Methods and apparatus for generating navigation paths, storage media and electronic devices

Abstract

This application discloses a method, apparatus, storage medium, and electronic device for generating flight paths. The method includes: first, dividing the flight area of ​​an aircraft into grid cells; then, determining the travel cost of each grid cell based on meteorological data; constructing a directed grid network according to the travel cost, where nodes in the directed grid network represent grid cells, directed edges of nodes indicate travel directions, and travel costs determine the edge weights of the directed edges; thereby generating the aircraft's flight path based on the directed grid network. This application solves the technical problem of poor usability of flight paths in existing aircraft flight path generation methods, which do not consider complex and changing application environments.

Description

Technical Field

[0001] This application relates to the field of geographic information, and more specifically, to a method and apparatus for generating navigation paths, a storage medium, and an electronic device. Background Technology

[0002] When planning and generating flight paths for aircraft, existing technologies are often limited to calculating the optimal path in a static environment, neglecting the influence of dynamic environmental factors such as wind fields. This leads to significant limitations in the practical application of the generated flight paths. For example, when an aircraft flies in a headwind environment according to the traditional shortest distance plan, it will encounter additional energy consumption and time delays, thus affecting the mission completion quality and flight safety. Furthermore, sudden changes in wind speed or the appearance of rainy areas limit the autonomous navigation capabilities of aircraft in dynamic environments. In summary, existing technologies suffer from poor usability of flight paths because they do not consider complex and ever-changing application environments.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides a method and apparatus for generating flight paths, a storage medium, and an electronic device to at least solve the technical problem that the availability of flight paths is poor because existing flight path generation methods for aircraft do not take into account complex and ever-changing application environments.

[0005] According to one aspect of the embodiments of this application, a method for generating a flight path is provided, comprising: dividing the travel area of ​​an aircraft to obtain grid cells; determining the travel cost of the grid cells based on meteorological data; constructing a directed grid network according to the travel cost, wherein nodes in the directed grid network represent the grid cells, directed edges of the nodes are used to indicate the travel direction, and the travel cost is used to determine the edge weight of the directed edges; and generating a flight path of the aircraft based on the directed grid network.

[0006] According to another aspect of the embodiments of this application, a flight path generation apparatus is also provided, comprising: a partitioning module for partitioning the travel area of ​​an aircraft to obtain grid cells; a determining module for determining the travel cost of the grid cells based on meteorological data, and constructing a directed grid network according to the travel cost, wherein nodes in the directed grid network represent the grid cells, directed edges of the nodes are used to indicate the travel direction, and the travel cost is used to determine the edge weight of the directed edges; and a generation module for generating the flight path of the aircraft based on the directed grid network.

[0007] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, and the computer program is configured to execute the above-described method for generating the navigation path when it is run.

[0008] According to another aspect of the embodiments of this application, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the navigation path generation method as described above.

[0009] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-described method for generating a navigation path through the computer program.

[0010] In this embodiment, by finely dividing the flight area of ​​the aircraft to obtain grid cells and further constructing a directed grid network, the technical problem of poor availability of flight paths due to the fact that existing flight path generation methods do not consider complex and ever-changing application environments is effectively solved. Specifically:

[0011] First, this embodiment divides the aircraft's travel area into grid cells, ensuring that each grid cell can independently assess its travel capacity based on its geographical features and environmental conditions. Furthermore, considering that in traditional route planning, grid cells are considered undirected, meaning the travel cost is the same regardless of the direction of entry or exit, but due to the influence of meteorological data, such as wind speed and direction, the travel cost of the same grid cell can differ significantly in different directions, this embodiment further determines the travel cost of each grid cell in each direction based on meteorological data, and constructs a directed grid network accordingly. Finally, the aircraft's flight path is generated based on the constructed directed grid network.

[0012] In summary, the embodiments of this application incorporate wind speed costs into the flight path planning of aircraft, ensuring that aircraft can generate the lowest cost and most efficient flight path based on actual meteorological data. This solves the technical problem that the availability of flight paths is poor because existing flight path generation methods do not consider complex and ever-changing application environments. Attached Figure Description

[0013] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0014] Figure 1 This is a schematic diagram of the application environment of an optional navigation path generation method according to an embodiment of this application;

[0015] Figure 2 This is a flowchart illustrating an optional method for generating a navigation path according to an embodiment of this application;

[0016] Figure 3 This is a schematic diagram of an optional wind field data and grid cell mapping according to an embodiment of this application;

[0017] Figure 4 This is a schematic diagram of a toll cost generation model according to an embodiment of this application;

[0018] Figure 5 This is a schematic diagram of the generation process of a gridded directed network according to an embodiment of this application;

[0019] Figure 6 This is a schematic diagram of cost encoding for an optional passage cost according to an embodiment of this application;

[0020] Figure 7 This is a schematic diagram of an optional navigation path according to an embodiment of this application;

[0021] Figure 8 This is a schematic diagram of an optional flight point control process according to an embodiment of this application;

[0022] Figure 9 This is a schematic diagram of an optional navigation path generation process according to an embodiment of this application;

[0023] Figure 10 This is a schematic diagram of an optional navigation path generation device according to an embodiment of this application;

[0024] Figure 11 This is a schematic diagram of the structure of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] The present application will be described below with reference to embodiments:

[0028] According to one aspect of the embodiments of this application, a method for generating a navigation path is provided.

[0029] Optionally, in this embodiment, the above-mentioned method for generating flight paths can be applied to fields such as air transport management, drone logistics delivery, air traffic control, and low-altitude flight safety monitoring, so as to realize real-time planning and adjustment of complex air routes, flexibly respond to changing weather conditions, airspace control regulations and emergencies, and ensure the safety and efficiency of flight activities. Furthermore, the above-mentioned method for generating flight paths can be implemented by terminal devices or servers respectively, or by terminal devices and servers together. This application embodiment does not limit this.

[0030] For example, the method for generating the above-mentioned navigation path can be implemented jointly by a terminal device and a server. The process of this method may include the following steps:

[0031] S1, the terminal device collects the aircraft's position data and the meteorological data corresponding to the passage area, and then divides the aircraft's passage area according to the aircraft's position data to obtain grid cells;

[0032] S2, the terminal device sends the corresponding data of the grid cell and meteorological data to the server, so that the server can determine the passage cost of the grid cell based on the meteorological data and construct a grid directed network according to the passage cost. In the grid directed network, the nodes represent grid cells, the directed edges of the nodes are used to indicate the passage direction, and the passage cost is used to determine the edge weight of the directed edges.

[0033] S3, the server generates the flight path of the aircraft based on the grid directed network, or the server sends the configuration data required for the grid directed network to the terminal device, so that the terminal device can rebuild the grid directed network locally, and then the terminal device generates the flight path of the aircraft based on the grid directed network.

[0034] It should be noted that the aforementioned server connects to the terminal device via a network and can be used to provide services to the terminal device or the application installed on the terminal device to implement the above-mentioned method for generating the navigation path. A database can also be set up on the server or independently of the server to provide data storage services for implementing the above-mentioned method for generating the navigation path. The aforementioned server can be a single server, a server cluster consisting of multiple servers, or a cloud server. The aforementioned network can include, but is not limited to, wired networks and wireless networks. The wired network includes local area networks (LANs), metropolitan area networks (MANs), and wide area networks (WANs), and the wireless network includes Bluetooth, Wi-Fi, and other networks that enable wireless communication.

[0035] It should also be noted that the aforementioned terminal equipment can be the aircraft's own onboard computer system, or the computer equipment used by the ground control station (GCS), or mobile devices such as smartphones or tablets. As long as such devices have sufficient processing power and network connectivity to collect and transmit the aircraft's position data and environmental data, they can participate in the aforementioned method for generating flight paths.

[0036] In an exemplary embodiment, taking the aforementioned aircraft as an example, such as a drone, the method for generating the flight path can be applied, but is not limited to, to applications such as... Figure 1 The illustration shows an application environment including drones and a central processing center. In drone logistics delivery scenarios, this method can provide dynamic cost guidance for drone delivery route planning by analyzing meteorological data, avoiding areas with severe weather, reducing flight time and energy consumption, and improving delivery efficiency and success rate.

[0037] exist Figure 1In the illustrated application environment, the central processing center is responsible for collecting meteorological data, constructing a grid-directed network, and performing path planning. This center can be a server, a cloud computing platform, or other equipment with high-performance computing and storage capabilities. Specifically, the central processing center divides the data into grids based on pre-configured UAV location data and can also receive meteorological data from official meteorological websites. Based on this data, it calculates the travel cost, constructs a grid-directed network according to the travel cost, generates the UAV's flight path based on the grid-directed network, and finally sends the flight path to the UAV, allowing the UAV to perform corresponding flight tasks within the designated travel area.

[0038] Optionally, as an alternative implementation, either the aircraft itself or a central processing center with analytical computing capabilities can serve as the executing entity for the aforementioned flight path generation method, such as... Figure 2 As shown, taking the central processing center as the executing entity as an example, the method for generating the aforementioned navigation path executed by the central processing center includes:

[0039] S202, by dividing the passage area of ​​the aircraft, grid cells are obtained;

[0040] Optionally, in this embodiment, the aforementioned aircraft includes, but is not limited to, drones, weather observation aircraft, and other flight equipment types that possess autonomous flight capabilities or require route planning. The passage area of ​​the aforementioned aircraft refers to the range within which the aircraft can safely fly in space. This passage area excludes obstacles (such as mountains and tall buildings), controlled areas (such as military restricted zones and airport perimeters), and areas with unsuitable meteorological conditions for flight (such as strong wind zones and thunderstorm areas), ensuring that the aircraft avoids these dangerous or restricted locations when planning its route. The aforementioned grid cell refers to a virtual unit area that divides the passage area; the shape of this area can be a cube, prism, etc., and this application does not impose any limitations on this.

[0041] For example, the passage area of ​​the aircraft can be divided using the GeoSOT (Global Discrete Partitioning Coding System) to obtain grid cells, specifically:

[0042] The central processing center first obtains the preset start and end coordinates of the aircraft. Both start and end coordinates are three-dimensional coordinates including altitude, longitude, and latitude. Then, based on the start and end coordinates, the type of access area where the aircraft is located is determined, or the preset access area type corresponding to the aircraft is directly determined. Then, the partitioning parameters are obtained according to the start coordinates, end coordinates, and access area type. GeoSOT partitioning is performed according to the partitioning parameters to obtain grid cells. The embodiments of this application do not specifically limit the number of grid cells after partitioning.

[0043] Specifically, when determining the type of access area where the aircraft is located based on the starting point coordinates and the ending point coordinates, the following may be included, but are not limited to:

[0044] S1, when both the starting and ending points of the aircraft are in urban areas, the passage area type is determined to be urban area type;

[0045] S2, when both the starting and ending points of the aircraft are in rural areas, the passage area type is determined to be rural area type.

[0046] In other words, the type of passage area can be understood as the main operating environment of the aircraft throughout the entire flight, which is related to the environmental conditions in which the aircraft is located. In addition, the type of passage area can be preset without being determined based on the starting and ending points of the aircraft. That is, it can be preset according to common application scenarios to quickly start the route planning process.

[0047] Specifically, when obtaining the partitioning parameters based on the starting point coordinates, ending point coordinates, and the type of travel area, these partitioning parameters include, but are not limited to, grid level, travel envelope range, and altitude domain range. Grid level refers to the size or resolution of a single grid cell determined according to the GeoSOT partitioning method; the higher the grid level, the smaller the grid cell and the higher the resolution, and vice versa. The travel envelope range refers to the geographical boundary of the flight path, and the altitude domain range refers to the vertical interval of the aircraft's travel area. Further, taking the grid level, travel envelope range, and altitude domain range as examples, the specific determination steps may include, but are not limited to:

[0048] Grid level: Determine the access area type; determine the grid level from a preset mapping relationship list based on the access area type. The preset mapping relationship list includes at least one set of mapping data, which includes an access area type and a grid level corresponding to that access area type. The purpose of this mapping relationship list is to store the mapping relationship between grid levels and access area types. Therefore, it is not limited to the form of a list and can be a database, hash table, or any structure that can quickly query and match, as long as it can achieve a fast correspondence between access area types and grid levels.

