Flight route generation method and device, electronic equipment and storage medium

Abstract

The invention provides a flight route generation method and device, electronic equipment and a storage medium. The flight route generation method comprises the steps that environment data and task data of a target airspace are acquired, the environment data comprise meteorological information, obstacle distribution information and airspace attributes, and the task data comprise a flight starting point, a flight ending point and a task priority; determining an initial flight route by using a path optimization algorithm based on the environment data and the task data; and performing effectiveness analysis on the initial flight path, and taking the effective initial flight path as a target flight path.

Description

Technical Field

[0001] The present disclosure relates to the technical fields such as low-altitude flight. In particular, the present disclosure relates to a flight route generation method, device, electronic device and storage medium. Background Art

[0002] In the development process of the low-altitude economy, route planning is a key link. The route planning of low-altitude aircraft not only needs to consider safety and efficiency, but also needs to take into account air traffic management rules and obstacle avoidance capabilities. Traditional route generation methods are mainly designed for ground vehicles, which follow a fixed lane pattern for path planning. This way limits the possibility of direct point-to-point movement in three-dimensional space. However, the low-altitude domain is completely different. Aircraft can freely shuttle between various nodes without being restricted by the ground road network. Current methods are difficult to meet the needs of low-altitude aircraft for flexible path selection. Especially in complex urban environments, how to effectively avoid factors such as buildings, other aircraft, and meteorological conditions becomes a challenge. Summary of the Invention

[0003] The present disclosure provides a flight route generation method, device, electronic device and storage medium to solve the problem that the related art is difficult to meet the needs of low-altitude aircraft for flexible path selection. Especially in complex urban environments, how to effectively avoid factors such as buildings, other aircraft, and meteorological conditions.

[0004] According to one aspect of the present disclosure, a flight route generation method is provided, including: obtaining environmental data and task data of a target airspace, where the environmental data includes meteorological information, obstacle distribution information and airspace attributes, and the task data includes a flight starting point, a flight ending point and a task priority; determining an initial flight route by using a path optimization algorithm based on the environmental data and the task data; performing effectiveness analysis on the initial flight route, and using the effective initial flight route as the target flight route.

[0005] In some embodiments, obtaining the environmental data of the target airspace includes: collecting the meteorological information based on a meteorological radar, where the meteorological information includes wind speed, precipitation and visibility data of the target airspace; determining the obstacle distribution information of the target airspace based on a geographic information system, and the obstacle distribution information records the three-dimensional coordinates of each obstacle; obtaining the airspace attribute of the target airspace based on an air traffic control first interface, and the airspace attribute characterizes the restriction situation of the corresponding space unit in the target airspace on the aircraft.

[0006] In some embodiments, based on the environmental data and the task data, an initial flight route is determined using a path optimization algorithm, including: discretizing the target airspace into a plurality of flight nodes according to the airspace attributes in the environmental data, where the flight nodes are positions that the aircraft can reach from the flight starting point to the flight ending point; calculating the minimum flight cost from the predecessor node to each of the flight nodes through a flight cost formula, with the flight starting point as the first predecessor node; taking the flight node corresponding to the minimum flight cost as the new predecessor node until the flight node corresponding to the minimum flight cost is the flight ending point, determining each of the predecessor nodes as the waypoints of the aircraft; and taking the connection lines between each of the predecessor nodes as the initial flight route.

[0007] In some embodiments, the flight cost formula is:

[0008]

[0009] where B(S i ) is the minimum flight cost of flight node S i , i is the serial number of the flight node, S i is the i-th flight node, S i-1 is the predecessor node of S i , Pre(S i ) is the set of all predecessor nodes before determining S i , E(S i-1 , S i ) is the energy consumption from S i-1 to S i , R(S i ) is the risk value of S i , △t i is the time increment from S i-1 to S i , ω1 is the weight of △t i , ω2 is the weight of E(S a-1 , S i ), and ω3 is the weight of R(S i ).

[0010] In some embodiments, it includes: determining the time increment △t i , the energy consumption E(S i-1 , S i ) and the risk value R(S i ) according to the environmental data.

[0011] In some embodiments, performing an effectiveness analysis on the initial flight route and using the effective initial flight route as the target flight route includes: determining the collision probability between the aircraft and obstacles when flying according to the initial flight route based on the obstacle distribution information of the environmental data and the task priority of the task data; when any of the collision probabilities is greater than a first threshold, marking the initial flight route as a risk route; or, when all the collision probabilities are less than the first threshold, using the initial flight route as the target flight route.

[0012] In some embodiments, it further includes: monitoring the environmental data and triggering a path replanning mechanism when the environmental data changes.

