on, each collision layer wraps the component, enabling the component to interact with the outside world.

[0100] Preferably, the collision layer is based on the principle of collision detection. When a point intersects with a spatial volume, it can be judged as a collision. Let the set of collision blocks of the armored vehicle be P. All the collision blocks within the P set do not collide with each other, but the collision blocks cannot overlap. When the distance between the objects in the collision block set Q and the objects in the P set is less than or equal to 0, a collision occurs.

[0101] When the search and rescue UAV is in normal flight or maneuvering, the power and attitude control module comprehensively adjusts the longitudinal, lateral, and vertical directions of the aircraft according to the thrust, brake idle speed, speed, control surface, and direction control interface parameters. The actual output power is allocated by combining the motor speed, torque, and battery capacity.

[0102] As the search and rescue UAV continues to fly, the energy management and loss calculation module tracks the real-time consumption of the battery or fuel, and evaluates the overall remaining endurance in combination with the thrust demand, environmental factors, and flight time. When the energy of the aircraft is lower than a certain warning threshold, this module issues a reminder, and flight is prohibited when the energy is exhausted.

[0103] During the normal flight or maneuvering of the search and rescue UAV, the power and attitude control module will comprehensively utilize interface parameters such as thrust, brake idle speed, flight speed, control surface commands, and direction control to perform real-time adjustment of the UAV in the longitudinal, lateral, and vertical directions. Specifically, the system will first obtain the current flight state (including attitude, position, speed, remaining energy, etc.) and flight target values (such as desired altitude or speed) from sensors and upper-layer commands, and then convert these targets into scheduling commands for thrust and control surfaces through control algorithms. When the system allocates the actual output power, it will first determine the available power range based on the current rotational speed, torque demand, and battery capacity. Usually, at low load or low flight speed, only partial motor rotational speed is required to provide sufficient lift and thrust; when the UAV performs high-speed maneuvers or carries a heavy load, the motor rotational speed needs to be increased, and correspondingly, the battery power consumption will also accelerate.

[0104] When a certain target torque or thrust needs to be output, the power demand of the motor is estimated based on the current motor rotational speed and the required torque. The required power P = τ·ω is calculated according to the torque τ and angular velocity ω. At the same time, the battery management module will monitor the battery state in real-time cycles, including information such as remaining capacity, current battery voltage, current, and temperature. If the calculated target power exceeds the power range that the battery can safely provide, the motor torque demand will be limited or attenuated, forming a determination of the available power range jointly affected by torque and battery constraints: as long as the power corresponding to the required torque does not exceed the safety upper limit of the current battery, the system will send the torque command to the motor; otherwise, it will be reduced to a safe level.

[0105] As Figure 7 shown, in step 6, the aggregation process of the search and rescue UAV model and the vehicle is as follows:

[0106] The UAV and the vehicle are aggregated through a parent-child relationship. When the UAV is parked on the vehicle, first establish a parent-child connection between the UAV model or physical body and the vehicle to make them consistent in spatial coordinates, thus simulating the state where the UAV and the vehicle are integrated. At this time, the movement of the vehicle will automatically drive the UAV to move together. In order to enable the UAV to take off, it is logically necessary to disconnect its physical connection with the vehicle at an appropriate time, get rid of the restraint of the parent-child relationship, and achieve autonomous lift-off. After landing, re-bind the physical bodies of the UAV and the vehicle, restore the parent-child relationship, and firmly fix the UAV to the vehicle to complete a complete aggregation and disaggregation process;

[0107] As Figure 8 shown, the disaggregation process of the search and rescue UAV model and the vehicle is as follows:

[0108] When building a drone-vehicle interaction system, you can leverage parent-child hierarchical relationships to simulate the process of a drone being mounted on a vehicle in real-world scenarios. The specific implementation strategy is as follows: When a drone is parked on a vehicle, the drone model (or physical body) is first mounted as a child object on the vehicle, ensuring that their local spatial coordinates remain consistent, indicating that the drone is securely attached to the vehicle. At this point, if the vehicle moves or turns, the drone moves with it, creating a visually and physically cohesive effect.

[0109] The specific implementation process is as follows:

[0110] When the drone needs to take off, the script logic dynamically releases the parent-child relationship between the drone and the vehicle, and gives the drone sufficient thrust or lift based on actual flight control requirements (such as motor acceleration, attitude adjustment, etc.), allowing it to break free from the constraints of the vehicle and take off autonomously. During this process, the drone's rigid body resumes its independent motion state, so that it no longer inherits the vehicle's displacement, rotation, or collision body information. When the drone is ready to land on the vehicle, it needs to dynamically calculate the relative position and speed with the vehicle in its flight control program, lower its altitude and speed when approaching the vehicle, and finally smoothly contact the vehicle surface. Subsequently, the logic is called again in the engine to establish a parent-child binding between the drone's rigid body or model and the vehicle again to ensure that the relative position remains fixed.

