Low-altitude emergency rescue data processing method and device for 5G low-delay communication

Abstract

The invention provides a low-altitude emergency rescue data processing method and device for 5G low-delay communication, and relates to the field of data processing. The method comprises the following steps: acquiring a first flight direction of a first unmanned aerial vehicle and a second flight direction of a second unmanned aerial vehicle; determining a first collision body corresponding to the first unmanned aerial vehicle and a second collision body corresponding to the second unmanned aerial vehicle according to the first flight direction and the second flight direction; generating a collision judgment result based on the first collision body, the second collision body, the real-time position data corresponding to the first unmanned aerial vehicle and the real-time position data corresponding to the second unmanned aerial vehicle; and if it is determined that the collision judgment result indicates that the first unmanned aerial vehicle and the second unmanned aerial vehicle will collide, planning an avoidance path between the first unmanned aerial vehicle and the second unmanned aerial vehicle according to the real-time position data corresponding to the first unmanned aerial vehicle and the real-time position data corresponding to the second unmanned aerial vehicle. By implementing the technical scheme provided by the invention, the risk of collision of the unmanned aerial vehicle can be reduced, and low-altitude emergency rescue of the unmanned aerial vehicle is facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and specifically to a method and device for processing low-altitude emergency rescue data for 5G low-latency communication. Background Art

[0002] In low-altitude emergency rescue scenarios, multiple drones coordinating to perform tasks has become an important technical means. However, with the increase in the number of drones and the complexity of flight missions, the problem of collisions between drones has become increasingly prominent, becoming a key factor restricting the efficiency and safety of low-altitude emergency rescue.

[0003] In the prior art, drones often rely on preset flight paths and simple obstacle avoidance algorithms when performing missions. However, in low-altitude environments, due to complex terrain, numerous obstacles, and changing flight conditions, traditional obstacle avoidance algorithms are difficult to effectively respond to. In addition, when multiple drones perform missions at the same time, the risk of collision between drones increases significantly due to the intersection and overlap of flight paths. Therefore, the above method is likely to cause drone collisions, which is not conducive to low-altitude emergency rescue of drones.

[0004] Therefore, there is an urgent need for a low-altitude emergency rescue data processing method and device for 5G low-latency communication. Summary of the invention

[0005] The present application provides a 5G low-latency communication low-altitude emergency rescue data processing method and device, which can reduce the risk of drone collision and facilitate low-altitude emergency rescue of drones.

[0006] In a first aspect of the present application, a method for processing low-altitude emergency rescue data for 5G low-latency communication is provided, the method comprising: obtaining a first flight direction of a first UAV and a second flight direction of a second UAV, the first UAV and the second UAV being any two UAVs among multiple UAVs that perform low-altitude emergency rescue tasks through 5G low-latency communication; determining a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV according to the first flight direction and the second flight direction; generating a collision judgment result based on the first collision body, the second collision body, and real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV; if it is determined that the collision judgment result indicates that the first UAV and the second UAV will collide, planning an avoidance path between the first UAV and the second UAV according to the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV.

[0007] By adopting the above technical solutions, through 5G low-latency communication, drones can share flight direction and location data in real time, ensuring the timeliness and accuracy of information. This helps to quickly identify potential collision risks. By determining the collision body based on the flight direction of the drone and making collision judgments based on real-time location data, potential collision threats can be discovered in advance, so that preventive measures can be taken. Once the risk of collision is determined, the system can quickly plan an avoidance path to ensure that the drones can safely avoid each other and continue to perform their missions. This collaborative obstacle avoidance capability is essential to maintaining the continuity and efficiency of rescue missions. By reducing the risk of collision between drones, mission interruptions or delays caused by collisions can be avoided, thereby improving the overall efficiency of mission execution. Collision avoidance not only protects the drone itself, but also ensures the safety of rescue personnel and equipment, and reduces the risks that may be caused by drone accidents. Therefore, the risk of drone collisions can be reduced, facilitating low-altitude emergency rescue by drones.

[0008] Optionally, determining a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV according to the first flight direction and the second flight direction specifically includes: determining a flight center point of the first UAV; taking the flight center point as the origin and the first flight direction as any one of a plurality of coordinate axis directions to construct a three-dimensional flight coordinate system; determining a collision module of the first UAV in each of the coordinate axis directions, the first collision body consisting of a plurality of the collision modules; calculating a target edge point of the collision module in each of the coordinate axis directions; extending a preset length toward the first flight direction according to a side surface where the target edge point in the first flight direction is located to obtain a convex body module, the convex body module being connected to the collision module in the coordinate axis direction corresponding to the first flight direction, the preset length being proportional to the flight speed of the first UAV; constructing the first collision body according to the target edge points of the convex body module and the collision module.

[0009] By adopting the above technical solution, the position and flight direction of the drone in space can be accurately described by determining the flight center point of the drone and constructing a three-dimensional flight coordinate system with this point as the origin. This coordinate system-based description method makes the determination of the collision body more accurate and reliable. The collision body is decomposed into multiple collision modules, each module corresponding to a collision area in the direction of a coordinate axis. This modular design not only simplifies the calculation process of the collision body, but also allows the shape and size of the collision body to be flexibly adjusted according to the actual size and flight characteristics of the drone. By calculating the target edge points of the collision module in each coordinate axis direction and extending the convex body module of a preset length according to the flight direction, a dynamic collision body that matches the flight speed and direction of the drone can be constructed. This dynamic adaptability ensures that the collision body can accurately reflect the actual collision risk of the drone during flight. The precise determination and dynamic adjustment of the collision body help to detect potential collision threats in advance and take corresponding avoidance measures. This can not only avoid collisions between drones, but also ensure the safe flight of drones in complex environments. Although this method involves multiple steps and calculation processes, the calculation efficiency can be significantly improved through modular design and simplification of the coordinate system. At the same time, the use of modern computing technology and algorithm optimization can further shorten the calculation time and ensure real-time requirements.