[0013] According to another aspect of the present disclosure, there is provided a flight route generation device, including: an acquisition module for acquiring environmental data and task data of a target airspace, where the environmental data includes meteorological information, obstacle distribution information, and airspace attributes, and the task data includes a flight starting point, a flight ending point, and a task priority; an analysis module for determining an initial flight route based on the environmental data and the task data by using a path optimization algorithm; and

[0014] a determination model for performing an effectiveness analysis on the initial flight route and using the effective initial flight route as the target flight route.

[0015] According to still another aspect of the present disclosure, there is provided an electronic device, including a processor and a memory coupled to the processor, where the memory stores program instructions executable by the processor; when the processor executes the program instructions stored in the memory, the flight route generation method as described in any of the above embodiments is implemented.

[0016] According to yet another aspect of the present disclosure, there is provided a readable storage medium, where execution instructions are stored in the readable storage medium, and when the execution instructions are executed by a processor, they are used to implement the flight route generation method of any of the embodiments.

[0017] The present disclosure provides efficient and safe flight route planning for low-altitude aircraft by comprehensively considering environmental data and mission requirements, and utilizing advanced path optimization algorithms and dynamic adjustment mechanisms. Its main advantages include: high safety, by accurately calculating the probability of collision and setting thresholds, it can effectively identify risky routes, ensure that aircraft avoid obstacles and adverse weather conditions in complex environments, and significantly reduce flight risks. Real-time adaptability, a powerful path re-planning mechanism has been established that can respond quickly when environmental data changes (such as the appearance of new obstacles or deterioration of weather conditions), and adjust the flight route in real time to ensure that the mission is not affected. Multi-objective optimization, the flight cost formula comprehensively considers multiple factors such as path length, energy consumption, time efficiency, obstacle avoidance, etc., and flexibly adjusts weights according to different mission requirements, achieving multi-objective optimization and improving overall mission execution efficiency. Intelligent decision-making, combining multi-source sensor data for fusion processing, and utilizing machine learning and artificial intelligence technologies, so that the system has stronger data processing capabilities and intelligent decision-making capabilities, further improving the accuracy and reliability of path planning. Flexibility and robustness, multi-level risk assessment and graded threshold settings enable the system to take corresponding response measures according to different risk levels, enhancing the flexibility and robustness of the system and ensuring that tasks can be completed smoothly even in emergency situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings illustrate exemplary embodiments of the present disclosure and together with the description serve to explain the principles of the present disclosure. These drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification.

[0019] Figure 1 It is an application scenario diagram of the flight route generation method according to an embodiment of the present disclosure.

[0020] Figure 2 4 is a flow chart of a flight path generation method according to an embodiment of the present disclosure.

[0021] Figure 3 It is a schematic block diagram of the structure of a flight path generating device according to an embodiment of the present disclosure.

[0022] Figure 4 is a schematic block diagram of the structure of an electronic device according to one embodiment of the present disclosure. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0024] The terms "first", "second", and "third" in this application are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", and "third" may explicitly or implicitly include at least one of such features. In the description of this application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative positional relationship, movement conditions, etc. between components in a specific posture (as shown in the drawings). If the specific posture changes, then the directional indications will change accordingly. In addition, the terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or devices.

[0025] Referring to "embodiments" herein means that specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0026] Therefore, the present disclosure proposes a flight route generation method.

[0027] Figure 1 is a schematic diagram of an application scenario of the flight route generation method according to an embodiment of the present disclosure. As Figure 1 shown, in this application scenario, it may include a server 100 and a terminal device 200. The server 100 and the terminal device 200 can be connected through a network or Bluetooth to perform data interaction. The server 100 can be a cloud server or a physical server, and the terminal device 200 can be an intelligent device such as a computer, a mobile phone, or a tablet. The server 100 is used to provide the basic data required to run the flight route generation method, and the terminal device 200 executes the flight route generation method of the present disclosure based on the basic data provided by the server 100.

[0028] Figure 2 is a flowchart of the flight route generation method according to an embodiment of the present disclosure. As Figure 2As shown in the figure, the present disclosure proposes a flight route generation method M200. Through steps S210 to S230, the initial flight route is determined based on environmental data and mission data, ensuring the fit between the flight route and the environment, as well as the flexibility of route changes. And the route is analyzed a second time to obtain the target flight route, maximizing the safety of the route.

[0029] In step S210, environmental data and mission data of the target airspace are acquired.

[0030] The target airspace refers to a three-dimensional space area where an aircraft plans to perform tasks or operations within a specific time and space range. This concept is not limited to geographical locations but also includes all relevant environmental conditions and limiting factors within the area.

[0031] The environmental data includes meteorological information, obstacle distribution information, and airspace attributes.

[0032] Among them, based on a weather radar, meteorological information is collected. The meteorological information includes wind speed, precipitation, and visibility data of the target airspace.