[0049] For example, if the passage area type is urban, due to the dense buildings and complex flight environment, the grid level is determined to be 26, with a corresponding cell size of about 1 meter, in order to improve the ability to capture obstacles and flight details; if the passage area type is rural, the grid level is determined to be 23, with a corresponding cell size of about 7.7 meters, in order to reduce the amount of calculation.

[0050] Passage envelope range: Connect the starting point coordinates and the ending point coordinates to obtain the corresponding line. Determine the initial range based on the line. Add a preset buffer range to the initial range to obtain the passage envelope range.

[0051] For example, first connect the starting point coordinates and the ending point coordinates to obtain a line. Using this line as a reference, determine an initial range. Assuming the line is in an east-west direction (the starting point and ending point coordinates are represented in three-dimensional coordinates), the starting point coordinates are (114.2°E, 39.7°N, 0m), and the ending point coordinates are (116.0°E, 38.0°N, 300m). The initial range connecting these two points is longitude from 114.2°E to 116.0°E, latitude from 38.0°N to 39.7°N, and altitude from 0m to 300m. Based on the initial range, add a preset buffer range. The size of this buffer range can be set according to actual needs and application scenarios. Assuming the preset buffer range is longitude ±0.2°, latitude ±0.15°, and altitude ±10m, the travel envelope range is obtained as follows:

[0052] Longitude [114.0°E, 116.2°E]: With the buffer range added by 0.2° before and after, the longitude of the travel envelope range is from 114.2°E-0.2° to 116.0°E+0.2°, that is, from 114.0°E to 116.2°E;

[0053] Latitude [37.85°N, 39.85°N]: With the buffer range added by 0.15° before and after, the latitude of the passable envelope range is from 38.0°N-0.15° to 39.7°N+0.15°, that is, from 37.85°N to 39.85°N;

[0054] Height [-10m, 310m]: With the buffer range increased by 10m above and below, the height of the passage envelope ranges from 0m-10m to 300m+10m, that is, from -10m to 310m.

[0055] Height range: Determine the coordinates of the highest and lowest points within the travel envelope, and determine the height range based on the altitude of the highest and lowest point coordinates.

[0056] For example, if the highest elevation within the area connected by the starting and ending points is 2000 meters and the lowest elevation is 500 meters, then the determined elevation range is from 500 meters to 2000 meters.

[0057] It should be noted that the GeoSOT subdivision method refers to dividing the Earth's surface into multiple grid cells of different scales, each with a unique code. The subdivision progresses from global to local areas, with the code length increasing with the subdivision level, accurately representing geospatial location and extent. Its coding structure is simple, easy to calculate and convert, and efficiently supports the indexing, querying, and analysis of geospatial data. It is widely used in geographic information systems, remote sensing image processing, and spatial big data management, providing an effective method for the unified representation and processing of global geospatial data.

[0058] Furthermore, the steps for implementing GeoSOT partitioning according to the partitioning parameters to obtain grid cells include, but are not limited to:

[0059] S1, based on a defined grid level, uses the GeoSOT algorithm to subdivide the geographic space within the access envelope and generate grid cells. The size of each grid cell is determined according to the selected grid level. For example, in the urban area type, a 26-level subdivision is used to generate a grid with a cell size of approximately 1 meter.

[0060] S2, For each generated grid cell, the GeoSOT algorithm pre-assigns a unique GeoSOT code based on its geographical location and partitioning parameters. This code reflects the precise location and hierarchy of the grid cell in the global partitioning system.

[0061] Understandably, as the grid cells are subdivided, each grid cell acquires a unique code. This code is based on the code of the previous grid level plus a character indicating the position of the grid cell at the current grid level.

[0062] S3 organizes and stores information about grid cells based on the assigned encoding and grid level, including location information, encoding, and the height domain range to which they belong.

[0063] Furthermore, after dividing the passage area into grid cells, the passage cost of each grid cell will be determined, thereby constructing a grid-directed network, including but not limited to the steps described in S204.

[0064] S204. Determine the passage cost of grid cells based on meteorological data, and construct a directed grid network according to the passage cost. In the directed grid network, nodes represent grid cells, the directed edges of nodes are used to indicate the passage direction, and the passage cost is used to determine the edge weight of the directed edges.

[0065] Optionally, in the embodiments of this application, the meteorological data mentioned above refers to data on various environmental factors in three-dimensional space, including but not limited to wind field data, temperature distribution data, air pressure change data, visibility data, etc.

[0066] Taking meteorological data, including wind field data, as an example, specifically including but not limited to the U (east-west), V (north-south), and W (vertical) components of wind speed, as well as vector information of wind direction, this wind field data can reflect the wind field conditions of different time periods and different grid cells. Specifically, the wind field data is represented as follows:

[0067] U component: East-west direction, corresponding to the east side E and west side W of the grid, representing the horizontal velocity component of the wind from east to west or from west to east;

[0068] V component: North-south direction, corresponding to the south side S and north side N of the grid, representing the horizontal velocity component of the wind from south to north or from north to south;

[0069] W component: Vertical direction, corresponding to the top U and bottom D of the grid, representing the vertical velocity component of the wind from top to bottom or from bottom to top.

[0070] Taking meteorological data, including temperature distribution data, as an example, this specifically includes, but is not limited to, temperature values ​​at different times and different altitudes.

[0071] Taking meteorological data, including air pressure change data, as an example, specifically including but not limited to air pressure change values ​​at different times and different altitudes.

[0072] Taking meteorological data, including visibility data, as an example, this includes, but is not limited to, visibility values ​​at different times and different altitudes.

[0073] Optionally, in the embodiments of this application, the above-mentioned passage cost refers to the additional energy consumption or time required for the aircraft to pass through the grid cell in any passage direction. It can be understood as the energy or time cost required to pass through the grid cell, and there is a passage cost corresponding to each passage direction.

[0074] Optionally, in the embodiments of this application, the above-mentioned grid directed network refers to a network structure composed of grid cells that has directional and cost attributes. Each grid cell is a node in the network, and the directed edge between it and its adjacent grid cells represents the travel direction, and the weight of the edge represents the travel cost.

[0075] It should be noted that when determining the passage cost of a grid cell based on meteorological data, multiple grid cells can be calculated in parallel, or individual grid cells can be calculated sequentially. This application does not impose any restrictions on this.

[0076] It should also be noted that meteorological data can be from historical periods or future periods. In other words, the meteorological data can be real data from historical periods or predicted data from future periods. For example, suppose the current time obtains the real meteorological data of the area for the previous 2 hours from the official meteorological website, and then determines the passage cost of the grid cell based on the real meteorological data of the previous 2 hours. Alternatively, the current time obtains the predicted meteorological data of the area for the next 2 hours from the official meteorological website, and then determines the passage cost of the grid cell based on the predicted meteorological data of the next 2 hours.

[0077] For example, taking meteorological data as wind field data, the travel cost of each grid cell in different travel directions is first determined. This travel cost includes component travel costs corresponding to multiple different travel directions. Then, a directed grid network is constructed based on this travel cost and the location of the grid cell. Specifically:

[0078] When determining the travel cost of each grid cell in different travel directions, including but not limited to:

[0079] S1. Considering that the GeoSOT algorithm performs planar partitioning using whole warp and weft, meaning the two bottom edges of the partitioned grid correspond exactly to the east-west and north-south directions, which aligns with the wind field data format, the wind field data is first mapped to different travel directions of the grid cells. That is, each velocity dimension of the wind field data is mapped to a face of the grid cell. This mapping is illustrated as follows: Figure 3 As shown;

[0080] For example, the wind field data is (U = eastward wind speed, V = northward wind speed, W = vertical wind speed). Taking the eastward-to-westward travel direction as an example, the eastward wind speed U will affect the component travel cost of the eastward-to-west (WE) travel direction, the northward wind speed V will affect the component travel cost of the southward-to-north (SN) travel direction, and the vertical wind speed W will affect the component travel cost of the bottom-up (DU) and top-down (UD) travel directions.

[0081] S2 generates the corresponding passage cost based on the wind speed value in each direction of passage.

[0082] For example, the higher the forward wind speed, the lower the passage cost; the higher the reverse wind speed, the higher the passage cost; the passage cost corresponding to reverse wind speed > the passage cost corresponding to no wind > the passage cost corresponding to forward wind speed.

[0083] Specifically, assuming the passage cost is 5 when the wind speed is 0, the generation model for this passage cost is expressed as y = -0.51x + 5, where x is the wind speed value (positive for forward winds and negative for reverse winds), and y is the corresponding passage cost value, which can be represented as follows: Figure 4As shown, the cost is set to a baseline value of 5 when the wind speed is 0.

[0084] For example, the wind field data includes a normal east-to-west wind direction with a wind speed of 3, and the grid cell's east-to-west component has a travel cost of -0.51. 3 + 5 = 3.47, generally rounded to 3; the component travel cost of the grid cell from west to east is -0.51. (-3) + 5 = 6.53, which is usually rounded to 6. The value of this component's toll cost ranges from 1 to 9.

[0085] When constructing a directed grid network based on the passage cost and the location of the grid cells, including but not limited to:

[0086] Determine the component travel cost of each grid cell in each travel direction. Then, set the component travel cost as the edge weight of the corresponding travel direction, and represent the grid cell as the corresponding node, such as... Figure 5 As shown, with Figure 5 Take node A as an example:

[0087] S1, grid cell A has adjacent grid cells in both the east-to-west and south-to-north travel directions. Grid cell A is represented as node A.

[0088] S2, obtain the component travel cost a corresponding to the east-to-west travel direction of grid cell A and the component travel cost b corresponding to the south-to-north travel direction.

[0089] S3 sets the travel cost of each component as the edge weight of the directed edge corresponding to the travel direction of node A.

[0090] It should be noted that if there are six travel directions of a grid cell (east to west, west to east, south to north, north to south, top to bottom, and bottom to top) with adjacent grid cells, then the directed edges corresponding to these six travel directions and the corresponding component travel costs can be established.

[0091] For example, the passage cost can also be stored as a string encoding; assuming the wind speed data from south to north is 4.8, the wind speed data from east to west is 3, and the wind speed data from top to bottom is 2, the generation model of the passage cost is represented as y = -0.51x + 5, and the component passage costs are all taken as integer parts, then we can obtain:

[0092] The cost of traveling from east to west is -0.51. 3 + 5 = 3, the cost of traveling from west to east is -0.51. (-3) + 5 = 6;

[0093] The component travel cost from south to north is -0.51. 4.8 + 5 = 2, the cost of traveling from north to south is -0.51. (-4.8) + 5 = 7;

[0094] The component passage cost from top to bottom is -0.51 2 + 5 = 3, the cost of passage from bottom to top is -0.51. (-2) + 5 = 6.

[0095] Then follow as follows Figure 6 The rule shown is encoded and stored as C632763, specifically:

[0096] The first priority value is C, which represents the cost code identifier symbol;

[0097] The second priority value is 6, representing the cost of passage from west to east; the third priority value is 3, representing the cost of passage from east to west.

[0098] The fourth priority value is 2, representing the component passage cost from south to north; the fifth priority value is 7, representing the component passage cost from north to south.

[0099] The 6th priority value is 6, representing the component passage cost from bottom to top; the 7th priority value is 3, representing the component passage cost from top to bottom.

[0100] It should be noted that the corresponding position of the encoding can be set flexibly, as long as it corresponds to the component pass encoding of the corresponding direction.

[0101] Furthermore, after the grid-directed network is constructed, the corresponding flight path of the aircraft can be generated using the grid-directed network, including but not limited to the steps described in S206.

[0102] S206, generating flight paths for aircraft based on grid-directed networks.

[0103] Optionally, in the embodiments of this application, the flight path refers to the planned flight trajectory of the aircraft from the starting point to the ending point in three-dimensional space.

[0104] For example, the flight path of the aircraft can be generated using the grid-directed network in ways including but not limited to:

[0105] S1, determine the passage cost data for each node;

[0106] For example, taking meteorological data as wind field data, the passage cost data here refers to the total cost incurred by the aircraft due to the wind field influence when passing through grid cells in different directions, including but not limited to actual cost (first cost data) and heuristic cost (second cost data).