[0010] Optionally, the collision module for determining the first UAV in each of the coordinate axis directions specifically includes: determining a first collision module in a first flight axis direction, the first flight axis direction is the same as the first flight direction, and the first collision module includes a low-speed rotor corresponding to the first UAV flying in the first flight direction; determining a second collision module in a second flight axis direction, the second flight axis direction is opposite to the first flight direction, and the second collision module includes a high-speed rotor corresponding to the first UAV flying in the first flight direction; determining a first side collision module in a first horizontal axis direction, the first horizontal axis direction is perpendicular to the first flight direction and parallel to a preset horizontal plane, and the first side collision module includes the left rotor of the first UAV; determining a second horizontal axis direction A second side collision module in the horizontal axis direction, the second horizontal axis direction is perpendicular to the first flight direction and parallel to the preset horizontal plane, the second horizontal axis direction is opposite to the first horizontal axis direction, and the second side collision module includes the right rotor of the first UAV; determine the first middle collision module in the first vertical axis direction, the first vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, and the first middle collision module includes the top cover of the first UAV; determine the second middle collision module in the second vertical axis direction, the second vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, the second vertical axis direction is opposite to the first vertical axis direction, and the second middle collision module includes the bottom landing gear of the first UAV.

[0011] By adopting the above technical solution, the collision characteristics of the drone can be described more accurately by subdividing the collision body of the drone into collision modules in multiple directions and considering the rotors, canopies, landing gear and other components in different directions respectively. This accuracy is crucial for predicting and avoiding collisions. The method not only considers the collision risk of the drone in the flight direction, but also considers the collision risk in the horizontal and vertical directions. This comprehensive consideration makes the determination of the collision body more complete and accurate. When determining the collision module, the difference in the rotor speed of the drone in different flight directions is considered, which reflects the dynamic characteristics of the drone during flight. This consideration of dynamic characteristics helps to more accurately assess the collision risk of the drone. By accurately determining the collision module in each direction, the possibility of collision between the drone and other objects or drones can be more accurately predicted, so that corresponding avoidance measures can be taken in advance. This helps to enhance the flight safety of the drone and reduce the risk of collision accidents.

[0012] Optionally, the calculation of the target edge point of the collision module in each coordinate axis direction specifically includes: determining a first collision point and a second collision point in the target coordinate axis direction, the first collision point and the second collision point are any two collision points on the target collision module, the target coordinate axis direction is any one of a plurality of coordinate axis directions, and the target collision module is any one of a plurality of collision modules; determining a first projection point of the first collision point in the target coordinate axis direction, and a second projection point of the second collision point in the target coordinate axis direction; calculating a first distance from the first projection point to the flight center point, and a second distance from the second projection point to the flight center point; if it is determined that the first distance is greater than the second distance, determining the first collision point as the target edge point.

[0013] By adopting the above technical solution, by determining the first collision point and the second collision point in the direction of the target coordinate axis and calculating the distance from their projection point in the direction of the target coordinate axis to the flight center point, the farthest boundary point of the collision module in this direction, that is, the target edge point, can be accurately found. This accuracy is crucial for building an accurate collision body model. The method determines the target edge point through simple geometric calculations, avoiding complex mathematical formulas and algorithms. This makes the method more concise, easy to understand and implement. The method is not only applicable to the currently described UAV collision body determination problem, but can also be extended to other similar scenes and objects. Since the method only involves simple geometric calculations and comparison operations, the calculation efficiency is high. This helps to quickly determine the target edge point of the collision body in scenes with high real-time requirements, so that corresponding avoidance measures can be taken in time.

[0014] Optionally, the generating of the collision judgment result based on the first collision body, the second collision body, the real-time position data corresponding to the first UAV, and the real-time position data corresponding to the second UAV specifically includes: calculating the first spatial volumes corresponding to the first collision body at multiple consecutive moments; screening out a first target spatial volume from the multiple first spatial volumes, the first spatial volume of the first target spatial volume at the target first moment is greater than a preset first threshold, the preset first threshold is determined based on the multiple first spatial volumes, and the target first moment is any one of the multiple consecutive moments; determining the first target collision body corresponding to the first target spatial volume; calculating the second collision body A second spatial volume corresponding to each of the multiple continuous moments; from the multiple second spatial volumes, a second target spatial volume is screened out, the second spatial volume of the second target spatial volume at the target second moment is greater than a preset second threshold, the preset second threshold is determined according to the multiple second spatial volumes, and the target second moment is any one of the multiple continuous moments; a second target collision body corresponding to the second target spatial volume is determined; after a preset time period, a first real-time position of the first target collision body and a second real-time position of the second target collision body at the same moment are obtained; it is determined whether the first target collision body and the second target collision body will overlap, and a collision judgment result is generated.

[0015] By adopting the above technical solution, the method can dynamically monitor and predict the changes of the collision body by calculating the spatial volume of the collision body at multiple consecutive moments and screening out the target spatial volume. This dynamicity helps to discover potential collision risks in advance and provide sufficient time for taking avoidance measures. By setting preset thresholds and determining these thresholds based on multiple spatial volumes, it can be ensured that the screened target spatial volume is real and significant. This helps to reduce false alarms and missed alarms and improve the accuracy of collision judgment. The method not only considers the position and size of the collision body at the current moment, but also predicts its future change trend through continuous moment monitoring. This comprehensive consideration makes the collision judgment more reliable and accurate. The real-time position of the target collision body at the same moment is obtained after a preset time period, and it is determined whether they will overlap, which ensures the real-time nature of the collision judgment. This real-time nature is crucial for rapid response and collision avoidance.

[0016] Optionally, planning the avoidance path between the first UAV and the second UAV based on the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV specifically includes: obtaining the collision time and collision position data of the first target collision body and the second target collision body; calculating the interval distance between the real-time position data of the first UAV and the collision position data; calculating the avoidance speed of the first UAV based on the interval distance and the current flight speed of the first UAV; and planning the avoidance path of the first UAV relative to the second UAV according to the avoidance speed.

[0017] By adopting the above technical solution, the method can accurately determine the potential collision point by obtaining the collision moment and collision position data. This helps to ensure that the planning of the avoidance path is based on accurate information, thereby improving the success rate of avoidance. The method relies on real-time position data to calculate the interval distance and avoidance speed, which ensures that the planning of the avoidance path is timely. During the flight of the drone, rapid response and timely adjustment of the path are essential to avoid collisions. The avoidance speed is calculated based on real-time position data and current flight speed, so that the drone can dynamically adjust its flight strategy according to changes in the environment. This dynamic adaptability helps the drone fly safely in complex environments. By planning the avoidance path, the method can significantly reduce the risk of collision between drones. This is essential to ensure the safety of drones in critical tasks such as low-altitude emergency rescue. The planning of the avoidance path not only takes safety into account, but also minimizes the impact of the avoidance action on the flight efficiency of the drone. By reasonably calculating the avoidance speed, the flight efficiency of the drone can be maintained as much as possible while ensuring safety.