[0033] The wind speed refers to the magnitude and direction of the wind speed in the target airspace where the aircraft is located or about to enter at a specific time and location. The wind speed has a direct impact on the speed, stability, and energy consumption of the aircraft. Precipitation includes any form of water vapor condensation and precipitation such as rain, snow, and hail. Precipitation will affect the visibility of the aircraft, the safety of the flight path, and the working state of the equipment. The visibility data refers to the maximum distance at which objects can be clearly seen by the human eye within a certain area. Low visibility (such as fog and haze) will significantly affect the operation safety and navigation accuracy of the aircraft.

[0034] The three-dimensional coordinates of the obstacle distribution information record the precise position of the obstacle in space, usually represented by three dimensions: longitude, latitude, and altitude. This enables the aircraft to accurately avoid obstacles and ensure the safety of the flight path. There can be multiple obstacles in the target airspace, and the obstacle information records the three-dimensional position information of all the obstacles that can be identified in the target airspace.

[0035] Of course, the obstacle distribution information not only records the three-dimensional coordinates of each obstacle but also should include the height, shape, material, and dynamic characteristics of the obstacle. Static obstacles such as buildings, high-voltage towers, and mountains need to be detailedly marked with their precise positions and dimensions so that the aircraft can perform precise obstacle avoidance. Dynamic obstacles such as birds, drones, and kites need to be dynamically updated through a real-time monitoring system to avoid collision risks. For some special obstacles, such as glass curtain wall buildings, the possible impact of their reflection characteristics on sensors also needs to be considered.

[0036] The airspace attributes characterize the restrictions imposed by the corresponding spatial units in the target airspace on the aircraft, which include not only no-fly zones, height-limited zones, and special control areas, but also communication coverage, distribution of navigation aids, electromagnetic interference areas, and temporary control measures, etc. For example, certain areas may be temporarily set as no-fly zones due to military exercises or major events; while some other areas may not be suitable for aircraft operations due to the lack of necessary communication infrastructure. In addition, different types of aircraft (such as manned aircraft, unmanned aircraft) may be subject to different restrictions in the same airspace, so these differences need to be particularly noted during planning.

[0037] Of course, meteorological information not only includes the target wind speed, precipitation, and visibility data, but also should be extended to more detailed weather parameters, such as temperature, humidity, air pressure, cloud height and density, frequency of thunderstorm activities, and lightning risk, etc. In addition, microclimate effects such as the urban heat island phenomenon also need to be considered because they have an important impact on the performance of the aircraft. The changes in wind speed and direction directly affect the speed and heading control of the aircraft; the amount and type of precipitation determine whether the aircraft needs to take special protective measures; while visibility is directly related to whether the aircraft can navigate and operate safely.

[0038] Mission data is a set of key information required for low-altitude aircraft to perform specific tasks, which not only includes the basic starting and ending positions, but also covers a variety of other parameters to ensure that the mission can be completed safely and efficiently.

[0039] The flight starting point includes geographical position coordinates: precise longitude, latitude, and altitude, which are used to determine the take-off position of the aircraft. For example, a logistics delivery unmanned aircraft may take off from the apron of a certain warehouse. The flight starting point should also include the starting conditions, which describe the specific operation requirements or restrictions at the starting point. For example, whether it is necessary to take off within a specific time period, whether it is necessary to conduct pre-take-off safety inspections or maintenance, and whether there are special take-off procedures (such as vertical take-off or runway take-off).

[0040] The flight starting point should also have a payload status, that is, the status of the goods or equipment carried at take-off. For logistics unmanned aircraft, this may include the weight, size, sensitivity, etc. of the goods; while for manned aircraft, it involves information such as the number of passengers and their health conditions.

[0041] Similarly, the flight ending point should record geographical position coordinates. Similar to the starting point, the ending point also has precise longitude, latitude, and altitude coordinates. For example, the destination of an emergency medical rescue unmanned aircraft may be the rooftop apron of a hospital.

[0042] It is also necessary to record the arrival conditions at the flight end point and describe the operation requirements at the end point. For example, whether it is necessary to hover, land, or perform special tasks (such as dropping supplies, collecting samples) at a specific location. In addition, issues related to how to handle the payload after landing may also be involved.

[0043] Based on the flight end point, the destination environment can also be determined, that is, considering the specific environmental conditions of the destination, such as the complexity of the terrain, the distribution of surrounding obstacles, and meteorological conditions. These factors will affect the landing method and safety of the aircraft.

[0044] The task priority is set with different priorities according to the importance and urgency of the task. For example, emergency medical services usually have the highest priority, while regular logistics distribution may belong to medium priority.

[0045] Specifically, high-priority tasks may receive more resource support, such as prioritizing the scheduling of aircraft, preferentially using communication channels, and preferentially obtaining real-time data updates. This helps to ensure that critical tasks can be completed in the shortest possible time.

[0046] In addition, each task has its specific time window, that is, the time range within which it must start and be completed. For example, emergency rescue tasks usually have very strict time limits, while agricultural spraying tasks may have a certain degree of flexibility.