[0107] The actual cost is expressed as follows:

[0108] ;

[0109] Among them, G n d represents the actual cost of node N. i Let f(i) be the Euclidean distance from node i to its parent node, and f(i) be the travel cost of node i. Node i is the node whose travel cost data has been determined between node N and the corresponding node of the grid cell where the starting coordinates of the spacecraft are located. Considering that the travel cost may include component travel costs corresponding to multiple travel directions, the travel cost here may include, but is not limited to, the sum of the component travel costs corresponding to each travel direction of node i, or the component travel costs corresponding to the relative travel directions between node i and node N. For example, if node N is located south of node i, the travel cost component of node i from south to north will be used when calculating the travel cost; similarly, if node N is located east of node i, the travel cost component from east to west will be used; if node N is located southeast of node i, the sum of the component travel costs from east to west and the component travel costs from south to north will be used.

[0110] The heuristic cost is represented as:

[0111] ;

[0112] Among them, H n Let be the heuristic cost of node N, and D be the Euclidean distance from node N to the destination. F1, F2, and F3 are the angles between the direction from node N to the destination and the east-west, north-south, and vertical directions, respectively. F1, F2, and F3 are the travel costs of node N in the east-west, north-south, and vertical directions, respectively.

[0113] Furthermore, considering that the east-west direction can be from east to west or from west to east; similarly, the north-south direction can be from south to north or from north to south; and the vertical direction can be from top to bottom or from bottom to top, when the angle between the direction from the Nth node to the destination and the east-west direction is the same as the angle between the direction from the Nth node to the destination and the east-west travel direction, then F1 refers to the component travel cost of the Nth node in the east-west travel direction; similarly, when the angle between the direction from the Nth node to the destination and the north-south direction is the same as the angle between the direction from the Nth node to the destination and the south-north travel direction, then F2 refers to the component travel cost of the Nth node in the south-north travel direction. This application does not limit this.

[0114] The actual cost and heuristic cost are then combined to determine the passage cost data corresponding to the node. Specifically, the combination here includes, but is not limited to, direct addition, weighted summation, etc., and this application does not limit this.

[0115] S2, using the A path planning algorithm to perform a path search operation on the grid directed network based on the passage cost data, to determine at least two target nodes. Here, at least two target nodes are the grid cell corresponding to the starting coordinates of the aircraft and the grid cell corresponding to the ending coordinates of the aircraft.

[0116] S3, Generate the navigation path based on at least two of the target nodes.

[0117] Specifically, during the execution of the A-path planning algorithm, the priorities of nodes in the open and closed lists are continuously adjusted, taking into account the dynamic cost of each grid cell, until the path with the lowest cost is found. This path is the flight path of the aircraft.

[0118] It should be noted that the A path planning algorithm (also known as A...) The algorithm is a widely used algorithm for pathfinding and graph traversal. It is an improved version of Dijkstra's algorithm and can find the shortest path from the starting point to the ending point more efficiently based on heuristic search.

[0119] In one exemplary embodiment, the application scenario of drone delivery service within an urban area is taken as an example:

[0120] S1, Determine the grid cell: Assume the drone's starting point is located on the rooftop of a building, and its ending point is located in a park. Based on the latitude and longitude information of the starting and ending points, determine the scene grid level as 26 (1m), the passage envelope range from 116.2°E to 116.5°E, 39.9°N to 40.1°N, and the altitude domain range from the ground to 100 meters.

[0121] S2, Identify Passable Areas: By acquiring real-time no-fly zones for drones, terrain obstacles, and meteorological data such as wind speed and rainfall, the system identifies obstacle areas, restricted areas, and areas with abnormal weather. For example, if meteorological data indicates an area at 116.3°E, 40.0°N with wind speeds exceeding 7.9 m / s, the grid cells in that area will be marked as impassable. Simultaneously, static obstacle areas such as tall buildings and high-voltage power line towers within the city are also marked as impassable, retaining only grid cells with no wind, suitable wind speeds, and no obstacles as passable areas.

[0122] S3. Construct a directed grid network: Based on the acquired meteorological data, calculate the wind speed values ​​in six directions (east, west, south, north, up, and down) for each grid cell corresponding to the passable area, and determine the passage cost based on the wind speed values. For example, if the wind speed is forward (tailwind), the passage cost is lower; if the wind speed is reverse (headwind), the passage cost is higher. In this way, the passage cost of each grid cell is determined, thus constructing a directed grid network, where each grid cell acts as a node, directed edges represent flight directions, and edge weights represent the passage cost in that direction.

[0123] S4. Route planning using dynamic cost: Based on the constructed grid-based directed network, the A-path planning algorithm is used, combined with travel cost calculation, to search node by node from the UAV's starting point until the destination. During the search process, the A-path planning algorithm evaluates the path cost based on the travel cost of each node, thereby selecting the lowest-cost flight path, such as a flight path with the wind.

[0124] Furthermore, such as Figure 7 As shown, flight path A is the flight path generated according to the embodiment of this application, and flight path B is the flight path directly generated according to the existing A-path planning algorithm. In this embodiment, the impact of meteorological data on flight costs is quantified into specific travel costs, thereby providing a more accurate cost calculation basis for path planning. The Euclidean distance cost of the existing A-path planning algorithm is replaced with the aforementioned travel costs to adapt to complex and ever-changing meteorological environments and ensure that route planning is always in an optimal state.

[0125] It should be noted that during actual flight, the aircraft can be controlled to use the center of each grid cell as a waypoint each time it flies from one grid cell to the next, until it reaches the center of the penultimate grid cell. From there, it flies directly to the position corresponding to the destination coordinates. This refers to the grid cell preceding the destination coordinates. The flight point control process is as follows: Figure 8 As shown:

[0126] S802, determine the current node in the navigation path corresponding to the current grid cell;

[0127] S804, determine the next grid cell corresponding to the next node based on the current node;

[0128] S806, the aircraft flies from its current position to the center of the next grid cell;

[0129] S808: Is the grid cell where the aircraft is currently located the second to last grid cell? If yes, execute S810; otherwise, return to S804 and continue execution.

[0130] S810: The aircraft flies directly from its current position to the position corresponding to the destination coordinates.

[0131] Through the embodiments of this application, the passage area of ​​the aircraft is finely divided to obtain grid cells and further construct a directed grid network. This effectively solves the technical problem that the availability of flight paths is poor because existing flight path generation methods do not consider complex and ever-changing application environments. Specifically:

[0132] First, this embodiment divides the aircraft's travel area into grid cells, ensuring that each grid cell can independently assess its travel capacity based on its geographical features and environmental conditions. Furthermore, considering that in traditional route planning, grid cells are considered undirected, meaning the travel cost is the same regardless of the direction of entry or exit, but due to the influence of meteorological data, such as wind speed and direction, the travel cost of the same grid cell can differ significantly in different directions, this embodiment further determines the travel cost of each grid cell in each direction based on meteorological data, and constructs a directed grid network accordingly. Finally, the aircraft's flight path is generated based on the constructed directed grid network.

[0133] In summary, the embodiments of this application integrate the travel cost generated based on meteorological data into the flight path planning of the aircraft, ensuring that the aircraft can generate the lowest cost and most efficient flight path, thereby solving the technical problem that the availability of flight paths is poor because the existing flight path generation methods of aircraft do not take into account the complex and ever-changing application environment.

[0134] As an optional approach, the above-mentioned method of determining the passage cost of a grid cell based on meteorological data includes: determining the current wind speed parameter based on the height of the grid cell and meteorological data, wherein the meteorological data includes at least one wind speed parameter corresponding to the height; and determining the passage cost based on a preset cost parameter and the current wind speed parameter, wherein the preset cost parameter is used to indicate the passage cost in a windless state.

[0135] Optionally, in the embodiments of this application, the determination of the current wind speed parameter refers to the matching of the aircraft's predetermined flight altitude with the corresponding wind speed data, including but not limited to determining the wind speed value of the altitude layer where the aircraft is located based on a preset multi-level altitude wind speed dataset, which can take into account the differences in wind speed at different altitude layers, thereby affecting the aircraft's travel cost.

[0136] Optionally, in the embodiments of this application, the above-mentioned wind speed parameters can be expressed as at least one of the U component (east-west wind speed), V component (north-south wind speed), and W component (vertical wind speed).

[0137] It should be noted that different grid cells can be at the same or different heights, so the corresponding current wind speed parameters can also be the same or different.

[0138] For example, the preset cost parameter is used to indicate the passage cost in a windless state. The preset cost parameter is adjusted according to the current wind speed parameter to determine the passage cost. That is, the cost calculation includes not only the static cost (the passage cost in a windless state) but also the dynamic cost (caused by wind speed) to ensure the comprehensiveness of the cost calculation and make the route planning closer to the actual flight situation.

[0139] In one exemplary embodiment, taking the application scenario of UAV route planning as an example:

[0140] S1, acquire meteorological data corresponding to the current position of the drone, including the U component (east-west wind speed), V component (north-south wind speed) and W component (vertical wind speed) corresponding to the first altitude, and the U component (east-west wind speed), V component (north-south wind speed) and W component (vertical wind speed) corresponding to the second altitude.

[0141] S2, determine the height of the grid cell. For example, the passage area includes two layers of grid cells in the vertical direction. The first layer of grid cells is located at the first height, and the second layer of grid cells is located at the second height. Therefore, the current wind speed parameters corresponding to the first layer of grid cells are the U component (east-west wind speed), V component (north-south wind speed), and W component (vertical wind speed) corresponding to the first height; the current wind speed parameters corresponding to the second layer of grid cells are the U component (east-west wind speed), V component (north-south wind speed), and W component (vertical wind speed) corresponding to the second height.

[0142] S3 calculates the travel cost of each grid cell in each travel direction based on preset cost parameters and current wind speed parameters.

[0143] Through the embodiments of this application, the passage cost calculation for each grid cell is completed. The passage cost of the grid cell is dynamically adjusted through wind speed data, enabling route planning to adapt to the constantly changing weather conditions during flight and ensuring the efficient execution of the aircraft's flight mission.

[0144] As an optional approach, the above-mentioned determination of the current wind speed parameter based on the height of the grid cell and meteorological data includes at least one of the following: when the meteorological data includes a target wind speed parameter, the target wind speed parameter is determined as the current wind speed parameter, wherein the target wind speed parameter represents the wind speed parameter corresponding to the height of the grid cell; when the meteorological data does not include a target wind speed parameter, an interpolation operation is performed on the meteorological data to determine the current wind speed parameter, wherein the target wind speed parameter represents the wind speed parameter corresponding to the height of the grid cell.

[0145] Optionally, in this embodiment, the current wind speed parameter is determined based on the height of the grid cell and meteorological data, including but not limited to the following two cases: when the meteorological data already covers the wind speed parameter at the height of the grid cell, the wind speed parameter at the corresponding height is directly used as the target wind speed parameter; when the meteorological data does not cover the wind speed parameter at the height of the grid cell, the target wind speed parameter is generated through interpolation.

[0146] It should be noted that the above interpolation operations include, but are not limited to, linear interpolation, bilinear interpolation, or multidimensional interpolation, etc., and this application does not make any specific limitations on them.

[0147] In one exemplary embodiment, taking the application scenario of UAV route planning as an example:

[0148] S1. Search for the target wind speed parameter at the height of the grid cell in the acquired meteorological data. If it exists, apply the parameter directly.

[0149] S2. If the wind speed parameter is missing, interpolation is performed based on the adjacent height values ​​of the meteorological data to obtain the target wind speed parameter at the height of the grid cell.

[0150] For example, if the grid cell is at an altitude of 300 meters, but the meteorological data does not provide wind speed parameters at 300 meters, but provides wind speed parameters at altitudes of 200 meters and 400 meters, taking one of the east-to-west traffic directions as an example:

[0151] The wind speed at a height of 300 meters can be calculated using linear interpolation, based on wind speeds at 200 meters (assumed to be 5 m / s) and 400 meters (assumed to be 7 m / s). Specifically:

[0152] Based on the linear relationship between the wind speed parameters at 200 meters and 400 meters, the wind speed value at 300 meters is determined to be between 5 m / s and 7 m / s. By calculating the difference between 200 meters and 400 meters (2 m / s), and based on the position of the target height of 300 meters relative to the reference heights (200 meters and 400 meters), the east-to-west component of the target wind speed parameter at 300 meters is obtained as 6 m / s.

[0153] Through the embodiments of this application, wind speed parameters are obtained and combined with interpolation operations, achieving the technical effect of accurately determining wind speed parameters at any altitude, thus achieving the goal of adapting to complex meteorological environments and improving the flexibility of flight route planning.