[0018] Optionally, the method also includes: correcting the avoidance path according to the second flight direction to generate a low-altitude emergency rescue path including the avoidance direction; sending the low-altitude emergency rescue path including the avoidance direction to the first UAV to control the first UAV to perform low-altitude emergency rescue according to the low-altitude emergency rescue path including the avoidance direction.

[0019] By adopting the above technical solution, by correcting the avoidance path, it can be ensured that the generated low-altitude emergency rescue path not only avoids potential collision risks, but also meets the actual needs of emergency rescue as much as possible. This optimization helps to improve the efficiency and success rate of emergency rescue. In the process of emergency rescue, it is very important to ensure the safety of the drone. By correcting the avoidance path and generating a path with a clear avoidance direction, the risk of the drone colliding with other obstacles during flight can be significantly reduced, thereby improving the safety of flight. The method allows the avoidance path to be flexibly adjusted according to the second flight direction. This flexibility helps the drone to quickly adapt to the complex and changing emergency rescue environment and ensure the smooth completion of the mission. Emergency rescue often requires a quick response in an emergency. By calculating and adjusting the avoidance path in real time, the method can ensure that the drone can quickly generate and execute a low-altitude emergency rescue path including an avoidance direction after receiving the mission instruction, thereby achieving a quick response to the emergency. By optimizing the path and clarifying the avoidance direction, the drone can perform emergency rescue tasks more efficiently. This helps to reduce flight time, increase the speed of task completion, and reduce resource consumption during emergency rescue.

[0020] In a second aspect of the present application, a low-altitude emergency rescue data processing device for 5G low-latency communication is provided, the low-altitude emergency rescue data processing device comprising an acquisition module and a processing module, wherein the acquisition module is used to acquire a first flight direction of a first UAV and a second flight direction of a second UAV, the first UAV and the second UAV being any two UAVs among multiple UAVs that perform low-altitude emergency rescue tasks through 5G low-latency communication; the processing module is used to determine a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV according to the first flight direction and the second flight direction; the processing module is also used to generate a collision judgment result based on the first collision body, the second collision body, and the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV; the processing module is also used to plan an avoidance path between the first UAV and the second UAV according to the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV if it is determined that the collision judgment result indicates that the first UAV and the second UAV will collide.

[0021] In the third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs the method described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method described above is executed.

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: Through 5G low-latency communication, drones can share flight direction and location data in real time, ensuring the timeliness and accuracy of information. This helps to quickly identify potential collision risks. By determining the collision body based on the flight direction of the drone and making collision judgments based on real-time location data, potential collision threats can be discovered in advance so that preventive measures can be taken. Once a collision risk is determined, the system can quickly plan an avoidance path to ensure that drones can safely avoid each other and continue to perform their missions. This collaborative obstacle avoidance capability is essential to maintaining the continuity and efficiency of rescue missions. By reducing the risk of collision between drones, mission interruptions or delays caused by collisions can be avoided, thereby improving the overall efficiency of mission execution. Collision avoidance not only protects the drone itself, but also ensures the safety of rescue personnel and equipment, and reduces the risks that may be caused by drone accidents. Therefore, the risk of drone collisions can be reduced, facilitating low-altitude emergency rescue by drones. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of a method for processing low-altitude emergency rescue data for 5G low-latency communication provided in an embodiment of the present application; Figure 2 Another flowchart of a method for processing low-altitude emergency rescue data for 5G low-latency communication provided in an embodiment of the present application; Figure 3 A module schematic diagram of a low-altitude emergency rescue data processing device for 5G low-latency communication provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0025] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0026] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0028] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] In low-altitude emergency rescue scenarios, the coordinated operation of multiple drones has become an indispensable technical means, greatly improving the efficiency of mission execution. However, with the surge in the number of drones and the increasing complexity of flight missions, the problem of collisions between drones has become increasingly prominent, and has become a major bottleneck restricting the efficiency and safety of low-altitude emergency rescue.

[0030] Currently, most drones rely on pre-set flight paths and relatively simple obstacle avoidance algorithms when performing missions. However, in low-altitude complex environments, these algorithms face huge challenges such as rugged terrain, dense obstacles, and rapidly changing flight conditions, which greatly reduces their effectiveness. Even more serious is that when multiple drones work together in the same airspace, the frequent intersection and overlap of flight paths causes the risk of collision between drones to increase dramatically.

[0031] In order to solve the above technical problems, the present application provides a 5G low-latency communication low-altitude emergency rescue data processing method, referring to Figure 1 , Figure 1 A flowchart of a method for processing low-altitude emergency rescue data in 5G low-latency communication provided in an embodiment of the present application. Applied to a server, including steps S110 to S140, the steps are as follows: S110. Obtain a first flight direction of a first UAV and a second flight direction of a second UAV, where the first UAV and the second UAV are any two UAVs among a plurality of UAVs that perform low-altitude emergency rescue missions through 5G low-latency communication.

[0032] Specifically, the server is a centralized data processing and communication node. It is responsible for collecting, processing and analyzing data from drones, and may send instructions or information to drones. The first drone and the second drone are two drones that are part of a low-altitude emergency rescue mission. They may have different functions, tasks or goals, but they are all part of the entire drone network. Here, "first" and "second" are used to distinguish them, but in fact they can be any two quadcopters on a mission. 5G provides extremely low communication latency, which is essential for real-time communication and collaborative operations between drones. In low-altitude emergency rescue missions, drones need to exchange information quickly and accurately in order to make correct decisions and actions. 5G low-latency communication makes this real-time communication possible. Flight direction refers to the direction in which a drone moves relative to a reference point, such as the ground, a landmark, or another drone during flight. The server obtains this information in order to understand the current status of the drone and possible future action paths, so as to carry out more effective task allocation and collaborative operations.