[0047] In addition, according to the flight mission, the payload information of the aircraft can also be determined. The payload information details the items or equipment carried by the aircraft. Including but not limited to weight, size, type (such as goods, sensors, cameras), sensitivity (such as fragile items, dangerous goods), and environmental requirements (such as temperature control, shock protection).

[0048] Furthermore, considering the battery capacity or fuel quantity of the aircraft, plan a reasonable energy consumption path to ensure that the task can be completed without refueling midway. This may involve estimating the flight time and distance and choosing the optimal path to save energy.

[0049] In addition, different safety standards are set according to the nature of the task, such as obstacle avoidance distance, preparation of alternate routes, etc. For example, high-priority tasks may require more stringent obstacle avoidance measures and more backup plans to improve flight safety. Clearly define the communication support required during the task, including frequency, bandwidth, signal strength, etc. Especially in complex environments, good communication guarantee is the key to ensuring the smooth completion of the task. By comprehensively collecting and analyzing the above task data, a more detailed and scientific task plan can be formulated for low-altitude aircraft. This not only improves the efficiency and success rate of task execution, but also effectively responds to various emergencies, ensuring the safety of the aircraft and its payload. At the same time, reasonably using these data can also optimize resource allocation and enhance the operation efficiency of the entire low-altitude economic system.

[0050] In step S220, based on the environmental data and the task data, an initial flight route is determined by using a path optimization algorithm.

[0051] Specifically, according to the airspace attributes in the environmental data, the target airspace is discretized into multiple flight nodes, where a flight node is a position that an aircraft can reach from the flight starting point to the flight ending point; through a flight cost formula, with the flight starting point as the first predecessor node, the minimum flight cost from the predecessor node to each flight node is calculated; the flight node corresponding to the minimum flight cost is used as the new predecessor node until the flight node corresponding to the minimum flight cost is the flight ending point, and each predecessor node is determined as a waypoint of the aircraft; and the connection lines between the predecessor nodes are used as the initial flight route.

[0052] In some embodiments, the flight cost formula is:

[0053]

[0054] where V(S i ) is the minimum flight cost of flight node S i , i is the serial number of the flight node, S i is the i-th flight node, S i-1 is the predecessor node of S i , Pre(S i ) is the set of all predecessor nodes before determining S i , E(S i-1 ,S i ) is the energy consumption from S i-1 to S i , R(S i ) is the risk value of S i , △t i is the time increment from S i-1 to S i , ω1 is the weight of △t i , ω2 is the weight of E(S i-1 [[ID=4 nine]],S i ), and ω3 is the weight of R(S i ).

[0055] In some embodiments, it includes: determining the time increment △t i , the energy consumption E(S i-1 ,S i ) and the risk value R(S i ) according to the environmental data.

[0056] The initial flight route determined by the flight cost formula comprehensively considers factors such as path length, energy consumption, time efficiency, safe obstacle avoidance, and meteorological conditions to minimize the total flight cost and ensure the successful completion of the mission. More specifically, this process not only includes the accurate modeling of static environmental data (such as obstacle distribution and airspace attributes) and mission requirements (such as start point, end point, and priority), but also involves the integration of dynamic factors (such as real-time weather updates and moving obstacle prediction) to generate an optimized flight path, maximizing the operational efficiency and safety of the aircraft. In addition, the flight cost formula can flexibly adjust the weights of various evaluation indicators according to the requirements of different missions, further enhancing the adaptability and robustness of path planning.

[0057] In step S230, the effectiveness of the initial flight route is analyzed, and the effective initial flight route is used as the target flight route.

[0058] After determining the initial flight route, it is necessary to conduct a detailed effectiveness analysis to ensure that the aircraft can perform the mission under safe and efficient conditions. The specific steps are as follows:

[0059] Collision probability calculation: Based on environmental data (such as obstacle distribution, dynamic obstacle prediction) and the flight route, calculate the probability of collision during the flight. This includes the potential collision risks of static obstacles (such as buildings, high-voltage pylons) and dynamic obstacles (such as other aircraft, birds).

[0060] First threshold setting: According to the mission priority and safety requirements, set a first threshold for the collision probability. If the collision probability of a certain flight route exceeds this threshold, it is marked as a risky route.

[0061] When the collision probability of a certain flight route is greater than the first threshold, this section of the route is identified as a high-risk route. At this time, further risk assessment and optimization of this section of the route are required, or the path replanning mechanism is directly triggered.

[0062] If the collision probability of all sections is lower than the first threshold, the entire flight route is confirmed as the target flight route and can be used for actual flight operations.