[0154] As an optional approach, the aforementioned current wind speed parameters include at least one of horizontal component wind speed parameters and vertical component wind speed parameters, wherein the horizontal component includes at least one of east-to-west, west-to-east, south-to-north, and north-to-south, and the vertical component includes at least one of top-down and bottom-up; the travel cost includes at least one of horizontal component travel cost and vertical component travel cost, wherein the horizontal component travel cost is determined based on the horizontal component wind speed parameters, and the vertical component travel cost is determined based on the vertical component wind speed parameters.

[0155] Optionally, in this embodiment, the wind speed parameter encompasses both horizontal and vertical components, specifically relating to wind speed measurements from east to west, west to east, south to north, north to south, and from top to bottom and bottom to top. The passage cost is correspondingly subdivided into horizontal component passage cost and vertical component passage cost, the calculation of which is directly related to the horizontal and vertical wind speed parameters.

[0156] It should be noted that the horizontal component travel cost is calculated based on the east-west and north-south wind speed components, while the vertical component travel cost is based on the vertical wind speed component. This application does not specify the details of this calculation method.

[0157] For example, the determination of passage costs depends not only on the wind speed but also on the degree of match between the wind direction and the flight direction. When the wind speed is in the same direction as the flight direction, the cost is lower; conversely, when the wind speed is in the opposite direction to the flight direction, the cost is higher.

[0158] In an exemplary embodiment, the horizontal component wind speed parameter is applied to the construction of a grid-directed graph as an example:

[0159] S1. First, obtain the U and V component data of the current wind field from the wind speed monitoring system. These data represent the wind speed intensity in the east-west and north-south directions.

[0160] S2. Then, the U and V components are mapped to the corresponding cost values, i.e., the cost value is lower when the wind speed is in the direction of the drone's flight and higher when the wind speed is not in the direction of the drone's flight.

[0161] Through the embodiments of this application, the horizontal and vertical components of wind speed are analyzed in detail, providing more comprehensive data support for the selection of flight paths for aircraft. At different flight directions and altitudes, the travel cost weights can be flexibly adjusted, so that the subsequently generated grid directed network can more accurately reflect the real conditions of the flight environment.

[0162] As an optional approach, the above method of determining the passage cost based on preset cost parameters and current wind speed parameters includes: determining the target product of preset wind speed weight value and current wind speed parameter; and determining the sum of the target product and preset cost parameter as the passage cost.

[0163] Optionally, in this embodiment, the target product of the aforementioned wind speed weight value and the current wind speed parameter refers to weighting the currently measured wind speed value using predefined wind speed weights to reflect the specific impact on flight costs under specific wind speed conditions. This includes, but is not limited to, assigning a higher wind speed weight to the headwind direction and a lower wind speed weight to the tailwind direction, or using the same wind speed weight value, to achieve fine-tuning of the wind field's effect on flight costs.

[0164] It should be noted that the preset cost parameters can come from multiple sources, such as the performance parameters of the UAV itself, terrain features, airspace control regulations, etc., and this application does not limit them.

[0165] In one exemplary embodiment, taking the application scenario of UAV route planning as an example:

[0166] S1, determine the preset wind speed weight value, for example, set a higher weight in the headwind direction and a lower weight in the tailwind direction, to reflect the impact of wind speed on flight costs.

[0167] S2, obtain the current wind speed parameters, including real-time monitored wind speed data and wind direction information.

[0168] S3, calculate the target product, which is to multiply the current wind speed value by the corresponding wind speed weight value to obtain the target product. This target product reflects the degree of wind speed influence of the grid cell.

[0169] S4. Add the target product to the preset cost parameter to determine the passage cost of the grid cell.

[0170] As an optional approach, the above method further includes at least one of the following: determining a first product of a preset wind speed weight value and a first component wind speed parameter, and determining the sum of the first product and a preset cost parameter as the first component travel cost, wherein the first component wind speed parameter represents the east-to-west component wind speed parameter in the current wind speed parameters, and the first component travel cost represents the east-to-west component travel cost in the travel cost; determining a second product of a preset wind speed weight value and a second component wind speed parameter, and determining the sum of the second product and a preset cost parameter as the second component travel cost, wherein the second component wind speed parameter represents the west-to-east component wind speed parameter in the current wind speed parameters, and the second component travel cost represents the east-to-west component travel cost in the travel cost. The west-to-east component travel cost; determine the preset wind speed weight value and the third product of the third component wind speed parameter, and determine the third component travel cost as the sum of the third product and the preset cost parameter, where the third component wind speed parameter represents the south-to-north component wind speed parameter in the current wind speed parameters, and the third component travel cost represents the south-to-north component travel cost in the travel cost; determine the preset wind speed weight value and the fourth product of the fourth component wind speed parameter, and determine the fourth component travel cost as the sum of the fourth product and the preset cost parameter, where the fourth component wind speed parameter represents the north-to-south component wind speed parameter in the current wind speed parameters, and the fourth component travel cost represents the north-to-south component travel cost in the travel cost.

[0171] As an optional approach, the above method further includes at least one of the following: determining a preset wind speed weight value and a fifth product of the fifth component wind speed parameter, and determining the sum of the fifth product and a preset cost parameter as the fifth component travel cost, wherein the fifth component wind speed parameter represents the top-down component wind speed parameter in the current wind speed parameters, and the fifth component travel cost represents the top-down component travel cost in the travel cost; determining a preset wind speed weight value and a sixth product of the sixth component wind speed parameter, and determining the sum of the sixth product and a preset cost parameter as the sixth component travel cost, wherein the sixth component wind speed parameter represents the bottom-up component wind speed parameter in the current wind speed parameters, and the sixth component travel cost represents the bottom-up component travel cost in the travel cost.

[0172] Optionally, in the embodiments of this application, the first to sixth wind speed parameters are the components of the current wind speed parameters along a specific direction, including from east to west, from west to east, from south to north, from north to south, from top to bottom, and from bottom to top, reflecting the specific values ​​of wind speed in each direction; the preset cost parameter is a basic cost value used for cost setting when there is no wind speed influence.

[0173] In one exemplary embodiment, taking the application scenario of dynamic cost generation for route planning as an example:

[0174] S1. First, a preset wind speed weight value is determined. This wind speed weight value is set based on the analysis of wind speed sensitivity. For example, it can be -0.51. The specific value can be flexibly set. This application embodiment does not make specific limitations.

[0175] S2, Next, obtain the component wind speed parameters corresponding to the six traffic directions in the current wind speed parameters, namely the component wind speed parameters from east to west, from west to east, from south to north, from north to south, from top to bottom, and from bottom to top.

[0176] S3, calculate the product of each component wind speed parameter and the current wind speed parameter according to the direction of travel;

[0177] S4. Add the above product to the preset cost parameters respectively to obtain the component travel cost corresponding to each travel direction, namely the component travel cost from east to west, the component travel cost from west to east, the component travel cost from south to north, the component travel cost from north to south, the component travel cost from top to bottom, and the component travel cost from bottom to top.

[0178] S5 integrates the cost values ​​from these six directions into a single value such as... Figure 6 The six-directional cost codes shown are used as input for subsequent route planning algorithms.

[0179] For example, the generation model for toll cost is represented as y = -0.51x + 5, where the preset wind speed weight is -0.51, x represents the current wind speed parameter, the east-to-west component wind speed parameter (Uw) is 2 m / s; the west-to-east component wind speed parameter (Ue) is -2 m / s; the south-to-north component wind speed parameter (Vs) is 3 m / s; the north-to-south component wind speed parameter (Vn) is -3 m / s; the top-to-bottom component wind speed parameter (Wd) is 1 m / s; and the bottom-to-up component wind speed parameter (Wu) is -1 m / s. The east-to-west component toll cost is used.

[0180] Furthermore, the component travel cost from east to west is -0.51. 2 + 5 = 4.98, generally rounded to 5; similarly, the cost of the component traveling from west to east is -0.51. (-2) + 5 = 5.02, which is generally rounded to 5; the same applies to the north-south and vertical directions, which will not be elaborated here.

[0181] Through the embodiments of this application, a dynamic cost generation mechanism is adopted to achieve the technical effect of adaptively adjusting the toll cost according to real-time weather conditions, thereby improving the efficiency and safety of route planning and optimizing the flight path.

[0182] As an optional approach, the above-mentioned construction of a grid-directed network based on travel cost includes: determining the target travel cost of a first grid cell based on meteorological data, wherein the first grid cell is any grid cell; determining a second grid cell adjacent to the first grid cell; establishing a target directed edge based on a first travel direction between the first and second grid cells, and setting the edge weight of the target directed edge based on the target travel cost, wherein the target directed edge starts from a first node and connects to a second node, the first node representing the first grid cell and the second node representing the second grid cell; and constructing a grid-directed network based on the first node, the second node, and the target directed edge.

[0183] It should be noted that the connection between the first grid cell and the second grid cell can be any face of a hexahedron, i.e., the six directions of east, west, south, north, up, and down, so that the constructed directed grid network can better fit the actual flight requirements and directional preferences of the aircraft. Furthermore, it can also be other directions, such as southeast, northwest, etc. This application does not limit these directions.

[0184] In one exemplary embodiment, taking the application scenario of route planning as an example:

[0185] S1, determine the start and end grid cells within the scene range;

[0186] S2, calculate the passage cost of the starting grid unit based on real-time meteorological data, including the cost value in each passage direction;

[0187] S3, identify the grid cells adjacent to the starting grid cell, and establish directed edges for the connection between these grid cells and the starting grid cell. The weight of the edge is determined by the target passage cost.

[0188] S4. Repeat steps S2 and S3 until a grid-directed network covering the entire scene is constructed.

[0189] S5 uses the A-path planning algorithm combined with the weights of edges in the grid directed network to plan the optimal flight path from the starting point to the destination as the aforementioned flight path.

[0190] The embodiments of this application achieve an effective combination of toll cost generation and route planning, and construct a grid-directed network by combining meteorological data, thereby optimizing flight paths, improving flight safety and efficiency, and reducing flight costs.

[0191] As an optional approach, the above-mentioned setting of the edge weight of the target directed edge based on the first travel cost includes at least one of the following: when the first travel direction is from east to west, setting the east-to-west component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from west to east, setting the west-to-east component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from south to north, setting the south-to-north component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from north to south, setting the north-to-south component of the first travel cost as the edge weight of the target directed edge.

[0192] As an optional approach, the above method further includes at least one of the following: when the first travel direction is from top to bottom, setting the travel cost of the top-down component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from bottom to top, setting the travel cost of the bottom-up component of the first travel cost as the edge weight of the target directed edge.

[0193] Optionally, in the embodiments of this application, the edge weight of the directed edge of the first passage cost setting target refers to the specific determination of the passage cost of the directed edge in a specific direction based on the wind speed components in different directions, including but not limited to the passage cost setting in six directions: east to west, west to east, south to north, north to south, top to bottom, and bottom to top.

[0194] It should be noted that the first passage cost is not limited to the meteorological element of wind speed, but can also be extended to other environmental factors, such as temperature distribution, air pressure changes, or visibility conditions. As long as these factors can be quantified and have an impact on the direction of passage, they can be considered as part of the passage cost. This application does not limit this.

[0195] Taking temperature distribution as an example, a temperature cost model is set up, which adjusts the passage cost according to the temperature. For example, when the temperature is within the airworthiness range (such as between 0°C and 30°C), the cost value is lower; when the temperature exceeds the airworthiness range, whether it is too hot or too cold, the cost value will increase.

[0196] In one exemplary embodiment, taking the application scenario of UAV route planning as an example:

[0197] S1, after determining the scene grid parameters, construct a cost calculation model using wind speed values. For example, toll cost = wind speed weight value. The current wind speed parameter plus the preset cost parameter are used to calculate the passage weight in the six directions of the grid, which is the first passage cost.

[0198] S2. For travel in the east-to-west direction, the component travel cost in the east-to-west direction is determined based on the component wind speed parameter in the east-to-west direction, and this cost value is set as the edge weight of the target directed edge in the east-to-west direction. Similarly, for travel in the other five directions, the component travel cost in each direction is also set as the edge weight of the directed edge in the corresponding direction.

[0199] This application's embodiments employ a strategy of directly quantifying wind speed components into travel costs, achieving the technical effect of dynamically adjusting route planning costs. This results in refined control of flight routes, improved flight safety, and increased efficiency. In practical implementation, the edge weights of directed edges are dynamically adjusted based on real-time meteorological data to ensure that route planning always considers the latest environmental factors, thereby optimizing flight paths, reducing unnecessary energy consumption and time waste, and enhancing the aircraft's ability to cope with complex weather conditions.