[0033] For example, suppose that in a forest fire emergency rescue scenario, multiple drones are deployed to perform different tasks, such as scouting the fire, throwing fire extinguishing agents, and guiding ground rescue teams. Among them, the first drone is designated as a reconnaissance aircraft, responsible for flying over the fire scene for fire reconnaissance; the second drone is used as a fire extinguisher, responsible for carrying fire extinguishing agents to the designated location for fire extinguishing operations. In this scenario, the server obtains the flight direction of the first drone through 5G low-latency communication technology, for example, flying northeast to approach the fire scene, and the flight direction of the second drone, for example, flying southwest to reach the fire extinguishing operation point. Based on this information, the server can determine whether the two drones will meet or conflict, and adjust their flight paths or task allocations accordingly to ensure that they can complete the task safely and efficiently.

[0034] S120: Determine a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV according to the first flight direction and the second flight direction.

[0035] Specifically, the collision body here does not refer to a specific physical object, but to the three-dimensional space range or path that the drone may occupy during flight. This range or path is determined based on factors such as the size of the drone, flight speed, flight direction, and possible maneuverability. Through calculation and analysis, the server can predict the spatial position that the drone may occupy at a certain point in the future, thereby determining their collision bodies. Based on the flight direction of the drone and other relevant information, the server calculates the possible path of each drone in the future, and determines their collision bodies accordingly. These collision bodies are represented as geometric shapes in three-dimensional space, such as spheres, ellipsoids, or cubes, etc., which are used to evaluate whether a collision may occur between drones. In an embodiment of the present application, the collision body is a rectangular box.

[0036] In a possible implementation, a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV are determined according to the first flight direction and the second flight direction, specifically including: determining the flight center point of the first UAV; taking the flight center point as the origin and the first flight direction as any one of a plurality of coordinate axis directions to construct a three-dimensional flight coordinate system; determining a collision module of the first UAV in each coordinate axis direction, wherein the first collision body is composed of a plurality of collision modules; calculating a target edge point of the collision module in each coordinate axis direction; extending a preset length toward the first flight direction according to a side surface where the target edge point in the first flight direction is located to obtain a convex body module, the convex body module being connected to the collision module in the coordinate axis direction corresponding to the first flight direction, the preset length being proportional to the flight speed of the first UAV; constructing a first collision body according to the target edge points of the convex body module and the collision module.

[0037] Specifically, the flight center point refers to a reference point of the drone during flight, which can be the geometric center or center of gravity of the drone. With the flight center point as the origin, a coordinate axis consistent with the flight direction is selected, and the other two coordinate axes are determined to construct a three-dimensional coordinate system. This coordinate system is used to describe the position and movement of the drone in three-dimensional space. In each coordinate axis direction, one or more collision modules are determined according to the size and shape of the drone. These modules represent the possible space occupied by the drone in this direction. For each collision module, the farthest point is found in the direction of its corresponding coordinate axis, and these points are called target edge points. They define the boundary of the collision body in this direction. In the first flight direction, according to the side where the target edge point is located, a preset length is extended in this direction to form a convex body module. This preset length is proportional to the flight speed of the drone, and there is a certain size ratio relationship between the two to take into account the dynamic changes of the drone during flight. The convex body module is connected with the collision module in the coordinate axis direction corresponding to the first flight direction to form a complete collision body. According to the target edge points of all convex body modules and collision modules, the collision body of the first drone is finally constructed.

[0038] For example, suppose a drone is flying toward the east at a certain speed, that is, the first flight direction is east, and the geometric center of the drone is assumed to be its flight center point. With the flight center point as the origin, select the east direction as the X axis, the north direction as the Y axis, and the upward direction as the Z axis to construct a three-dimensional coordinate system. In the X axis direction, a collision module is determined according to the length of the drone; in the Y axis and Z axis directions, the collision modules are determined according to the width and height of the drone respectively. In the X axis direction, the easternmost and westernmost points of the drone are found as the target edge points; in the Y axis and Z axis directions, the northernmost, southernmost, uppermost and lowermost points are also found. In the X axis direction, according to the flight speed of the drone and the preset proportional relationship, an additional length is extended to the east to form a convex body module. This length should be large enough to take into account the dynamic changes and possible maneuverability of the drone during flight. Connect the convex body module with the collision module in the X axis direction to form a complete collision body. In the Y axis and Z axis directions, the collision body is directly composed of the corresponding collision modules. Finally, the first collision body of the drone is constructed based on the target edge points of all convex body modules and collision modules. This example shows how to construct an accurate collision body based on the flight direction and speed of the drone, which is crucial to ensure the safety of the drone during flight. The construction process of the second collision body of the second drone is the same as that of the first drone, so it will not be repeated here.

[0039] In a possible implementation, determining a collision module of the first UAV in each coordinate axis direction specifically includes: determining a first collision module in the first flight axis direction, the first flight axis direction is the same as the first flight direction, and the first collision module includes a low-speed rotor corresponding to the first UAV flying in the first flight direction; determining a second collision module in the second flight axis direction, the second flight axis direction is opposite to the first flight direction, and the second collision module includes a high-speed rotor corresponding to the first UAV flying in the first flight direction; determining a first side collision module in the first horizontal axis direction, the first horizontal axis direction is perpendicular to the first flight direction and parallel to a preset horizontal plane, and the first side collision module includes a left rotor of the first UAV ; Determine a second side collision module in the second horizontal axis direction, the second horizontal axis direction is perpendicular to the first flight direction and parallel to the preset horizontal plane, the second horizontal axis direction is opposite to the first horizontal axis direction, and the second side collision module includes the right rotor of the first UAV; determine the first middle collision module in the first vertical axis direction, the first vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, and the first middle collision module includes the top cover of the first UAV; determine the second middle collision module in the second vertical axis direction, the second vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, the second vertical axis direction is opposite to the first vertical axis direction, and the second middle collision module includes the bottom landing gear of the first UAV.

