Unmanned aerial vehicle route planning method and device, electronic equipment and storage medium

Abstract

The invention provides an unmanned aerial vehicle route planning method and device, electronic equipment and a storage medium, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: determining initial routes of a plurality of unmanned aerial vehicles according to a first constraint condition of the unmanned aerial vehicles; performing space-time grid division on each initial route to obtain a plurality of airspace grids; determining a safety distance between the unmanned aerial vehicles, wherein the safety distance is expressed as a plurality of airspace grids; and according to the second constraint condition of the unmanned aerial vehicle, determining the simultaneous flight route of the plurality of unmanned aerial vehicles. According to the invention, route planning of simultaneous flight of a large number of unmanned aerial vehicles is realized, the utilization rate of airspace is improved, and maximum utilization of route airspace resources is realized. Meanwhile, the low-altitude air traffic control system can perceive, monitor and control the flight of the unmanned aerial vehicle in real time within the defined route range, and unsafe conditions such as communication loss and out-of-control are prevented. The flight density of the unmanned aerial vehicle is improved on the premise of safe flight by finely dividing the airspace of the flight route, and airspace resources of the flight route are utilized to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and in particular to a route planning method, device, electronic equipment and storage medium for unmanned aerial vehicles. Background Art

[0002] At present, the route planning method of UAVs only considers the safe flight of a small number of UAVs. There is a lack of research on the scenario of a large number of UAVs flying at the same time, and there is no fine division of routes, which leads to the problem of insufficient airspace utilization. Therefore, how to realize the route planning of UAVs in the case of a large number of UAVs flying at the same time has become an urgent problem to be solved. Summary of the invention

[0003] The present invention provides a route planning method, device, electronic device and storage medium for an unmanned aerial vehicle, which are used to solve the problem of how to implement route planning for unmanned aerial vehicles when a large number of unmanned aerial vehicles are flying at the same time in the prior art, realize route planning for a large number of unmanned aerial vehicles flying at the same time, and improve the utilization rate of airspace.

[0004] The present invention provides a route planning method for an unmanned aerial vehicle, comprising the following steps: Determining initial routes of a plurality of the drones according to the first constraint condition of the drones; Performing space-time grid division on each of the initial routes to obtain a plurality of airspace grids; Determine a safe distance between each of the drones, wherein the safe distance is represented by a plurality of airspace grids; According to the second constraint condition of the drones, the routes for the simultaneous flight of the multiple drones are determined; the second constraint condition includes a safe distance between the drones.

[0005] According to a route planning method for an unmanned aerial vehicle provided by the present invention, the first constraint condition includes at least one of building information, residential areas, controlled areas, meteorological data, communication equipment information, navigation equipment information and monitoring equipment information.

[0006] According to a method for planning a route for a drone provided by the present invention, determining initial routes for a plurality of drones according to a first constraint condition of the drones comprises: According to the flight mission of each drone, the starting point and the end point of each drone are obtained; Determine the flight area of ​​each drone according to the starting point and the end point of each drone; Determine initial routes of the plurality of UAVs according to the flight area and the first constraint condition.

[0007] According to a method for planning a route for a drone provided by the present invention, the step of determining a safe distance between the drones comprises: Obtaining the radius of the flight protection zone of each of the drones; Determining the distance between the drones according to the spatial position coordinates of the drones; If the distance is smaller than the sum of the radii of the flight protection zone of the UAV, the distance is determined to be the safety distance.

[0008] According to a route planning method for a drone provided by the present invention, the radius of the flight protection zone of the drone is determined based on the following method: The sum of the UAV radius, the system navigation error, the flight technical error and the UAV safety radius is obtained, and the sum is used as the radius of the flight protection zone of the UAV.

[0009] According to a route planning method for a drone provided by the present invention, the second constraint condition includes at least one of a flight altitude, a flight range, a flight speed and the safety distance; The step of determining the routes for the simultaneous flight of the plurality of drones according to the second constraint condition of the drones comprises: When the second constraint condition is met, the number of the drones flying simultaneously is increased one by one until the distance between the drones does not meet the safety distance, thereby obtaining a route in which the multiple drones fly simultaneously.

[0010] According to a method for planning a route for a drone provided by the present invention, the step of dividing each of the initial routes into time-space grids to obtain a plurality of airspace grids includes: Determining the boundary coordinates of each of the initial routes; Using the set encoding precision, convert each of the boundary coordinates into a corresponding encoding string; Each of the coded strings is used as the spatial grid, wherein each of the coded strings represents a spatial unit.