[0200] As an optional approach, the above-mentioned generation of a navigation path based on a grid-directed network includes: generating travel cost data for each node in the grid-directed network based on travel cost; performing a path search operation on the grid-directed network based on the travel cost data to determine at least two target nodes; and generating a navigation path based on the at least two target nodes.

[0201] It should be noted that the above at least two target nodes are the nodes corresponding to the grid cell where the starting coordinates of the aircraft are located and the nodes corresponding to the grid cell where the ending coordinates of the aircraft are located.

[0202] For example, taking meteorological data as wind field data, the passage cost data here refers to the total cost incurred by the aircraft due to the wind field influence when passing through grid cells in different directions, including but not limited to actual cost (first cost data) and heuristic cost (second cost data).

[0203] In one exemplary embodiment, taking the application scenario of UAV route planning as an example:

[0204] S1, Generate passage cost data for each node in the gridded directed network based on passage cost;

[0205] S2, treat each grid cell as a node, treat the six directions as directed edges between nodes, and determine at least one of the actual cost (first cost data) and heuristic cost (second cost data) for each node;

[0206] S3, merge the actual cost and the heuristic cost to determine the passage cost data corresponding to the node. Specifically, the merging here includes, but is not limited to, direct addition, weighted summation, etc., which are not limited in this application; or the actual cost can be directly determined as the passage cost data corresponding to the node; or the heuristic cost can be directly determined as the passage cost data corresponding to the node.

[0207] S4 executes the A-path planning algorithm, starting from the starting node and gradually expanding to each adjacent node until the ending node is found. During the expansion process, the passage cost data of each node is recorded, and the navigation path with the lowest total passage cost is selected based on the passage cost data.

[0208] By introducing travel cost data related to meteorological data through the embodiments of this application, and then determining the flight path based on the travel cost data, that is, optimizing the flight path using meteorological data, the technical effect of improving the accuracy and availability of the flight path is achieved.

[0209] As an optional approach, the above-mentioned generation of travel cost data for each node in a grid-directed network based on the travel cost of each node includes: determining a third node based on the starting node and the first current node, wherein the third node includes at least one of the first current node and historical nodes, where historical nodes represent nodes for which travel cost data has been determined between the starting node and the first current node, the starting node represents the node corresponding to the grid cell where the starting position of the aircraft is located, and the first current node is the node corresponding to any grid cell; determining a first Euclidean distance between each third node and the ending node, wherein the ending node represents the node corresponding to the grid cell where the ending position of the aircraft is located; performing a multiplication operation on the travel cost of each third node and its corresponding first Euclidean distance to obtain a first sub-cost parameter; and performing a summation operation on the first sub-cost parameter to obtain first cost data, wherein the travel cost data of the first current node includes the first cost data.

[0210] Optionally, in this embodiment, the aforementioned determination of the third node refers to a set of nodes dynamically determined during the path planning process, including but not limited to the first current node and nodes on the path from the starting node to the first current node whose passage cost data has been determined; the aforementioned passage cost refers to the passage cost corresponding to the six directions generated based on the real-time wind field data mapping; the aforementioned first Euclidean distance refers to the straight-line distance between the third node and the endpoint node.

[0211] It should be noted that the steps of selecting the first current node, updating the set of the third node, and calculating the passage cost data are highly flexible and diverse depending on the specific application scenario and changes in environmental data, and this application does not limit them.

[0212] For example, the first cost data can be represented as:

[0213] ;

[0214] Among them, G n d represents the actual cost of node N. iLet f(i) be the Euclidean distance from node i to its parent node, and f(i) be the travel cost of node i. Node i is a node whose travel cost data has been determined between node N and the corresponding node of the grid cell where the starting coordinates of the spacecraft are located. Considering that the travel cost may include component travel costs corresponding to multiple travel directions, the travel cost here may include, but is not limited to, the sum of the component travel costs corresponding to each travel direction of node i, or the component travel costs corresponding to the relative travel directions between node i and node N. For example, if node N is located south of node i, the travel cost component of node i from south to north will be used when calculating the cost; similarly, if node N is located east of node i, the travel cost component from east to west will be used; if node N is located southeast of node i, the sum of the component travel costs from east to west and from south to north will be used.

[0215] In one exemplary embodiment, the application scenario of urban logistics drone delivery is taken as an example:

[0216] S1, After the initial position of the UAV is determined, the grid cell at the current position is marked as the starting node;

[0217] S2, based on the A-path planning algorithm, dynamically calculates the travel cost data to the destination. During the calculation process, the set of third nodes corresponding to each grid cell is updated, including the current node's neighbor nodes and nodes on the historical path. For each third node, the first Euclidean distance between it and the destination is calculated, and combined with the dynamic cost, the first sub-cost parameter is generated.

[0218] S3, the first sub-cost parameter is summed to obtain the passage cost data of the first current node, thus completing the dynamic cost calculation of path planning.

[0219] As an optional approach, traffic cost data is generated based on the traffic costs of each node in the directed grid network. This includes: determining the second Euclidean distance between the second current node and the destination node, where the second current node is a node corresponding to any grid cell, and the destination node represents the node corresponding to the grid cell where the aircraft's destination position is located; determining the target cosine value based on the target traffic direction between the second current node and the destination node, where the target cosine value represents the cosine of the angle between the target traffic direction and the target direction, and the target direction is at least one of the east-west, north-south, and vertical directions; and performing a merging operation on the second Euclidean distance, the target cosine value, and the traffic cost of the second current node to obtain the second cost data, where the traffic cost data of the second current node includes the second cost data.

[0220] As an alternative, the east-west direction refers to the direction of travel from east to west or from west to east; the north-south direction refers to the direction of travel from south to north or from north to south; and the vertical direction refers to the direction of travel from top to bottom or from bottom to top.

[0221] As an optional approach, the above-mentioned merging operation on the second Euclidean distance, the target cosine value, and the travel cost of the second current node to obtain second cost data includes at least one of the following: determining the east-west cost parameter by multiplying the second Euclidean distance, the first cosine value, and the east-west travel cost, wherein the first cosine value represents the cosine of the angle between the target travel direction and the east-west direction, and the east-west travel cost represents the east-west component travel cost of the second current node; the second cost data is determined based on the east-west cost parameter; and merging the second Euclidean distance, the second cosine value, and the north-south travel cost... The product is determined as the north-south cost parameter, where the second cosine value represents the cosine of the angle between the target travel direction and the north-south direction, and the north-south travel cost represents the travel cost of the second current node in the north-south direction. The second cost data is determined based on the north-south cost parameter. The product of the second Euclidean distance, the third cosine value, and the vertical travel cost is determined as the vertical cost parameter, where the third cosine value represents the cosine of the angle between the target travel direction and the vertical direction, and the vertical travel cost represents the travel cost of the second current node in the vertical direction. The second cost data is determined based on the vertical cost parameter.

[0222] Optionally, the aforementioned east-west, north-south, and vertical directions refer to the travel directions from east to west, from west to east, from south to north, from north to south, and from bottom to top and from top to bottom. These directions cover the six basic travel directions of a grid-directed graph.

[0223] It should be noted that the target cosine value can be determined based on the angle between the target travel direction and the east-west, north-south, and vertical directions, calculated using a standard cosine function. This value is used to quantify the impact of the travel direction on travel costs. The east-west, north-south, and vertical travel costs correspond to the component travel costs of the second current node in the east-west, north-south, and vertical directions, respectively.

[0224] It should also be noted that the above merging operations include, but are not limited to, direct addition, weighted summation, etc., and this application does not limit them.

[0225] For example, the second cost data is represented as:

[0226] ;

[0227] Among them, H nLet be the heuristic cost of node N, D be the Euclidean distance from node N to the destination, and θ1, θ2, and θ3 be the angles between the direction from node N to the destination and the east-west, north-south, and vertical directions, respectively. F1, F2, and F3 are the travel costs of node N in the east-west, north-south, and vertical directions, respectively.

[0228] Furthermore, considering that the east-west direction can be from east to west or from west to east; similarly, the north-south direction can be from south to north or from north to south; and the vertical direction can be from top to bottom or from bottom to top, when the angle between the direction from the Nth node to the destination and the east-west direction is the same as the angle between the direction from the Nth node to the destination and the east-west travel direction, then F1 refers to the component travel cost of the Nth node in the east-west travel direction; similarly, when the angle between the direction from the Nth node to the destination and the north-south direction is the same as the angle between the direction from the Nth node to the destination and the south-north travel direction, then F2 refers to the component travel cost of the Nth node in the south-north travel direction. This application does not limit this.

[0229] In one exemplary embodiment, taking the application scenario of route planning as an example:

[0230] S1, determine the second Euclidean distance between the second current node and the end node;

[0231] S2, based on the travel direction of the second current node, calculate the cosine value of the target direction, which can be east-west, north-south, or vertical.

[0232] S3, based on the direction of travel, obtain the travel cost in the east-west, north-south, or perpendicular direction;

[0233] S4. Multiply the second Euclidean distance by the target cosine value and the passage cost to obtain the east-west cost parameter, north-south cost parameter, and vertical cost parameter;

[0234] S5, comprehensively analyze the second cost data, and determine the optimal travel path for the second current node.

[0235] Through the embodiments of this application, traffic cost data is determined based on at least one of the first cost data and the second cost data. Based on the traffic cost data, route planning optimization that integrates meteorological environmental factors and flight direction is achieved, thereby improving the flight efficiency and safety of UAVs.

[0236] As an optional approach, the above-mentioned division of the aircraft's travel area into grid cells includes: determining the aircraft's starting coordinates, ending coordinates, and travel area type based on the aircraft's position data; determining the grid level according to the travel area type; determining the travel envelope range according to the starting and ending coordinates; determining the altitude domain range according to the highest and lowest point coordinates within the travel envelope range; and using the grid level and altitude domain range to divide the aircraft's travel area into grid cells.

[0237] Optionally, in the embodiments of this application, the above-mentioned access area type refers to the geographical environment of the aircraft operation, including but not limited to urban areas, rural areas or complex terrain areas; grid level refers to the size and resolution of grid cells, which are used to adapt to the needs of different geographical environments and flight missions; altitude domain range refers to the vertical space range of the aircraft's passage, which is determined by the coordinates of the highest and lowest points within the passage envelope, and is used to limit the vertical flight space of the aircraft.

[0238] It should be noted that the determination of the passage envelope range can be adjusted according to the flight mission and safety requirements of the aircraft. For example, when performing express delivery missions in urban areas, the buffer parameters of the envelope range can be increased to avoid potential obstacles and high-risk areas; when performing surveying missions in rural areas, the grid level can be dynamically adjusted according to the terrain features to achieve more refined terrain coverage.

[0239] In one exemplary embodiment, taking the application scenario of urban express delivery as an example:

[0240] S1. Based on the starting coordinates (114.2°E, 39.7°N, 0m) and ending coordinates (116.0°E, 38.0°N, 300m) of the aircraft and combined with the city area type, the scene grid level is determined to be 23 (7.7m).

[0241] S2, based on the coordinates of the starting point and the ending point, the initial range connecting these two points is longitude from 114.2°E to 116.0°E, latitude from 38.0°N to 39.7°N, and altitude from 0m to 300m; on the basis of the initial range, a preset buffer range is added. The size of the buffer range can be set according to actual needs and application scenarios. Assuming that the preset buffer range is longitude ±0.2°, latitude ±0.15°, and altitude ±10m, the travel envelope range is obtained as follows: longitude [114.0°E, 116.2°E]; latitude [37.85°N, 39.85°N]; altitude [-10m, 310m].

[0242] S3. Determine the coordinates of the highest and lowest points within the passage envelope. Based on the altitude of the highest and lowest points, determine the range of the altitude domain. For example, if the highest altitude within the area connecting the starting and ending points is 2000 meters and the lowest altitude is 500 meters, then the determined range of the segmented altitude domain is from 500 meters to 2000 meters.

[0243] S4 uses the GeoSOT global discrete partitioning coding system and the determined grid level and height domain range to divide the urban area into grid cells.

[0244] Through the embodiments of this application, a grid cell division method based on the aircraft's operating environment and mission requirements is adopted, which achieves a more refined and dynamic airspace passage area division technology effect, thereby improving the accuracy and adaptability of aircraft route planning, as well as enhancing flight safety and efficiency.