[0040] Specifically, the first collision module in the first flight axis direction refers to a collision module on the same coordinate axis (e.g., X axis) as the first flight direction. Since the rotation speed and position of the rotor of the drone will affect the space range it occupies when it is flying, the "low-speed rotor" is specifically mentioned here. This is because when the drone flies forward (i.e., the first flight direction), its front rotor may run at a lower speed, thereby occupying a smaller space. The second collision module in the second flight axis direction refers to a collision module on the coordinate axis opposite to the first flight direction (i.e., -X axis). Here, the "high-speed rotor" is specifically mentioned. This may be because when the drone flies forward, its rear rotor may need to run at a higher speed to maintain flight stability and speed, and may therefore occupy a larger space. The first side collision module in the first horizontal axis direction refers to a collision module on a coordinate axis (e.g., Y axis) that is perpendicular to the first flight direction and parallel to a preset horizontal plane (e.g., the ground). The "left rotor" mentioned here represents the space range that the left side of the drone may occupy during flight. The second side collision module in the second horizontal axis direction refers to the collision module on the coordinate axis (i.e. -Y axis) perpendicular to the first flight direction and parallel to the preset horizontal plane, but opposite to the first horizontal axis direction. "Right rotor" represents the space range that the right side of the drone may occupy during flight. The first middle collision module in the first vertical axis direction refers to the collision module on the coordinate axis (e.g. Z axis) perpendicular to the first flight direction and perpendicular to the preset horizontal plane (e.g. the ground). The top canopy represents the space range that the drone may occupy above it during flight. The second middle collision module in the second vertical axis direction refers to the collision module on the coordinate axis (i.e. -Z axis) perpendicular to the first flight direction and perpendicular to the preset horizontal plane, but opposite to the first vertical axis direction. "Bottom landing gear" represents the space range that the drone may occupy below during flight (although the landing gear does not touch the ground) or when it lands.

[0041] In a possible implementation, the target edge point of the collision module in each coordinate axis direction is calculated, specifically including: determining a first collision point and a second collision point in the target coordinate axis direction, the first collision point and the second collision point are any two collision points on the target collision module, the target coordinate axis direction is any one of a plurality of coordinate axis directions, and the target collision module is any one of a plurality of collision modules; determining a first projection point of the first collision point in the target coordinate axis direction, and a second projection point of the second collision point in the target coordinate axis direction; calculating a first distance from the first projection point to the flight center point, and a second distance from the second projection point to the flight center point; if it is determined that the first distance is greater than the second distance, determining the first collision point as the target edge point.

[0042] Specifically, first, a target coordinate axis direction (such as the X axis, Y axis, or Z axis) is selected. Then, a target collision module is selected, which refers to a collision module that needs to calculate a target edge point in the selected coordinate axis direction. Any two collision points are selected on the target collision module, which can be vertices on the module, points on the edge, or any other points that can represent the boundary of the module in this direction. The first collision point and the second collision point are projected onto the target coordinate axis direction respectively to obtain a first projection point and a second projection point. The projection operation means moving a point along a plane perpendicular to the target coordinate axis onto the axis, thereby obtaining a point on the axis. The first distance from the first projection point to the flight center point is calculated. The second distance from the second projection point to the flight center point is calculated. The first distance and the second distance are compared, and if the first distance is greater than the second distance, the first collision point is determined to be a target edge point. This means that in the selected coordinate axis direction, the first collision point deviates further from the flight center point than the second collision point, so it defines the boundary of the collision module in this direction.

[0043] S130, generating a collision judgment result based on the first collision body, the second collision body, and the real-time position data corresponding to the first drone, and the real-time position data corresponding to the second drone.

[0044] Specifically, real-time location data refers to the current location information of the drone obtained in real time during flight, which includes coordinate information such as longitude, latitude, and altitude. Here, drone A and drone B have their own real-time location data, which is the basis for the server to make collision judgments. The server judges whether the two drones may collide by comparing the relative position relationship between the collision body of drone A and the collision body of drone B in three-dimensional space, as well as their respective real-time location data. If the collision bodies of the two drones overlap or approach to a certain extent in three-dimensional space, and this extent is determined according to the safety distance threshold, the server will generate a collision judgment result, indicating that the two drones may collide. On the contrary, if the collision bodies of the two drones do not overlap in three-dimensional space and the distance is far enough, the server will generate a collision judgment result, indicating that the two drones will not collide.

[0045] In a possible implementation, based on the first collision body, the second collision body, and the real-time position data corresponding to the first drone, and the real-time position data corresponding to the second drone, a collision judgment result is generated, specifically including: calculating the first spatial volume corresponding to the first collision body at multiple continuous moments; screening out a first target spatial volume from the multiple first spatial volumes, the first spatial volume of the first target spatial volume at the target first moment is greater than a preset first threshold, the preset first threshold is determined according to the multiple first spatial volumes, and the target first moment is any one of the multiple continuous moments; determining the first target collision body corresponding to the first target spatial volume; calculating the second spatial volume corresponding to the second collision body at multiple continuous moments; screening out the second target spatial volume from the multiple second spatial volumes, the second spatial volume of the second target spatial volume at the target second moment is greater than a preset second threshold, the preset second threshold is determined according to the multiple second spatial volumes, and the target second moment is any one of the multiple continuous moments; determining the second target collision body corresponding to the second target spatial volume; after a preset time period, obtaining the first real-time position of the first target collision body and the second real-time position of the second target collision body at the same moment; judging whether the first target collision body and the second target collision body overlap, and generating a collision judgment result.

[0046] Specifically, for the first drone, the volume of its first collision body in three-dimensional space is calculated at multiple consecutive moments, for example, every second or every few milliseconds. This involves simulating or calculating the shape and size of the collision body according to the real-time position and attitude data of the drone. From the multiple first spatial volumes, those volumes whose volumes are greater than the preset first threshold at a certain specific moment (the first target moment) are screened out to obtain the first target spatial volume. The preset first threshold is determined based on factors such as the size, flight speed, and flight environment of the drone to ensure that the volume of the collision body that may cause a collision is not missed during the screening process. According to the screened first target spatial volume, the corresponding first target collision body is determined. This collision body represents the maximum spatial range that drone A may occupy at the first target moment. For the second drone, the above steps are repeated to calculate the spatial volume of its second collision body at multiple consecutive moments, and the second target spatial volume is screened out. According to the screened second target spatial volume, the corresponding second target collision body is determined. After a preset time period, the real-time position data of the first target collision body and the second target collision body at the same moment are obtained. According to the acquired real-time position data, it is determined whether the first target collision body and the second target collision body overlap. If two collision bodies have overlapping areas in three-dimensional space, or the distance between them is less than the preset safety distance threshold, it is considered that a collision may occur and a corresponding collision judgment result is generated.