[0063] In order to cope with changes in environmental data and other unforeseen factors, an effective path replanning mechanism must be established. The following are the detailed steps:

[0064] When environmental data changes (such as deteriorating meteorological conditions, the appearance of new obstacles, or the movement of existing obstacles), the system will automatically detect these changes and evaluate their impact on the current flight route. For example, the sudden appearance of a thunderstorm area or a newly added no-fly zone may trigger path replanning.

[0065] Continuously monitor the changes in the environment around the aircraft through sensor, satellite data and ground station feedback. Once a change in a key factor affecting flight safety is detected, immediately initiate the path replanning process.

[0066] Input the latest environmental data and mission requirements into the path optimization algorithm. For example, update key parameters such as meteorological information, obstacle positions, and airspace attributes.

[0067] Regenerate the path: Use the selected path optimization algorithm to regenerate a new flight route. The new route should minimize the collision risk and meet the mission's time window and other constraints.

[0068] Adjust the weights of each item in the flight cost formula according to the new environmental data and mission requirements. For example, increase the obstacle avoidance weight to cope with high-density obstacle areas, or increase the time efficiency weight to ensure that urgent tasks are completed on time.

[0069] Conduct simulation tests on the newly generated flight route in a virtual environment to check whether it meets all constraints and achieves the expected results. Ensure that the new route can effectively avoid all known obstacles and adverse weather areas.

[0070] If the simulation results show that the new route is feasible and better than the original route, immediately send it to the aircraft control system for implementation. At the same time, continue to monitor environmental changes during the flight and trigger path replanning again if necessary.

[0071] In addition to the first threshold, multiple different collision probability thresholds (such as the second threshold, the third threshold) can be set, corresponding to different levels of risk. For example, low risk (below the first threshold), medium risk (between the first and second thresholds), and high risk (above the second threshold). For different levels of risk, take corresponding countermeasures, such as fine-tuning the route, local replanning, or full replanning.

[0072] During the path replanning process, consider resource limitations such as the aircraft's energy consumption and communication bandwidth, and dynamically adjust the resource allocation strategy. For example, preferentially schedule the resources required for high-priority tasks to ensure that critical tasks are not affected.

[0073] Combine data from different sensors (such as radar, lidar, cameras, etc.) for more accurate environmental perception and path planning. Utilize machine learning and artificial intelligence technologies to improve data processing and decision-making capabilities, making the path planning more intelligent and adaptive.

[0074] Through the above method, the effective analysis and dynamic adjustment of the initial flight route can be achieved, ensuring that the low-altitude aircraft can complete tasks safely and efficiently in complex and changeable environments. This multi-level and multi-dimensional path optimization and replanning mechanism not only improves the flight safety but also enhances the robustness and flexibility of the system.

[0075] It should be noted that the aircraft of the present disclosure can be a low-altitude aircraft, that is, an aviation device designed specifically for performing various tasks at low altitudes (usually referring to the altitude range from 120 meters to 500 meters above the ground). According to different application scenarios and requirements, low-altitude aircraft can be divided into various types, including but not limited to unmanned aerial vehicles, vertical takeoff and landing aircraft, unmanned helicopters, etc.

[0076] Low-altitude aircraft are usually made of lightweight but high-strength materials (such as carbon fiber, aluminum alloy) to ensure their structural strength and durability, while reducing weight and improving endurance.

[0077] Common propulsion methods include electric motors, internal combustion engines, or hybrid power systems. Electric motors are widely used in small unmanned aerial vehicles due to their quietness and environmental friendliness; while internal combustion engines are suitable for tasks requiring long endurance and high payloads.

[0078] Equipped with advanced autopilot and navigation systems, it can achieve functions such as automatic takeoff, hovering, route tracking, and automatic landing. These systems usually integrate multiple sensors such as GPS, inertial measurement units, and barometers to provide precise position and attitude control.

[0079] Vision sensors include cameras, infrared cameras, etc., which are used to monitor the flight environment in real time for obstacle detection and avoidance operations. High-definition cameras can also be used to capture high-quality images and videos to support the data collection requirements during tasks.

[0080] By emitting laser beams and receiving reflected signals, a high-precision three-dimensional map is generated to help the aircraft perform precise positioning and obstacle avoidance in complex environments.

[0081] Radar is used to detect obstacles and other aircraft at a long distance, especially providing additional safety guarantees under low visibility conditions (such as fog, haze).

[0082] The wireless communication module supports two-way communication, allowing the aircraft to perform real-time data exchange with the ground station or other aircraft. Common communication protocols include Wi-Fi, LTE, 5G, etc., ensuring stable data transmission rates and coverage.

[0083] In addition to the basic remote control command transmission, the data link also supports the real-time transmission of high-definition video streams, telemetry data, and mission status information, facilitating remote monitoring and operation.