[0245] As an alternative, before determining the passage cost of a grid cell based on meteorological data, the method further includes: identifying obstacle grid cells within each grid cell, wherein the aircraft cannot pass through the obstacle grid cells; and removing the obstacle grid cells from the grid cell to update the grid cell.

[0246] As an optional approach, the above method also includes at least one of the following: identifying grid cells in areas with obstacles as obstacle grid cells; identifying grid cells in areas where drones are restricted from flying as obstacle grid cells; identifying grid cells in areas with abnormal weather as obstacle grid cells.

[0247] Optionally, in the embodiments of this application, obstacle grid cells refer to grid cells that an aircraft cannot pass through due to terrain, buildings, controlled areas or abnormal weather conditions, including but not limited to hills, tall buildings, no-fly zones or areas with strong winds.

[0248] It should be noted that in practical applications, the identification of obstacle grid cells may be based on various types of data sources, such as high-resolution topographic maps, urban planning maps, real-time airspace control information, or meteorological early warning systems. This application does not limit this.

[0249] For example, the process of identifying obstacle grid cells can be further refined, including but not limited to identifying non-flyable grids by analyzing a terrain database; eliminating non-navigable spaces by using building information; determining flight restrictions based on controlled area regulations; and identifying areas affected by severe weather using meteorological data, so as to ensure that the final directed grid map reflects both the dynamic effects of the wind field and fully considers physical obstacles.

[0250] Through the embodiments of this application, the obstacle grid cell identification and removal mechanism is adopted to reduce flight risks and improve the reliability of route planning, thereby achieving the goal of improving the operating efficiency and safety level of UAVs in complex environments.

[0251] As an optional approach, the above method further includes at least one of the following: determining the passage cost of a grid cell based on meteorological data at the starting node, and constructing a directed grid network according to the passage cost, wherein the starting node represents the node corresponding to the grid cell where the aircraft's starting position is located; generating a flight path based on the directed grid network; responding to meteorological data updates, determining the passage cost of a grid cell based on meteorological data at the updated node, and constructing a directed grid network according to the passage cost, wherein the updated node represents the node corresponding to the current grid cell where the aircraft is located; and updating the flight path based on the directed grid network.

[0252] It should be noted that meteorological data updates can be periodic or non-periodic. For example, the system will automatically trigger an update mechanism when a significant change in wind field conditions is detected. Furthermore, the update nodes are not limited to the grid cells corresponding to the aircraft's current position, but can be extended to multiple grid cells along the aircraft's future path to predict and adjust flight strategies in advance, enhancing the foresight of flight planning.

[0253] For example, in this embodiment of the application, meteorological data, specifically wind speed and wind direction, are associated with the six faces (east-west, north-south, and vertical up-down) of the grid cell to construct a grid directed network diagram that considers the influence of the wind field. The magnitude of the wind speed directly affects the cost value, thereby realizing dynamic cost adjustment.

[0254] In one exemplary embodiment, taking the application scenario of real-time flight path planning for unmanned aerial vehicles as an example:

[0255] S1. Before the drone takes off, based on the current meteorological data, calculate the travel cost in each direction of the grid cell where the starting node is located, and construct the initial grid directed network graph.

[0256] S2 uses the A-path planning algorithm, combined with travel cost as a weight value, to plan an optimal navigation path from the starting node to the destination.

[0257] S3, during flight, whenever the drone enters a new grid cell or receives an update in meteorological data, the system immediately recalculates the passage cost of the corresponding grid cell based on the latest wind field conditions;

[0258] S4: The system automatically adjusts the directed grid network and optimizes the existing flight path based on the updated network graph to cope with the impact of wind field changes, while ensuring flight safety and efficiency.

[0259] Through the embodiments of this application, the above-mentioned flight path can be generated at the grid cell corresponding to different nodes of the aircraft, ensuring that the flight path planning is optimal regardless of which grid cell the aircraft is in, thereby achieving the purpose of intelligent and refined management.

[0260] In an exemplary embodiment, the above-described method for generating flight paths can be applied to the fields of geographic information and airspace control. It enables the construction of directed graphs and route planning using global grid meshes and environmental data. By binding disordered airspace grid cells with the passage costs in six directions, a directed airspace grid is constructed, which can then provide powerful services and support for application scenarios such as airspace route planning and low-altitude "traffic lights".

[0261] Existing flight path generation methods do not consider grid orientation and mostly rely solely on obstacles as primary considerations. However, weather conditions are equally crucial during UAV flight, with wind, rainfall, and humidity being key factors affecting flight safety and efficiency. Failure to adequately consider these weather factors renders flight plans unscientific and unreliable. Furthermore, dynamic adaptability is poor, as dynamic design primarily relies on obstacle changes. Obstacles themselves rarely change frequently, and even when they do, they are difficult to detect in a timely manner. This hinders flexible adjustments to flight plans based on actual conditions and prevents effective responses to complex and ever-changing flight environments. Finally, the cost calculation method is simplistic, using only the shortest distance or time as the cost benchmark, completely ignoring the impact of environmental factors. This singular cost calculation method fails to comprehensively and accurately reflect the actual costs during flight, hindering flight path generation.

[0262] Based on this, in this embodiment of the application, a grid-directed network is designed, a flight direction mechanism is introduced, and it is deeply integrated with meteorological data. The travel cost weight is adjusted according to the dynamic attributes of the wind field, and then combined with a route planning algorithm to generate a real-time flight path, such as... Figure 9 As shown, including but not limited to:

[0263] S1. Determine the scene grid parameters: Based on the UAV's planned start and end points and the type of administrative division it occupies (the aforementioned travel area type), determine the grid level, travel envelope, and altitude domain. The grid level is preset according to the actual application scenario requirements. In urban areas, a 26-level (1m) grid can be selected, and in rural areas, a 23-level (7.7m) grid can be selected. The travel envelope is determined by connecting the starting points of the flight path plan, and certain buffer parameters can be dynamically adjusted according to application needs to form the scene range. The altitude domain is determined by the highest and lowest points within the travel envelope. Then, according to the corresponding grid level and altitude domain, the travel area is divided into grid units using the GeoSOT partitioning method.

[0264] S2, Passable Area Identification: Obtain grid cells corresponding to passable areas by eliminating obstacles, drone restricted flight areas, and areas with abnormal weather; Obstacles: refer to static objects existing in space, including terrain, buildings, etc.; Drone restricted flight areas; Areas with abnormal weather: refer to the "General Technical Standard for Chinese Unmanned Aerial Vehicles", this area refers to areas with rainfall and areas with excessively high wind speeds (above 7.9 m / s).

[0265] S3, GeoSOT uses a planar meshing method based on whole longitude and whole latitude, meaning the two bottom edges of the mesh correspond exactly to the east-west and north-south directions, which corresponds to the wind field data format. This allows the three velocity dimensions (U, V, W components) of the wind field data to be mapped onto the six faces of the grid. Specifically: the U component, east-west, corresponds to the east face E and west face W of the grid, representing the horizontal velocity component of the wind moving from east to west or from west to east; the V component, north-south, corresponds to the south face S and north face N of the grid, representing the horizontal velocity component of the wind moving from south to north or from north to south; and the W component, vertical, corresponds to the top U and bottom D of the grid, representing the vertical velocity component of the wind moving from top to bottom or from bottom to top.

[0266] Through the mapping relationships in S3, complex three-dimensional wind field data can be simplified into a six-face field representation of a grid, thus providing a foundation for subsequent cost value mapping and path planning.

[0267] S4 maps wind speed values ​​to cost values ​​from 1 to 9. The higher the forward wind speed, the lower the cost; conversely, the higher the reverse wind speed, the higher the cost. The cost of passage under reverse wind speed > the cost of passage under no wind conditions > the cost of passage under forward wind speed. Assuming the cost of passage is 5 when the wind speed is 0, the wind speed cost model is: Passage Cost = -0.51 Wind speed +5.

[0268] S5 constructs a grid-directed network using U, V, W components and the passage cost in the six directions of the grid.

[0269] S6 employs the A-path planning algorithm combined with the travel cost weights of the six directions of the grid to plan the navigation path. The A-path planning algorithm, through a combination of heuristic functions and actual costs, can efficiently find the optimal path in complex environments and is suitable for grid or graph data. Actual cost refers to the actual path cost from the starting point to the current node N (the first cost data mentioned above), and the heuristic function is used to determine the estimated cost from the current node N to the target destination (the second cost data mentioned above).

[0270] In yet another exemplary embodiment, the steps include, but are not limited to, the following:

[0271] Step 1: Input the coordinates of the starting point (114.2°E, 39.7°N, 0m) and ending point (116.0°E, 38.0°N, 0m) of the route planning; the passage envelope ranges from longitude 114.0°E to 116.4°E, latitude 37.6°N to 40.0°N, altitude 0m to 300m, and the grid level is 23 (7.7m). Then, the passage area is divided to obtain grid cells.

[0272] Step 2: Obtain simulated GRIB2 meteorological data for the corresponding scene range of the passage area. Select three parameters from the GRIB2 data: UGRD, VGRD, and VVEL. Specifically, UGRD refers to the wind speed component in the U direction, i.e., the wind speed in the east-west direction. UGRD usually represents the horizontal velocity component of the wind from west to east, with positive values ​​indicating easterly winds and negative values ​​indicating westerly winds; VGRD refers to the wind speed component in the V direction, i.e., the wind speed in the north-south direction. VGRD usually represents the horizontal velocity component of the wind from south to north, with positive values ​​indicating northerly winds and negative values ​​indicating southerly winds; VVEL refers to the vertical velocity component, i.e., the rising and falling wind speeds. VVEL usually represents the vertical speed of air movement, with positive values ​​indicating rising air currents and negative values ​​indicating falling air currents.

[0273] Step 3: Calculate the latitude and longitude of the data coordinate points based on the origin coordinates (Lo1, La1) and horizontal spans Dx and Dy in the GRIB2 header file. The origin coordinates refer to the latitude and longitude coordinates of the lower left corner (i.e., the southernmost and westernmost point) of the data coverage area in the GRIB2 header file. The horizontal spans Dx and Dy represent the interval between two adjacent data points along the longitude and latitude directions, respectively, usually in degrees. The coordinate point height is consistent with the height of the selected data location; in this example, it is 0m and 300m, totaling 17,640 wind field points, divided into two layers of 8,820 points each.

[0274] Step 4: Mark the obstacle area, controlled area, and meteorological anomaly area data, and mark the corresponding grid as impassable. Map the remaining data values ​​to cost values ​​according to the mapping rules. Assuming the wind speed data from south to north is 4.8, according to Formula 1, the cost value from south to north is 2, and the cost value from north to south is 7. The calculation methods for the east-west and vertical directions remain consistent.

[0275] Step 5: Adjust the actual cost and heuristic cost calculation methods of the A-path planning algorithm, and iteratively solve for the optimal path. Actual cost calculation: Calculate the cumulative value of the Euclidean distance and the cost in the movement direction for each node, where the cost in the movement direction is obtained from the six-direction cost encoding. Heuristic cost calculation: Calculate the distance from the current node to the destination and the angles between the east-west, north-south, and vertical directions, and obtain the heuristic cost of the current node according to the calculation.

[0276] In this embodiment, the three velocity components (U, V, W) of the wind field are mapped to the six faces of a GeoSOT grid cell. This mapping effectively simplifies and quantifies complex three-dimensional wind field data, providing a foundation for subsequent cost value mapping and path planning. Furthermore, wind speed values ​​are mapped to cost values ​​ranging from 1 to 9. This mapping quantifies the impact of wind field data on navigation costs into specific cost values, thus providing a more accurate basis for cost calculation in path planning. Replacing the Euclidean distance cost of the traditional A-path planning algorithm with dynamic costs allows for adaptation to complex and changing meteorological environments, ensuring that route planning is always in an optimal state. This reconstructs the cost dependency mechanism of the A-path planning algorithm, improving the adaptability and accuracy of route planning.