[0047] S140: If it is determined that the collision judgment result indicates that the first UAV and the second UAV will collide, an avoidance path between the first UAV and the second UAV is planned according to the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV.

[0048] Specifically, the collision judgment result is generated by comparing the collision bodies of the two drones and their real-time position data. If the judgment result shows that the collision bodies of the two drones may overlap or approach to a dangerous degree at a certain moment or in a certain period of time in the future, it is considered that they may collide. Once it is determined that the two drones may collide, it is necessary to plan an avoidance path based on their real-time position data. This involves complex algorithms, such as path planning algorithms, optimization algorithms, etc., to ensure that the two drones can safely avoid each other while changing their original flight plans as little as possible. The planning of the avoidance path may need to consider multiple factors, such as the drone's flight speed, acceleration, steering ability, flight environment, such as obstacles, airflow, etc., and flight efficiency after avoidance.

[0049] In a possible implementation, an avoidance path between the first UAV and the second UAV is planned based on the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV, specifically including: obtaining the collision time and collision position data of the first target collision body and the second target collision body; calculating the interval distance between the real-time position data of the first UAV and the collision position data; based on the interval distance and the current flight speed of the first UAV, calculating the avoidance speed of the first UAV; and planning the avoidance path of the first UAV relative to the second UAV according to the avoidance speed.

[0050] Specifically, after determining that the two drones may collide, it is first necessary to determine the specific time when they collide and the location where the collision occurs. This is predicted by analyzing the flight trajectories, speeds, accelerations, and relative positional relationships of the two drones. Once the collision time and collision location data are determined, the interval distance between the real-time location data of the first drone and the collision location data needs to be calculated. This interval distance refers to the straight-line distance from the current position of the first drone to the predicted collision location, or the Euclidean distance in three-dimensional space, which reflects the distance between the first drone and the potential collision point. Based on the interval distance and the current flight speed of the first drone, the avoidance speed that the first drone needs to achieve can be calculated. The avoidance speed refers to the flight speed that the first drone needs to adjust to in order to avoid a collision. The calculation of this speed involves multiple factors, such as the acceleration capability, steering capability, and flight environment of the drone. The purpose of calculating the avoidance speed is to ensure that the first drone can safely change its flight trajectory before a collision occurs. Finally, based on the calculated avoidance speed, the avoidance path of the first drone relative to the second drone can be planned. The avoidance path refers to the flight trajectory that the first drone needs to take in order to avoid a collision. The planning of this path needs to take into account multiple factors, such as the flight capability of the UAV, the flight environment, the flight efficiency after avoidance, etc. The planned avoidance path should ensure that the first UAV will not collide with the second UAV or other obstacles during the avoidance process, and can return to the original flight plan as soon as possible.

[0051] In one possible implementation, refer to Figure 2 , Figure 2 Another flow chart of a method for processing low-altitude emergency rescue data for 5G low-latency communication provided in an embodiment of the present application. The method includes steps S210 to S220, which are as follows: S210, correcting the avoidance path according to the second flight direction to generate a low-altitude emergency rescue path including the avoidance direction; S220, sending the low-altitude emergency rescue path including the avoidance direction to the first UAV to control the first UAV to perform low-altitude emergency rescue according to the low-altitude emergency rescue path including the avoidance direction.

[0052] Specifically, in a low-altitude emergency rescue scenario, the first UAV may need to avoid obstacles or maintain a safe distance from other UAVs. The server first plans a preliminary avoidance path based on the real-time location data of the first UAV and possible collision risks. Then, the server considers the second flight direction. This direction may be determined by the flight path of the second UAV, the location of the rescue target, wind direction, terrain conditions or other relevant factors. The server will correct the preliminary avoidance path based on this direction to ensure that the first UAV can reach the rescue target more efficiently or follow a better flight strategy while avoiding. After correction, the server will generate a path that includes both the avoidance direction and is suitable for low-altitude emergency rescue. This path takes into account the flight capability, flight environment, rescue mission requirements and possible avoidance actions of the first UAV. The generation of the path requires the use of complex algorithms, such as path planning algorithms, optimization algorithms, etc., to ensure the feasibility and efficiency of the path. Once the path generation is completed, the server will send the low-altitude emergency rescue path including the avoidance direction to the first UAV. After receiving the path, the first UAV will adjust its flight status, such as speed, direction, altitude, etc., according to the path information to ensure that the low-altitude emergency rescue mission is carried out according to the path. During the flight, the First UAV may also make fine adjustments to the path based on real-time flight data and environmental information to maintain flight safety and efficiency.

[0053] This application also provides a 5G low-latency communication low-altitude emergency rescue data processing device, referring to Figure 3 , Figure 3 A module schematic diagram of a low-altitude emergency rescue data processing device for 5G low-latency communication provided in an embodiment of the present application. The low-altitude emergency rescue data processing device is a server, and the server includes an acquisition module 31 and a processing module 32, wherein the acquisition module 31 acquires a first flight direction of a first drone and a second flight direction of a second drone, and the first drone and the second drone are any two drones among multiple drones that perform low-altitude emergency rescue tasks through 5G low-latency communication; the processing module 32 determines the first collision body corresponding to the first drone and the second collision body corresponding to the second drone according to the first flight direction and the second flight direction; the processing module 32 generates a collision judgment result based on the first collision body, the second collision body, and the real-time position data corresponding to the first drone and the real-time position data corresponding to the second drone; if the processing module 32 determines that the collision judgment result indicates that the first drone and the second drone will collide, then the avoidance path between the first drone and the second drone is planned according to the real-time position data corresponding to the first drone and the real-time position data corresponding to the second drone.

[0054] In a possible implementation, the processing module 32 determines a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV according to the first flight direction and the second flight direction, specifically including: the processing module 32 determines the flight center point of the first UAV; the processing module 32 takes the flight center point as the origin and the first flight direction as any one of multiple coordinate axis directions to construct a three-dimensional flight coordinate system; the processing module 32 determines the collision module of the first UAV in each coordinate axis direction, and the first collision body is composed of multiple collision modules; the processing module 32 calculates the target edge point of the collision module in each coordinate axis direction; the processing module 32 extends a preset length to the first flight direction according to the side where the target edge point in the first flight direction is located to obtain a convex body module, the convex body module is connected to the collision module in the coordinate axis direction corresponding to the first flight direction, and the preset length is proportional to the flight speed of the first UAV; the processing module 32 constructs the first collision body according to the target edge points of the convex body module and the collision module.