[0084] For logistics and distribution tasks, the aircraft can carry specially designed cargo boxes or mounting devices for transporting items such as parcels and medicines. The payload capacity and size can be customized according to specific task requirements. For tasks such as agricultural monitoring, geographical mapping, and environmental monitoring, the aircraft can carry a variety of sensors, such as multispectral cameras, gas analyzers, weather stations, etc., to collect detailed environmental data. In emergency medical services, the aircraft can carry first aid kits, medical equipment, and even automated external defibrillators to quickly respond to emergencies and provide timely assistance.

[0085] For electric aircraft, an efficient battery management system is crucial. It not only monitors the battery status (such as power and temperature) but also optimizes energy distribution to extend the flight duration. Some aircraft are equipped with solar panels that can absorb solar energy during flight to further enhance the endurance, which is especially suitable for long-duration operation tasks.

[0086] Using advanced path planning algorithms, combined with environmental data and task requirements, it generates the optimal flight route and makes dynamic adjustments when necessary. Through deep learning and reinforcement learning technologies, the aircraft can continuously optimize its decision-making ability, improve its adaptability to complex environments, and enhance its autonomous flight and obstacle avoidance capabilities.

[0087] The aircraft can quickly and efficiently deliver parcels from the warehouse to customers, especially in remote areas with inconvenient transportation. By carrying multispectral cameras and sensors, it can monitor the health status of farmland in real time and optimize irrigation and fertilization strategies. In natural disasters or emergencies, it can quickly transport first aid supplies or conduct aerial reconnaissance to provide first-hand on-site information. As part of future urban air traffic, the aircraft can relieve ground traffic pressure and provide new travel options.

[0088] In summary, with its flexible design, advanced technology, and diverse application scenarios, low-altitude aircraft are becoming an important part of the modern aviation field, driving the development of the low-altitude economy and social progress. Whether for commercial use or public services, low-altitude aircraft demonstrate great potential and broad application prospects.

[0089] This solution provides efficient and safe flight route planning for low-altitude aircraft by comprehensively considering environmental data and mission requirements, and using advanced path optimization algorithms and dynamic adjustment mechanisms. Its main advantages include: high safety, by accurately calculating the collision probability and setting thresholds, it can effectively identify risky routes, ensure that the aircraft avoids obstacles and adverse weather conditions in complex environments, and significantly reduce flight risks. Real-time adaptability, a powerful path replanning mechanism is established, which can quickly respond when environmental data changes (such as the emergence of new obstacles or the deterioration of weather conditions), and adjust the flight route in real time to ensure that the mission is not affected. Multi-objective optimization, the flight cost formula comprehensively considers multiple factors such as path length, energy consumption, time efficiency, and obstacle avoidance, and flexibly adjusts the weights according to different mission requirements, achieving multi-objective optimization and improving the overall mission execution efficiency. Intelligent decision-making, by fusing multi-source sensor data and using machine learning and artificial intelligence technologies, the system has stronger data processing capabilities and intelligent decision-making capabilities, further improving the accuracy and reliability of path planning. Flexibility and robustness, multi-level risk assessment and hierarchical threshold settings enable the system to take corresponding countermeasures according to different risk levels, enhancing the flexibility and robustness of the system, and ensuring that the mission can be successfully completed even in emergencies.

[0090] In summary, this solution not only improves the safety and mission completion rate of low-altitude aircraft, but also enhances the adaptability and reliability of the system through intelligent path planning and dynamic adjustment mechanisms, providing a solid technical guarantee for the development of the low-altitude economy.

[0091] Figure 3 It is a structural schematic diagram of a flight route generation device according to an embodiment of the present disclosure.

[0092] As Figure 3 shown, the flight route generation device 300 of the present disclosure includes an acquisition module 310 for obtaining environmental data and mission data of the target airspace, where the environmental data includes meteorological information, obstacle distribution information, and airspace attributes, and the mission data includes a flight starting point, a flight ending point, and a mission priority; an analysis module 320 for determining an initial flight route based on the environmental data and the mission data by using a path optimization algorithm; and a determination model 330 for performing effectiveness analysis on the initial flight route and using the effective initial flight route as the target flight route.

[0093] In some embodiments, environmental data of a target airspace is obtained, including: collecting the meteorological information based on a weather radar, where the meteorological information includes wind speed, precipitation, and visibility data of the target airspace; determining obstacle distribution information of the target airspace based on a geographic information system, where the obstacle distribution information records the three-dimensional coordinates of each obstacle; and obtaining the airspace attributes of the target airspace based on an air traffic control first interface, where the airspace attributes characterize the restrictions on aircraft in corresponding spatial units of the target airspace.

[0094] In some embodiments, based on the environmental data and the mission data, an initial flight route is determined using a path optimization algorithm, including: discretizing the target airspace into multiple flight nodes according to the airspace attributes in the environmental data, where the flight nodes are positions that an aircraft can reach from the flight starting point to the flight ending point; calculating the minimum flight cost from the predecessor node to each of the flight nodes through a flight cost formula, with the flight starting point as the first predecessor node; using the flight node corresponding to the minimum flight cost as the new predecessor node until the flight node corresponding to the minimum flight cost is the flight ending point, determining each of the predecessor nodes as waypoints of the aircraft; and taking the connections between each of the predecessor nodes as the initial flight route.