[0011] The present invention also provides a route planning device for an unmanned aerial vehicle, comprising the following modules: A first route determination module, used to determine initial routes of a plurality of drones according to a first constraint condition of the drones; A grid division module, used for performing time-space grid division on each of the initial routes to obtain a plurality of airspace grids; A safety distance determination module, used to determine the safety distance between the drones, wherein the safety distance is represented by a plurality of airspace grids; The second route determination module is used to determine the routes for the simultaneous flight of multiple drones according to the second constraint condition of the drones; the second constraint condition includes the safe distance between the drones.

[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a route planning method for a drone as described above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the route planning method for a drone as described in any one of the above is implemented.

[0014] The route planning method, device, electronic device and storage medium of the drone provided by the present invention determine the initial routes of multiple drones according to the first constraint condition of the drone; divide each initial route into time and space grids to obtain multiple airspace grids; determine the safety distance between each drone, and the safety distance is expressed as multiple airspace grids; according to the second constraint condition of the drone, determine the routes of multiple drones flying simultaneously. The present invention realizes the route planning for a large number of drones flying simultaneously, improves the utilization rate of airspace, and realizes the maximum utilization of route airspace resources. At the same time, within the designated route range, the low-altitude air traffic control system can sense, monitor and control the flight of drones in real time to prevent unsafe situations such as communication loss and loss of control. By finely dividing the route airspace, the flight density of drones is increased under the premise of safe flight, and the route airspace resources are utilized to the maximum extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 This is one of the flow charts of the route planning method for a UAV provided by the present invention.

[0017] Figure 2 This is the second flow chart of the route planning method for a UAV provided by the present invention.

[0018] Figure 3 It is a structural schematic diagram of the route planning device for the UAV provided by the present invention.

[0019] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Combine the following Figure 1-Figure 4 The invention describes a route planning method, device, electronic device and storage medium for a drone.

[0022] Figure 1 This is one of the flow charts of the route planning method for a UAV provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 101, determining initial routes of a plurality of drones according to a first constraint condition of the drones.

[0023] In an embodiment of the present invention, the first constraint condition is determined based on the flight requirements of the UAV, and the first constraint condition includes at least one of building information, residential areas, control areas, meteorological data, communication equipment information, navigation equipment information, and monitoring equipment information. It is understandable that buildings, residential areas, and control areas are ground structures and densely populated areas, and their impact on the flight of the UAV needs to be considered. The route planning of the UAV should avoid buildings, residential areas, and control areas to ensure flight safety. Secondly, meteorological conditions are crucial to the flight safety of the UAV. For example, severe weather such as strong winds, thunderstorms, and precipitation will affect the flight capability and stability of the UAV. Therefore, route planning needs to consider meteorological data to ensure that the flight mission is performed under appropriate weather conditions. Furthermore, the UAV relies on communication equipment to communicate with the ground control center during flight, the navigation equipment determines its position and flight direction, and the monitoring equipment is used to track and monitor the flight status. Therefore, route planning needs to ensure that these devices are intact and can operate effectively to ensure the safety and controllability of the flight.

[0024] Optionally, the first constraint also includes information such as electromagnetic interference and topography. It can be understood that electromagnetic interference refers to interference signals from electronic devices or other electromagnetic sources, which will affect the communication and navigation systems of the drone. Therefore, route planning needs to avoid electromagnetic interference areas to ensure the normal operation of communication and navigation equipment. Topography is also an important constraint factor in low-altitude drone flight. They can affect the choice and safety of the flight path. Therefore, route planning needs to consider the impact of terrain undulations and landform features on the flight path.

[0025] According to the designated available low-altitude flight airspace, taking into account the constraints of buildings, residential areas, control areas, meteorological data, communication equipment, navigation equipment and surveillance equipment in the area, the flight route is drawn, and communication blind spot equipment is added as appropriate to build a route. The UAV flies within the route, and the communication, navigation, surveillance equipment and other equipment can be kept intact within the route, and the low-altitude air traffic control system can control and monitor the flight of the UAV.

[0026] In one embodiment, the starting point and the end point of each drone are obtained according to the flight mission of each drone, and then the flight area of ​​each drone is determined according to the starting point and the end point of each drone; further, the initial routes of multiple drones are determined according to the flight area and the first constraint. Among them, the flight mission refers to a specific task or action performed by a drone or aircraft, the purpose of which is to complete a series of operations according to predetermined goals and requirements. The route of a drone refers to the trajectory or route of flying in the air according to a predetermined flight path, and the route should always be within the range of the route.

[0027] For example, assuming that the flight mission is to perform a specific task from one location to another, such as logistics distribution, monitoring, patrolling or photography, the starting point and the end point of the drone can be obtained. Then, based on the locations of the starting point and the end point, a larger flight area is determined to ensure that the drone does not exceed the predetermined area during the mission. Within the flight area, the first constraint condition is applied to generate the initial route of the drone. For example, the initial route is generated using a route generation algorithm or a route planning software or tool.