[0055] In a possible implementation, the processing module 32 determines the collision module of the first UAV in each coordinate axis direction, specifically including: the processing module 32 determines the first collision module in the first flight axis direction, the first flight axis direction is the same as the first flight direction, and the first collision module includes the low-speed rotor corresponding to the first UAV flying in the first flight direction; the processing module 32 determines the second collision module in the second flight axis direction, the second flight axis direction is opposite to the first flight direction, and the second collision module includes the high-speed rotor corresponding to the first UAV flying in the first flight direction; the processing module 32 determines the first side collision module in the first horizontal axis direction, the first horizontal axis direction is perpendicular to the first flight direction and parallel to the preset horizontal plane, and the first side collision module includes the left side of the first UAV side rotor; the processing module 32 determines a second side collision module in the second horizontal axis direction, the second horizontal axis direction is perpendicular to the first flight direction and parallel to the preset horizontal plane, the second horizontal axis direction is opposite to the first horizontal axis direction, and the second side collision module includes the right rotor of the first UAV; the processing module 32 determines a first middle collision module in the first vertical axis direction, the first vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, and the first middle collision module includes the top cover of the first UAV; the processing module 32 determines a second middle collision module in the second vertical axis direction, the second vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, the second vertical axis direction is opposite to the first vertical axis direction, and the second middle collision module includes the bottom landing gear of the first UAV.

[0056] In a possible implementation, the processing module 32 calculates the target edge point of the collision module in each coordinate axis direction, specifically including: the processing module 32 determines the first collision point and the second collision point in the target coordinate axis direction, the first collision point and the second collision point are any two collision points on the target collision module, the target coordinate axis direction is any one of multiple coordinate axis directions, and the target collision module is any one of multiple collision modules; the processing module 32 determines the first projection point of the first collision point in the target coordinate axis direction, and the second projection point of the second collision point in the target coordinate axis direction; the processing module 32 calculates the first distance from the first projection point to the flight center point, and the second distance from the second projection point to the flight center point; if the processing module 32 determines that the first distance is greater than the second distance, then the first collision point is determined to be the target edge point.

[0057] In a possible implementation, the processing module 32 generates a collision judgment result based on the first collision body, the second collision body, the real-time position data corresponding to the first drone, and the real-time position data corresponding to the second drone, specifically including: the processing module 32 calculates the first spatial volumes corresponding to the first collision body at multiple consecutive moments; the processing module 32 selects a first target spatial volume from the multiple first spatial volumes, the first spatial volume of the first target spatial volume at the target first moment is greater than a preset first threshold, the preset first threshold is determined based on the multiple first spatial volumes, and the target first moment is any one of the multiple consecutive moments; the processing module 32 determines the first target collision body corresponding to the first target spatial volume; the processing module 32 calculates The second collision body corresponds to a second spatial volume at each of multiple consecutive moments; the processing module 32 selects a second target spatial volume from the multiple second spatial volumes, and the second spatial volume of the second target spatial volume at the target second moment is greater than a preset second threshold, the preset second threshold is determined based on the multiple second spatial volumes, and the target second moment is any one of the multiple consecutive moments; the processing module 32 determines the second target collision body corresponding to the second target spatial volume; the acquisition module 31 acquires the first real-time position of the first target collision body and the second real-time position of the second target collision body at the same moment after a preset time period; the processing module 32 determines whether the first target collision body and the second target collision body will overlap, and generates a collision judgment result.

[0058] In a possible implementation, the processing module 32 plans an avoidance path between the first UAV and the second UAV based on the real-time position data corresponding to the first UAV and the real-time position data corresponding to the second UAV, specifically including: the acquisition module 31 acquires the collision time and collision position data of the first target collision body and the second target collision body; the processing module 32 calculates the interval distance between the real-time position data of the first UAV and the collision position data; the processing module 32 calculates the avoidance speed of the first UAV based on the interval distance and the current flight speed of the first UAV; the processing module 32 plans the avoidance path of the first UAV relative to the second UAV according to the avoidance speed.

[0059] In one possible implementation, the processing module 32 corrects the avoidance path according to the second flight direction to generate a low-altitude emergency rescue path including the avoidance direction; the processing module 32 sends the low-altitude emergency rescue path including the avoidance direction to the first UAV to control the first UAV to perform low-altitude emergency rescue according to the low-altitude emergency rescue path including the avoidance direction.

[0060] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0061] The present application also provides an electronic device, referring to Figure 4 , Figure 4 The electronic device may include: at least one processor 41 , at least one network interface 44 , a user interface 43 , a memory 45 , and at least one communication bus 42 .

[0062] The communication bus 42 is used to realize the connection and communication between these components.

[0063] The user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0064] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0065] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 45, and calling data stored in the memory 45. Optionally, the processor 41 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 41 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 41, and it can be implemented separately through a chip.

[0066] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4 As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a low-altitude emergency rescue data processing method for 5G low-latency communication.

[0067] exist Figure 4In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program stored in the memory 45 for a low-altitude emergency rescue data processing method for 5G low-latency communication. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0068] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0069] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0070] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0071] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0072] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0073] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0074] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0075] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for processing low-altitude emergency rescue data for 5G low-latency communication, characterized in that: The method comprises: Obtaining a first flight direction of a first drone and a second flight direction of a second drone, where the first drone and the second drone are any two drones among a plurality of drones that perform low-altitude emergency rescue missions through 5G low-latency communication; Determine a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV according to the first flight direction and the second flight direction; Generate a collision judgment result based on the first collision body, the second collision body, the real-time position data corresponding to the first UAV, and the real-time position data corresponding to the second UAV; If it is determined that the collision judgment result indicates that the first drone and the second drone will collide, an avoidance path between the first drone and the second drone is planned according to the real-time position data corresponding to the first drone and the real-time position data corresponding to the second drone.