[0095] In some embodiments, the flight cost formula is:

[0096]

[0097] where V(S i ) is the minimum flight cost of flight node S i , i is the serial number of the flight node, S i is the i-th flight node, S i-1 is the predecessor node of S i , Pre(S i ) is the set of all predecessor nodes before determining S i , E(S i-1 , S i ) is the energy consumption from S i-1 to S i , R(S i ) is the risk value of S i , △t i is the time increment from S i-1 to S i , ω1 is the weight of △t i , ω2 is the weight of E(S i-1 , S i ), and ω3 is the weight of R(S i ).

[0098] In some embodiments, it includes: determining a time increment Δt according to the environmental data i , energy consumption E(S i-1 ,S i ), and risk value R(S i ).

[0099] In some embodiments, performing an effectiveness analysis on the initial flight route and using the effective initial flight route as the target flight route includes: determining the collision probability of the aircraft with obstacles when flying according to the initial flight route based on the obstacle distribution information of the environmental data and the task priority of the task data; when any of the collision probabilities is greater than a first threshold, marking the initial flight route as a risky route; or, when all the collision probabilities are less than the first threshold, using the initial flight route as the target flight route.

[0100] In some embodiments, it further includes: monitoring the environmental data and triggering a path replanning mechanism when the environmental data changes.

[0101] This solution comprehensively considers environmental data and mission requirements, and uses advanced path optimization algorithms and dynamic adjustment mechanisms to provide efficient and safe flight route planning for low-altitude aircraft. Its main advantages include: high safety. By accurately calculating the collision probability and setting thresholds, it can effectively identify risky routes, ensure that the aircraft avoids obstacles and adverse weather conditions in complex environments, and significantly reduce flight risks. Real-time adaptability. A powerful path replanning mechanism is established, which can quickly respond when the environmental data changes (such as the appearance of new obstacles or the deterioration of weather conditions), and adjust the flight route in real time to ensure that the mission is not affected. Multi-objective optimization. The flight cost formula comprehensively considers multiple factors such as path length, energy consumption, time efficiency, and obstacle avoidance, and flexibly adjusts the weights according to different mission requirements, achieving multi-objective optimization and improving the overall mission execution efficiency. Intelligent decision-making. By fusing multi-source sensor data and using machine learning and artificial intelligence technologies, the system has stronger data processing capabilities and intelligent decision-making capabilities, further improving the accuracy and reliability of path planning. Flexibility and robustness. The multi-level risk assessment and hierarchical threshold setting enable the system to take corresponding countermeasures according to different risk levels, enhancing the flexibility and robustness of the system, and ensuring that the mission can be successfully completed even in case of emergencies.

[0102] In summary, this solution not only improves the safety and mission completion rate of low-altitude aircraft, but also enhances the adaptability and reliability of the system through intelligent path planning and dynamic adjustment mechanisms, providing a solid technical guarantee for the development of the low-altitude economy.

[0103] The flight route generation device 300 of the present disclosure may be in the form of computer software, and each module of the flight route generation device 300 may be in the form of a computer software module.

[0104] Each module of the flight route generation device 300 of the present disclosure is set to implement each step of the flight route generation method. Its execution principle and steps can be referred to the foregoing, and will not be elaborated here.

[0105] Figure 4 It is a structural schematic diagram of an electronic device according to an embodiment of the present disclosure. As Figure 4 shown, the present disclosure also provides an electronic device 1000, including: a processor 1200 and a memory 1300, the memory 1300 stores execution instructions; the processor 1200 executes the execution instructions stored in the memory 1300, so that the processor 1200 executes the flight route generation method.

[0106] The hardware structure of the electronic device 1000 can be implemented by using a bus architecture. The bus architecture may include any number of interconnecting buses and bridges, depending on the specific application of the hardware and the overall design constraints. The bus 1100 connects various circuits including one or more processors 1200, the memory 1300, and / or hardware modules together. The bus 1100 can also connect various other circuits 1400 such as peripheral devices, voltage regulators, power management circuits, external antennas, etc.

[0107] The bus 1100 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Component (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, only one connecting line is used in this figure, but it does not mean that there is only one bus or one type of bus.

[0108] The present disclosure also provides a readable storage medium storing a computer program which, when executed by a processor, is used to implement the above method. The "readable storage medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples of the readable storage medium include the following: an electrical connection part with one or more wirings (electronic device), a portable computer diskette case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM), etc.

[0109] The present disclosure also provides a computer program product. The method of the present disclosure can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed, the processes or functions of the present disclosure are executed in whole or in part.