[0277] It is understood that in the specific embodiments of this application, data such as user information are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0278] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0279] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0280] Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / random access memory (RAM), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0281] According to another aspect of the embodiments of this application, a navigation path generation apparatus for implementing the above-described navigation path generation method is also provided. This navigation path generation apparatus can be used to implement the navigation path generation method provided in the above embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0282] Figure 10 This is a structural block diagram of an optional navigation path generation apparatus according to an embodiment of this application, such as... Figure 10 As shown, the apparatus for generating the navigation path includes:

[0283] The partitioning module 1002 is used to partition the passage area of ​​the aircraft to obtain grid cells;

[0284] The determination module 1004 is used to determine the passage cost of the grid cell based on meteorological data, and to construct a directed grid network according to the passage cost. In the directed grid network, the nodes represent grid cells, the directed edges of the nodes are used to indicate the passage direction, and the passage cost is used to determine the edge weight of the directed edges.

[0285] Generation module 1006 is used to generate the flight path of the aircraft based on the grid directed network.

[0286] As an alternative, the device is used to determine the passage cost of a grid cell based on meteorological data in the following manner: determining the current wind speed parameter based on the height of the grid cell and the meteorological data, wherein the meteorological data includes at least one wind speed parameter corresponding to the height; determining the passage cost based on a preset cost parameter and the current wind speed parameter, wherein the preset cost parameter is used to indicate the passage cost in a windless state.

[0287] As an optional approach, the device is used to determine the current wind speed parameter based on the height of the grid cell and meteorological data in the following manner, including at least one of the following: if the meteorological data includes a target wind speed parameter, the target wind speed parameter is determined as the current wind speed parameter, wherein the target wind speed parameter represents the wind speed parameter corresponding to the height of the grid cell; if the meteorological data does not include a target wind speed parameter, an interpolation operation is performed on the meteorological data to determine the current wind speed parameter, wherein the target wind speed parameter represents the wind speed parameter corresponding to the height of the grid cell.

[0288] As an optional approach, the current wind speed parameters include at least one of the horizontal component wind speed parameters and the vertical component wind speed parameters. The horizontal component wind speed parameters include at least one of the following: east-to-west, west-to-east, south-to-north, and north-to-south. The vertical component wind speed parameters include at least one of the following: top-down and bottom-up. The passage cost includes at least one of the horizontal component passage cost and the vertical component passage cost. The horizontal component passage cost is determined based on the horizontal component wind speed parameters, and the vertical component passage cost is determined based on the vertical component wind speed parameters.

[0289] As an optional approach, the device is used to determine the passage cost based on preset cost parameters and current wind speed parameters in the following manner: determining the target product of a preset wind speed weight value and the current wind speed parameter; and determining the sum of the target product and the preset cost parameter as the passage cost.

[0290] As an optional scheme, the device is also used for at least one of the following: determining a first product of a preset wind speed weight value and a first component wind speed parameter, and determining the sum of the first product and a preset cost parameter as the first component travel cost, wherein the first component wind speed parameter represents the component wind speed parameter from east to west in the current wind speed parameters, and the first component travel cost represents the component travel cost from east to west in the travel cost; determining a second product of a preset wind speed weight value and a second component wind speed parameter, and determining the sum of the second product and a preset cost parameter as the second component travel cost, wherein the second component wind speed parameter represents the component wind speed parameter from west to east in the current wind speed parameters, and the second component travel cost represents the component travel cost from east to west in the travel cost; The west-to-east component travel cost; determine the preset wind speed weight value and the third product of the third component wind speed parameter, and determine the third component travel cost as the sum of the third product and the preset cost parameter, where the third component wind speed parameter represents the south-to-north component wind speed parameter in the current wind speed parameters, and the third component travel cost represents the south-to-north component travel cost in the travel cost; determine the preset wind speed weight value and the fourth product of the fourth component wind speed parameter, and determine the fourth component travel cost as the sum of the fourth product and the preset cost parameter, where the fourth component wind speed parameter represents the north-to-south component wind speed parameter in the current wind speed parameters, and the fourth component travel cost represents the north-to-south component travel cost in the travel cost.

[0291] As an optional solution, the device is also used for at least one of the following: determining a preset wind speed weight value and a fifth product of a fifth component wind speed parameter, and determining the sum of the fifth product and a preset cost parameter as the fifth component travel cost, wherein the fifth component wind speed parameter represents the top-down component wind speed parameter in the current wind speed parameters, and the fifth component travel cost represents the top-down component travel cost in the travel cost; determining a preset wind speed weight value and a sixth product of a sixth component wind speed parameter, and determining the sum of the sixth product and a preset cost parameter as the sixth component travel cost, wherein the sixth component wind speed parameter represents the bottom-up component wind speed parameter in the current wind speed parameters, and the sixth component travel cost represents the bottom-up component travel cost in the travel cost.

[0292] As an optional approach, the device is used to construct a grid-directed network based on passage cost in the following manner: determining the target passage cost of a first grid cell based on meteorological data, wherein the first grid cell is any grid cell; determining a second grid cell adjacent to the first grid cell; establishing a target directed edge based on a first passage direction between the first and second grid cells, and setting the edge weight of the target directed edge based on the target passage cost, wherein the target directed edge starts from a first node and connects to a second node, where the first node represents the first grid cell and the second node represents the second grid cell; and constructing the grid-directed network based on the first node, the second node, and the target directed edge.

[0293] As an optional approach, the device is used to set the edge weight of the target directed edge based on the first travel cost in the following manner, including at least one of the following: when the first travel direction is from east to west, setting the east-to-west component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from west to east, setting the west-to-east component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from south to north, setting the south-to-north component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from north to south, setting the north-to-south component of the first travel cost as the edge weight of the target directed edge.

[0294] As an optional approach, the device is also used to: when the first travel direction is from top to bottom, set the travel cost of the top-down component of the first travel cost as the edge weight of the target directed edge; when the first travel direction is from bottom to top, set the travel cost of the bottom-up component of the first travel cost as the edge weight of the target directed edge.

[0295] As an alternative approach, the device is used to generate a navigation path based on a grid-directed network in the following manner: generating travel cost data for each node in the grid-directed network based on travel cost; performing a path search operation on the grid-directed network based on the travel cost data to determine at least two target nodes; and generating a navigation path based on the at least two target nodes.

[0296] As an optional approach, the device generates passage cost data for each node in a grid-directed network based on the passage cost corresponding to each node in the network as follows: A third node is determined based on the starting node and the first current node, wherein the third node includes at least one of the first current node and historical nodes, where historical nodes represent nodes for which passage cost data has been determined between the starting node and the first current node, the starting node represents the node corresponding to the grid cell where the starting position of the aircraft is located, and the first current node is the node corresponding to any grid cell; a first Euclidean distance is determined between each third node and the ending node, where the ending node represents the node corresponding to the grid cell where the ending position of the aircraft is located; a multiplication operation is performed on the passage cost of each third node and its corresponding first Euclidean distance to obtain a first sub-cost parameter; a summation operation is performed on the first sub-cost parameter to obtain first cost data, wherein the passage cost data of the first current node includes the first cost data.

[0297] As an optional approach, the device generates respective travel cost data based on the travel costs corresponding to each node in the grid-directed network in the following manner: determining a second Euclidean distance between a second current node and a destination node, wherein the second current node is a node corresponding to any grid cell, and the destination node represents the node corresponding to the grid cell where the destination position of the aircraft is located; determining a target cosine value based on the target travel direction between the second current node and the destination node, wherein the target cosine value represents the cosine value of the angle between the target travel direction and the target direction, and the target direction is at least one of the east-west direction, the north-south direction, and the vertical direction; and performing a merging operation on the second Euclidean distance, the target cosine value, and the travel cost of the second current node to obtain second cost data, wherein the travel cost data of the second current node includes the second cost data.

[0298] As an alternative, the east-west direction is the direction of travel from east to west or from west to east; the north-south direction is the direction of travel from south to north or from north to south; and the vertical direction is the direction of travel from top to bottom or from bottom to top.

[0299] As an optional approach, the device is used to perform a merging operation on the second Euclidean distance, the target cosine value, and the travel cost of the second current node to obtain second cost data, including at least one of the following: determining the east-west cost parameter by multiplying the second Euclidean distance, the first cosine value, and the east-west travel cost, wherein the first cosine value represents the cosine of the angle between the target travel direction and the east-west direction, the east-west travel cost represents the east-west component travel cost of the second current node, and the second cost data is determined based on the east-west cost parameter; merging the second Euclidean distance, the second cosine value, and the north-south travel cost... The product of travel costs is used to determine the north-south cost parameter, where the second cosine value represents the cosine of the angle between the target travel direction and the north-south direction, and the north-south travel cost represents the travel cost of the second current node in the north-south direction. The second cost data is determined based on the north-south cost parameter. The product of the second Euclidean distance, the third cosine value, and the vertical travel cost is used to determine the vertical cost parameter, where the third cosine value represents the cosine of the angle between the target travel direction and the vertical direction, and the vertical travel cost represents the travel cost of the second current node in the vertical direction. The second cost data is determined based on the vertical cost parameter.

[0300] As an optional approach, the device is used to divide the passage area of ​​an aircraft into grid cells by: determining the starting coordinates, ending coordinates, and passage area type of the aircraft based on the aircraft's position data; determining the grid level according to the passage area type; determining the passage envelope range according to the starting and ending coordinates; determining the altitude domain range according to the highest and lowest point coordinates within the passage envelope; and dividing the passage area of ​​the aircraft into grid cells using the grid level and altitude domain range.

[0301] As an alternative, the device is also used to: identify obstacle grid cells within each grid cell, wherein the aircraft cannot pass through the obstacle grid cells, before determining the passage cost of the grid cell based on meteorological data; and remove the obstacle grid cells from the grid cell to update the grid cell.

[0302] As an optional solution, the device is also used to: identify grid cells in areas with obstacles as obstacle grid cells; identify grid cells in areas with restricted drone flights as obstacle grid cells; identify grid cells in areas with abnormal weather as obstacle grid cells.

[0303] As an optional approach, the device is also used for at least one of the following: determining the passage cost of a grid cell based on meteorological data at the starting node, and constructing a directed grid network according to the passage cost, wherein the starting node represents the node corresponding to the grid cell where the starting position of the aircraft is located; generating a flight path based on the directed grid network; responding to meteorological data updates, determining the passage cost of a grid cell based on meteorological data at the updated node, and constructing a directed grid network according to the passage cost, wherein the updated node represents the node corresponding to the current grid cell where the aircraft is located; and updating the flight path based on the directed grid network.

[0304] Regarding the apparatus in the above embodiments, the terms "module" or "unit" refer to a computer program or part of a computer program with a predetermined function, which works together with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit. The specific manner in which each module performs its operations has been described in detail in the embodiments relating to the method, and will not be elaborated upon here.

[0305] According to another aspect of the embodiments of this application, an electronic device is provided.

[0306] The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor is configured to perform the steps in any of the above method embodiments via the computer program. In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor. Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0307] According to one aspect of this application, a computer program product is also provided, which includes a computer program.

[0308] The computer program product includes a computer program / instructions containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via communication section 1109, and / or installed from removable media 1111. When the computer program is executed by central processing unit 1101, it performs various functions provided in the embodiments of this application. The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0309] Figure 11 A schematic block diagram of a computer system architecture for implementing embodiments of the present application is shown. Figure 11 As shown, the computer system 1100 includes a Central Processing Unit (CPU) 1101, which can perform various appropriate actions and processes based on programs stored in ROM 1102 or programs loaded into RAM 1103 from storage section 1108. Random access memory 1103 also stores various programs and data required for system operation. The CPU 1101, ROM 1102, and RAM 1103 are interconnected via bus 1104. Input / output (I / O) interface 1105 is also connected to bus 1104.

[0310] The following components are connected to I / O interface 1105: an input section 1106 including a keyboard, mouse, etc.; an output section 1107 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1108 including a hard disk, etc.; and a communication section 1109 including a network interface card such as a local area network card, modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to I / O interface 1105 as needed. Removable media 1111, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1110 as needed so that computer programs read from them can be installed into storage section 1108 as needed.

[0311] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0312] Specifically, according to embodiments of this application, the processes described in the various method flowcharts can be implemented as computer programs / instructions. For example, embodiments of this application include a computer program / instruction comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication portion, and / or installed from a removable medium. When the computer program is executed by a central processing unit, it performs various functions defined in the system of this application. In such embodiments, the computer program / instruction can be downloaded and installed from a network via a communication portion, and / or installed from a removable medium. When the computer program / instruction is executed by a central processing unit, it performs the aforementioned method for generating navigation paths.

[0313] According to one aspect of this application, a computer-readable storage medium is also provided.