2. The low-altitude emergency rescue data processing method for 5G low-latency communication according to claim 1 is characterized in that: The determining, according to the first flight direction and the second flight direction, a first collision body corresponding to the first UAV and a second collision body corresponding to the second UAV specifically includes: Determining a flight center point of the first UAV; Taking the flight center point as the origin and the first flight direction as any one of the multiple coordinate axis directions to construct a three-dimensional flight coordinate system; Determine a collision module of the first UAV in each of the coordinate axis directions, wherein the first collision body is composed of a plurality of the collision modules; Calculate the target edge point of the collision module in each coordinate axis direction; According to the side where the target edge point in the first flight direction is located, a convex body module is extended in the first flight direction by a preset length, and the convex body module is connected to the collision module in the direction of the coordinate axis corresponding to the first flight direction, and the preset length is proportional to the flight speed of the first UAV; The first collision body is constructed according to the target edge points of the convex body module and the collision module.

3. The low-altitude emergency rescue data processing method for 5G low-latency communication according to claim 2 is characterized in that: The module for determining the collision of the first drone in each of the coordinate axis directions specifically includes: Determine a first collision module in a first flight axis direction, the first flight axis direction is the same as the first flight direction, the first collision module includes a low-speed rotor corresponding to the first UAV flying in the first flight direction; Determine a second collision module in a second flight axis direction, the second flight axis direction is opposite to the first flight direction, the second collision module includes a high-speed rotor corresponding to when the first UAV flies in the first flight direction; Determine a first side collision module in a first horizontal axis direction, wherein the first horizontal axis direction is perpendicular to the first flight direction and parallel to a preset horizontal plane, and the first side collision module includes a left rotor of the first UAV; Determine a second side collision module in a second horizontal axis direction, wherein the second horizontal axis direction is perpendicular to the first flight direction and parallel to the preset horizontal plane, the second horizontal axis direction is opposite to the first horizontal axis direction, and the second side collision module includes a right rotor of the first UAV; Determine a first middle collision module in a first vertical axis direction, wherein the first vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, wherein the first middle collision module includes a top cover of the first UAV; Determine a second middle collision module in a second vertical axis direction, wherein the second vertical axis direction is perpendicular to the first flight direction and perpendicular to the preset horizontal plane, the second vertical axis direction is opposite to the first vertical axis direction, and the second middle collision module includes a bottom landing gear of the first UAV.

4. The low-altitude emergency rescue data processing method for 5G low-latency communication according to claim 2 is characterized in that: The calculating the target edge point of the collision module in each coordinate axis direction specifically includes: Determine a first collision point and a second collision point in a target coordinate axis direction, wherein the first collision point and the second collision point are any two collision points on a target collision module, the target coordinate axis direction is any one of the plurality of coordinate axis directions, and the target collision module is any one of the plurality of collision modules; Determine a first projection point of the first collision point in the direction of the target coordinate axis, and a second projection point of the second collision point in the direction of the target coordinate axis; Calculating a first distance from the first projection point to the flight center point, and a second distance from the second projection point to the flight center point; If it is determined that the first distance is greater than the second distance, the first collision point is determined to be the target edge point.

5. The low-altitude emergency rescue data processing method for 5G low-latency communication according to claim 1 is characterized in that: The generating a collision judgment result based on the first collision body, the second collision body, the real-time position data corresponding to the first UAV, and the real-time position data corresponding to the second UAV specifically includes: Calculating first spatial volumes corresponding to the first collision body at a plurality of consecutive moments; A first target spatial volume is selected from the plurality of first spatial volumes, wherein the first spatial volume of the first target spatial volume at a target first moment is greater than a preset first threshold, wherein the preset first threshold is determined according to the plurality of first spatial volumes, and the target first moment is any one of the plurality of continuous moments; Determining a first target collision body corresponding to the first target space volume; Calculating the second spatial volume corresponding to each of the second collision body at a plurality of the consecutive moments; A second target spatial volume is selected from the plurality of second spatial volumes, wherein the second spatial volume of the second target spatial volume at the target second moment is greater than a preset second threshold, wherein the preset second threshold is determined according to the plurality of second spatial volumes, and the target second moment is any one of the plurality of continuous moments; Determining a second target collision body corresponding to the second target space volume; After a preset time period, obtaining a first real-time position of the first target collision body and a second real-time position of the second target collision body at the same time; It is determined whether the first target collision body and the second target collision body overlap, and a collision determination result is generated.

6. The low-altitude emergency rescue data processing method for 5G low-latency communication according to claim 5 is characterized in that: The planning of an avoidance path between the first drone and the second drone according to the real-time position data corresponding to the first drone and the real-time position data corresponding to the second drone specifically includes: Acquire collision time and collision position data of the first target collision body and the second target collision body; Calculating the interval distance between the real-time position data of the first UAV and the collision position data; Calculate the avoidance speed of the first UAV based on the interval distance and the current flight speed of the first UAV; An avoidance path of the first UAV relative to the second UAV is planned according to the avoidance speed.

7. The low-altitude emergency rescue data processing method for 5G low-latency communication according to claim 6 is characterized in that: The method further comprises: According to the second flight direction, the avoidance path is corrected to generate a low-altitude emergency rescue path including the avoidance direction; The low-altitude emergency rescue path including the avoidance direction is sent to the first UAV to control the first UAV to perform low-altitude emergency rescue according to the low-altitude emergency rescue path including the avoidance direction.

8. A low-altitude emergency rescue data processing device for 5G low-latency communication, characterized in that: The low-altitude emergency rescue data processing device comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to acquire a first flight direction of a first drone and a second flight direction of a second drone, wherein the first drone and the second drone are any two drones among a plurality of drones that perform low-altitude emergency rescue tasks through 5G low-latency communication; The processing module (32) is used to determine a first collision body corresponding to the first unmanned aerial vehicle and a second collision body corresponding to the second unmanned aerial vehicle according to the first flight direction and the second flight direction; The processing module (32) is further used to generate a collision judgment result based on the first collision body, the second collision body, the real-time position data corresponding to the first drone, and the real-time position data corresponding to the second drone; The processing module (32) is further configured to plan an avoidance path between the first drone and the second drone based on the real-time position data corresponding to the first drone and the real-time position data corresponding to the second drone if it is determined that the collision judgment result indicates that the first drone and the second drone will collide.

9. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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