[0110] The computer program or instructions can be stored in a readable storage medium, or transmitted from one readable storage medium to another. For example, the computer program or instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner. The readable storage medium can be any available medium that can be accessed, or a data storage device such as a server or data center integrating one or more available mediums. The available medium can be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it can also be an optical medium, such as a digital video disc; or it can be a semiconductor medium, such as a solid state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or can include both volatile and non-volatile types of storage media.

[0111] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, an electronic device, a readable storage medium, or a computer program product. Therefore, the present disclosure can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] This disclosure is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to the disclosure. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce means for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0113] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0115] In several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there can be other division methods in actual implementation. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can be in electrical, mechanical, or other forms.

[0116] In addition, in each embodiment of the present application, each functional unit can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. The above is only the implementation manner of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be included in the patent protection scope of the present application by the same token.

[0117] The specific embodiments of the invention have been described in detail above, but they are only examples, and the present application is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the present application. Therefore, all equal transformations, modifications, improvements, etc. made without departing from the spirit and principles of the present application should be covered by the scope of the present application.

Claims

1. A flight route generation method, characterized in that, Including: Obtain the environmental data and mission data of the target airspace, where the environmental data includes meteorological information, obstacle distribution information, and airspace attributes, and the mission data includes the flight starting point, flight ending point, and mission priority; Based on the environmental data and the mission data, use a path optimization algorithm to determine an initial flight route; Conduct an effectiveness analysis on the initial flight route, and use the effective initial flight route as the target flight route.

2. The flight route generation method according to claim 1, wherein Obtain the environmental data of the target airspace, including Based on a weather radar, collect the meteorological information, where the meteorological information includes the wind speed, precipitation, and visibility data of the target airspace; Based on a geographic information system, determine the obstacle distribution information of the target airspace, and the obstacle distribution information records the three-dimensional coordinates of each obstacle; Based on an air traffic control first interface, obtain the airspace attributes of the target airspace, and the airspace attributes characterize the restrictions on the aircraft in the corresponding spatial units of the target airspace.

3. The flight route generation method according to claim 1, characterized in that, Based on the environmental data and the mission data, use a path optimization algorithm to determine an initial flight route, including: According to the airspace attributes in the environmental data, discretize the target airspace into multiple flight nodes, and the flight nodes are the positions that the aircraft can reach from the flight starting point to the flight ending point; Through a flight cost formula, with the flight starting point as the first predecessor node, calculate the minimum flight cost from the predecessor node to each flight node; Use the flight node corresponding to the minimum flight cost as the new predecessor node until the flight node corresponding to the minimum flight cost is the flight ending point, and determine each predecessor node as the waypoint of the aircraft; and Use the connection lines between each predecessor node as the initial flight route.

4. The flight route generation method according to claim 3, wherein The flight cost formula is: Among them, V(S i ) is the minimum flight cost of the flight node S i . Here, i is the serial number of the flight node, S i is the i-th flight node, S i-1 is the predecessor node of S i . Pre(S i ) is the set of all predecessor nodes before determining S i . E(S i-1 , S i ) is the energy consumption from S i-1 to S i . R(S i ) is the risk value of S i . △t i is the time increment from S i-1 to S i . ω1 is the weight of △t i . ω2 is the weight of E(S i-1 , S i ). ω3 is the weight of R(S i ).

5. The flight route generation method according to claim 4, characterized in that Including: Determine the time increment Δt according to the environmental data i , energy consumption E(S i-1 , S i ), and risk value R(S i ).

6. The flight route generation method according to claim 1, wherein Conduct an effectiveness analysis on the initial flight route, and use the effective initial flight route as the target flight route, including: According to the obstacle distribution information in the environmental data and the mission priority in the mission data, determine the collision probability between the aircraft and the obstacles when flying according to the initial flight route; When there is any collision probability greater than the first threshold, mark the initial flight route as a risky route; or, when all the collision probabilities are less than the first threshold, use the initial flight route as the target flight route.

7. The flight route generation method according to claim 1, wherein Also including: Monitor the environmental data, and trigger a path replanning mechanism when the environmental data changes.

8. A flight route generation device, characterized in that, Including: A collection module for obtaining the environmental data and mission data of the target airspace, where the environmental data includes meteorological information, obstacle distribution information, and airspace attributes, and the mission data includes the flight starting point, flight ending point, and mission priority; An analysis module for using a path optimization algorithm to determine an initial flight route based on the environmental data and the mission data; And A determination model for conducting an effectiveness analysis on the initial flight route and using the effective initial flight route as the target flight route.

9. An electronic device, characterized in that, It includes a processor and a memory coupled to the processor, and the memory stores program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the flight route generation method of the park as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores program instructions, and when the program instructions are executed by a processor, it can implement the flight route generation method as described in any one of claims 1 to 7.

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