[0314] The processor of the aforementioned electronic device can read the computer instructions from a computer-readable storage medium, and the processor executes the computer instructions, causing the electronic device to perform the navigation path generation method provided in the various alternative implementations of the navigation path generation aspect.

[0315] Optionally, in this embodiment, the computer-readable storage medium described above may be configured to store methods for performing the embodiments of this application.

[0316] Optionally, in this embodiment, those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0317] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0318] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause one or more electronic devices to execute all or part of the steps of the methods described in the various embodiments of this application.

[0319] In the several embodiments provided in this application, it should be understood that the disclosed application can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0320] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0321] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0322] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for generating a navigation path, characterized in that, include: The passage area of ​​the aircraft is divided into grid cells; The passage cost of the grid cell is determined based on meteorological data, and a directed grid network is constructed according to the passage cost. The nodes in the directed grid network represent the grid cells, the directed edges of the nodes are used to indicate the passage direction, and the passage cost is used to determine the edge weight of the directed edges. Based on the passage cost, generate passage cost data for each node in the grid-directed network; perform a path search operation on the grid-directed network based on the passage cost data to determine at least two target nodes; generate the navigation path based on the at least two target nodes; The step of generating passage cost data for each node in the directed grid network based on the passage cost corresponding to each node includes: determining a third node based on a starting node and a first current node, wherein the third node includes at least one of the first current node and historical nodes, the historical node represents a node between the starting node and the first current node whose passage cost data has been determined, the starting node represents the node corresponding to the grid cell where the starting position of the aircraft is located, and the first current node is a node corresponding to any grid cell; determining a first Euclidean distance between each third node and an end node, wherein the end node represents the node corresponding to the grid cell where the end position of the aircraft is located; performing a multiplication operation on the passage cost of each third node and its corresponding first Euclidean distance to obtain a first sub-cost parameter; performing a summation operation on the first sub-cost parameter to obtain first cost data, wherein the passage cost data of the first current node includes the first cost data.

2. The method according to claim 1, characterized in that, The determination of the passage cost of the grid cell based on meteorological data includes: The current wind speed parameter is determined based on the height of the grid cell and the meteorological data, wherein the meteorological data includes at least one wind speed parameter corresponding to the height; The passage cost is determined based on preset cost parameters and the current wind speed parameters, wherein the preset cost parameters are used to indicate the passage cost in a windless state.

3. The method according to claim 2, characterized in that, Determining the current wind speed parameter based on the height of the grid cell and the meteorological data includes at least one of the following: When the meteorological data includes a target wind speed parameter, the target wind speed parameter is determined as the current wind speed parameter, wherein the target wind speed parameter represents the wind speed parameter corresponding to the height of the grid cell; If the meteorological data does not include the target wind speed parameter, an interpolation operation is performed on the meteorological data to determine the current wind speed parameter, wherein the target wind speed parameter represents the wind speed parameter corresponding to the height of the grid cell.

4. The method according to claim 2, characterized in that, The current wind speed parameter includes at least one of the horizontal component wind speed parameter and the vertical component wind speed parameter, wherein the horizontal component includes at least one of east-to-west, west-to-east, south-to-north, and north-to-south, and the vertical component includes at least one of top-to-bottom and bottom-to-up. The passage cost includes at least one of the horizontal component passage cost and the vertical component passage cost, wherein the horizontal component passage cost is determined based on the horizontal component wind speed parameter, and the vertical component passage cost is determined based on the vertical component wind speed parameter.

5. The method according to claim 2, characterized in that, Determining the passage cost based on preset cost parameters and the current wind speed parameters includes: Determine the target product of the preset wind speed weight value and the current wind speed parameter; The sum of the target product and the preset cost parameter is determined as the toll cost.

6. The method according to claim 5, characterized in that, The method further includes at least one of the following: The first product of the preset wind speed weight value and the first component wind speed parameter is determined, and the sum of the first product and the preset cost parameter is determined as the first component travel cost, wherein the first component wind speed parameter represents the component wind speed parameter from east to west in the current wind speed parameter, and the first component travel cost represents the component travel cost from east to west in the travel cost; The second product of the preset wind speed weight value and the second component wind speed parameter is determined, and the sum of the second product and the preset cost parameter is determined as the second component travel cost, wherein the second component wind speed parameter represents the component wind speed parameter from west to east in the current wind speed parameter, and the second component travel cost represents the component travel cost from west to east in the travel cost; The third product of the preset wind speed weight value and the third component wind speed parameter is determined, and the sum of the third product and the preset cost parameter is determined as the third component travel cost. The third component wind speed parameter represents the component wind speed parameter from south to north in the current wind speed parameter, and the third component travel cost represents the component travel cost from south to north in the travel cost. The fourth product of the preset wind speed weight value and the fourth component wind speed parameter is determined, and the sum of the fourth product and the preset cost parameter is determined as the fourth component travel cost. The fourth component wind speed parameter represents the component wind speed parameter from north to south in the current wind speed parameter, and the fourth component travel cost represents the component travel cost from north to south in the travel cost.

7. The method according to claim 5, characterized in that, The method further includes at least one of the following: The fifth product of the preset wind speed weight value and the fifth component wind speed parameter is determined, and the sum of the fifth product and the preset cost parameter is determined as the fifth component travel cost. The fifth component wind speed parameter represents the top-down component wind speed parameter in the current wind speed parameter, and the fifth component travel cost represents the top-down component travel cost in the travel cost. The sixth product of the preset wind speed weight value and the sixth component wind speed parameter is determined, and the sum of the sixth product and the preset cost parameter is determined as the sixth component travel cost. The sixth component wind speed parameter represents the bottom-up component wind speed parameter in the current wind speed parameter, and the sixth component travel cost represents the bottom-up component travel cost in the travel cost.

8. The method according to claim 1, characterized in that, The construction of the grid-directed network according to the aforementioned passage cost includes: The target passage cost of the first grid cell is determined based on the meteorological data, wherein the first grid cell is any of the grid cells. Determine the second grid cell adjacent to the first grid cell; A target directed edge is established based on the first travel direction between the first grid cell and the second grid cell, and the edge weight of the target directed edge is set according to the target travel cost. The target directed edge starts from the first node and connects to the second node, where the first node represents the first grid cell and the second node represents the second grid cell. The grid-directed network is constructed based on the first node, the second node, and the target directed edge.

9. The method according to claim 8, characterized in that, Setting the edge weight of the target directed edge based on the target passage cost includes at least one of the following: When the first travel direction is from east to west, the east-to-west component of the target travel cost is set as the edge weight of the target directed edge. When the first travel direction is from west to east, the travel cost of the west-to-east component of the target travel cost is set as the edge weight of the target directed edge. When the first travel direction is from south to north, the travel cost of the south-to-north component of the target travel cost is set as the edge weight of the target directed edge. When the first travel direction is from north to south, the travel cost of the north-to-south component of the target travel cost is set as the edge weight of the target directed edge.

10. The method according to claim 8, characterized in that, The method further includes at least one of the following: When the first travel direction is from top to bottom, the travel cost of the top-down component of the target travel cost is set as the edge weight of the target directed edge. When the first travel direction is from bottom to top, the travel cost of the bottom-up component of the target travel cost is set as the edge weight of the target directed edge.

11. The method according to claim 1, characterized in that, The process of generating passage cost data for each node in the grid-directed network based on the passage cost corresponding to each node includes: Determine the second Euclidean distance between the second current node and the endpoint node, wherein the second current node is a node corresponding to any of the grid cells, and the endpoint node represents the node corresponding to the grid cell where the endpoint position of the spacecraft is located; The target cosine value is determined based on the target travel direction between the second current node and the destination node, wherein the target cosine value represents the cosine of the angle between the target travel direction and the target direction, and the target direction is at least one of the east-west direction, the north-south direction, and the vertical direction; A merging operation is performed on the second Euclidean distance, the target cosine value, and the passage cost of the second current node to obtain second cost data, wherein the passage cost data of the second current node includes the second cost data.

12. The method according to claim 11, characterized in that, The east-west direction refers to the direction of travel from east to west or from west to east; the north-south direction refers to the direction of travel from south to north or from north to south; and the vertical direction refers to the direction of travel from top to bottom or from bottom to top.

13. The method according to claim 11, characterized in that, The step of performing a merging operation on the second Euclidean distance, the target cosine value, and the passage cost of the second current node to obtain second cost data includes at least one of the following: The product of the second Euclidean distance, the first cosine value, and the east-west travel cost is determined as the east-west cost parameter, wherein the first cosine value represents the cosine of the angle between the target travel direction and the east-west direction, the east-west travel cost represents the component travel cost of the second current node in the east-west direction, and the second cost data is determined based on the east-west cost parameter; The product of the second Euclidean distance, the second cosine value, and the north-south travel cost is determined as the north-south cost parameter, wherein the second cosine value represents the cosine of the angle between the target travel direction and the north-south direction, the north-south travel cost represents the component travel cost of the second current node in the north-south direction, and the second cost data is determined based on the north-south cost parameter; The product of the second Euclidean distance, the third cosine value, and the vertical travel cost is determined as the vertical cost parameter, wherein the third cosine value represents the cosine of the angle between the target travel direction and the vertical direction, the vertical travel cost represents the component travel cost of the second current node in the vertical direction, and the second cost data is determined based on the vertical cost parameter.

14. The method according to claim 1, characterized in that, The division of the aircraft's passage area into grid cells includes: The origin coordinates, destination coordinates, and passage area type of the aircraft are determined based on the aircraft's position data. The grid level is determined based on the type of the passage area; The passage envelope range is determined based on the starting point coordinates and the ending point coordinates; The height domain range is determined based on the coordinates of the highest and lowest points within the passage envelope; The passage area of ​​the aircraft is divided using the grid hierarchy and the altitude domain range to obtain the grid cells.

15. The method according to claim 1, characterized in that, Before determining the passage cost of the grid cell based on meteorological data, the method further includes: Identify obstacle grid cells within each of the grid cells, wherein the aircraft cannot pass through the obstacle grid cells; Remove obstacle grid cells from the grid cells to update the grid cells.

16. The method according to claim 15, characterized in that, The method further includes at least one of the following: The grid cell containing the obstacle is defined as the obstacle grid cell; The grid cell in the area where drones are restricted from flying is identified as the obstacle grid cell; The grid cells in areas with meteorological anomalies are identified as the obstacle grid cells.

17. The method according to claim 1, characterized in that, The method further includes at least one of the following: At the starting node, the travel cost of the grid cell is determined based on the meteorological data, and the directed grid network is constructed according to the travel cost. The starting node represents the node corresponding to the grid cell where the starting position of the aircraft is located. A flight path is generated based on the directed grid network. In response to the meteorological data update, the update node determines the passage cost of the grid cell based on the meteorological data, and constructs the grid directed network according to the passage cost, wherein the update node represents the node corresponding to the current grid cell where the aircraft is located; and updates the flight path based on the grid directed network.

18. A navigation path generation device, characterized in that, include: The partitioning module is used to divide the spacecraft's passage area into grid cells; The determination module is used to determine the passage cost of the grid cell based on meteorological data, and construct a directed grid network according to the passage cost. The nodes in the directed grid network represent the grid cell, the directed edges of the nodes are used to indicate the passage direction, and the passage cost is used to determine the edge weight of the directed edges. The generation module is used to generate the flight path of the aircraft based on the grid-directed network; The device is further configured to: generate passage cost data for each node in the grid-directed network based on the passage cost; perform a path search operation on the grid-directed network based on the passage cost data to determine at least two target nodes; and generate the navigation path based on the at least two target nodes. The device is configured to generate respective travel cost data based on the travel costs corresponding to each node in the grid directed network in the following manner: determining a third node based on a starting node and a first current node, wherein the third node includes at least one of the first current node and a historical node, the historical node representing a node between the starting node and the first current node whose travel cost data has been determined, the starting node representing the node corresponding to the grid cell where the starting position of the aircraft is located, and the first current node being a node corresponding to any of the grid cells; determining a first Euclidean distance between each third node and an end node, wherein the end node represents the node corresponding to the grid cell where the end position of the aircraft is located; performing a multiplication operation on the travel cost of each third node and its corresponding first Euclidean distance to obtain a first sub-cost parameter; performing a summation operation on the first sub-cost parameter to obtain first cost data, wherein the travel cost data of the first current node includes the first cost data.

19. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 17.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method according to any one of claims 1 to 17.

21. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 17.

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