[0111] Under the same time base t, if the positions and velocities of the two parties in the common coordinate system have been obtained, the relative quantity can be simply calculated as the vector difference: pr(t) = pu(t) - pv(t)

[0112] vr(t)=vu(t)-vv(t)

[0113] Where: pr(t) represents the spatial displacement vector of the drone relative to the vehicle

[0114] vr(t) represents the relative velocity vector of the drone relative to the vehicle

[0115] After calculating relative position and velocity, the drone can plan its actions in the following ways: Predicting trajectory: Inferring the drone's position at the next moment or several moments later based on the vehicle's velocity vv(t), with a lag to allow for the drone to plan its landing path or docking action. Introducing constraints: For example, limiting the relative velocity between the drone and the vehicle to a threshold to avoid collision, or temporarily suspending landing if the vehicle is shaking violently. Control based on the relative coordinate system: Setting the drone's outer loop control target to pr(t)→0, performing real-time error correction at the attitude and thrust levels, ultimately achieving a safe and precise landing or docking.

[0116] The simulation platform of the present invention can be selected from VBS, Unity, DPS, WEB website, etc., which is not limited here.

[0117] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention.

[0118] It should be understood that the present invention is not limited to the content already described above, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A method for constructing an unmanned search and rescue system based on a simulation platform, characterized in that, The following steps are involved: Step 1: Personalize the modeling of the search and rescue drone; Step 2: Create the behavior logic of the search and rescue drone model; Step 3: Functionally divide the components of the actual drone, determine the impact of each component on the action, obtain the performance parameters corresponding to each component, and map the performance parameters to the components corresponding to the search and rescue drone model; Step 4: Construct an unmanned control device capable of transmitting data in real time to the search and rescue drone model, and the unmanned control device can control the behavior of the search and rescue drone model; Step 5: Creating a simulation map for the search and rescue drone model and unmanned equipment; Step 6: Establish a vehicle. The search and rescue drone model and the vehicle can be bound to establish a parent-child relationship, or the parent-child relationship can be released to complete the aggregation or deaggregation of the search and rescue drone model and the vehicle.

2. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 1, wherein In step 1, the modeling process of the search and rescue drone model is as follows: Step 1.1: Based on the engineering drawings or photos of the actual drone, create a three-dimensional model of each component of the search and rescue drone on the simulation platform, and create a texture for each of the three-dimensional models; Step 1.2: Combine the 3D models with the textures to form a search and rescue drone model. The search and rescue drone model is also provided with a virtual camera and a network communication interface.

3. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 2, wherein The search and rescue drone model is provided with a sensor system and a GPS system.

4. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 2, wherein, The search and rescue drone module also includes a collision detection module.

5. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 1, wherein In step 2, the behavior logic includes setting interface parameters, which include thrust, brake idle speed, speed, battery capacity, anti-rollover force coefficient, engine redline idle speed, engine speed, torque, control surface and direction control.

6. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 1, wherein, In step 4, the construction process of the unmanned device is as follows: Step 4.1: 3D model the unmanned vehicle and create a texture. Step 4.2: Build a network communication interface on the unmanned control device that can communicate with the search and rescue drone model.

7. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 6, wherein The virtual camera is connected to the unmanned control device and is used to obtain the dynamics of the unmanned rescue aircraft and display it on the unmanned control device.

8. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 1, characterized in that The process of creating the simulation map is as follows: Step 5.

1. Create a map camera, fix its height and direction to a top-down perspective, and synchronize the two-dimensional plane coordinates of the map camera with the world coordinates of the search and rescue drone model; Step 5.2: delivering the rendering output of the map camera to the UI control interface of the unmanned device to obtain a simulated map; Wherein, an icon or direction indication of the search and rescue drone is superimposed on the simulated map.

9. The method for constructing an unmanned search and rescue system based on a simulation platform according to claim 1, wherein, In step 6, the aggregation process of the search and rescue drone model and the vehicle is as follows: When the search and rescue drone model is parked on the vehicle, a parent-child relationship is established between the search and rescue drone model and the vehicle so that the two are consistent in spatial coordinates, thus completing the fusion; The decomposition process of the search and rescue drone model and the vehicle is as follows: When the search and rescue drone model needs to take off, the parent-child relationship between the search and rescue drone model and the vehicle is removed, and the disaggregation is completed.

Images