[0028] Step 102, dividing each of the initial routes into time-space grids to obtain a plurality of airspace grids.

[0029] In the embodiment of the present invention, the GeoHash algorithm is used to divide the initial route into a spatiotemporal grid, discretize the route airspace, and subdivide the continuous airspace into multiple basic airspace units, namely airspace grids or grid units. It can be understood that the basic airspace unit can be used as a spatial index for organizing and managing air traffic operation data, as a benchmark for physical information mapping of aircraft operations, and as an airspace component element for various different needs.

[0030] In one embodiment, the boundary coordinates of each initial route are determined, and then each boundary coordinate is converted into a corresponding code string using a set coding precision, and each code string is used as an airspace grid, where each code string represents a spatial unit. It can be understood that the use of the GeoHash algorithm to perform spatiotemporal grid division on low-altitude routes is to discretize the complex route airspace to facilitate the management and monitoring of drone flights. The GeoHash algorithm can divide the geographic space into rectangular areas of different precisions, each of which has a unique GeoHash code, which can be effectively used as a tool for spatial indexing and airspace management.

[0031] For example, using the GeoHash algorithm to divide the low-altitude flight routes into time and space grids mainly includes the following contents: (1) Determine the airspace boundaries of the route. First, it is necessary to determine the boundary coordinates of the low-altitude route airspace, such as the latitude and longitude coordinates of the northwest corner and the southeast corner. The route airspace can be understood as the airspace where the initial route is located. Assume that the boundaries of the route airspace are as follows: Northwest Corner: longitude 120°E, latitude 35°N; Southeast Corner: longitude 125°E, latitude 30°N.

[0032] (2) Select GeoHash encoding accuracy. Select an appropriate GeoHash encoding length based on the size of the airspace and the required accuracy. A shorter encoding length represents a larger rectangular area, while a longer encoding length represents a smaller rectangular area. The specific length needs to be determined based on specific application requirements.

[0033] (3) GeoHash code generation. Using the selected GeoHash code length, the boundary longitude and latitude range of the route airspace is converted into GeoHash codes, i.e., GeoHash code strings. These codes will become the discretization units of the route airspace.

[0034] For example, assuming that a 5-bit precision GeoHash code is selected, the GeoHash code of the northwest corner point is ww8g0, and the GeoHash code of the southeast corner point is w9k4z. These two codes will cover the entire area of ​​the route airspace, and each GeoHash code represents a specific spatial unit.

[0035] (4) Dividing the space-time grid. The selected GeoHash codes are regarded as the basic units of the space-time grid. These codes can help divide the route airspace into discrete spatial units that can be managed and monitored. For example, different GeoHash codes in the route airspace can be assigned to different drones or aircraft in order to manage their flight paths and avoid collisions.

[0036] The four-dimensional space-time grid is divided by using the GeoHash algorithm, including length (longitude), width (latitude), height and time. Among them, the GeoHash algorithm divides the area on the earth's surface by longitude and latitude, and divides the continuous geographic space into discrete grid cells. The altitude dimension refers to the flight altitude, that is, the vertical position of the drone relative to the ground. The time dimension represents the flight time, that is, the flight period of the drone in the air. By combining these four dimensions, a composite space-time grid system can be formed, and each grid cell can be uniquely identified, for example, through GeoHash coding, so that the air traffic management system can accurately monitor and manage the flight activities of drones. This space-time grid division method can not only improve the efficiency of airspace utilization and flight safety, but also provide a feasible technical solution for the large-scale integration and management of drones in the future.

[0037] Optionally, the division accuracy of the airspace grid is determined by modifying the number of iterations of the GeoHash algorithm.

[0038] The embodiment of the present invention divides the complex low-altitude airspace into discrete units through the GeoHash algorithm, providing an effective spatial indexing and management tool for the safe flight of drones and air traffic management.

[0039] Step 103: determine a safe distance between each of the drones, wherein the safe distance is represented by a plurality of airspace grids.

[0040] In an embodiment of the present invention, the route airspace is divided into N airspace grids, each of which can be regarded as a cube or a grid point in a cube. The position of each drone can be mapped to the nearest airspace grid through its spatial coordinates (x, y, z). By discretizing the grids, the minimum safety distance requirement between each pair of drones can be clarified to reduce the risk of collision.

[0041] In one embodiment, the radius of the flight protection zone of each drone is obtained, and then the distance between the drones is determined according to the spatial position coordinates of each drone; if the distance is less than the sum of the radii of the flight protection zones of the drones, the distance is determined to be a safe distance. The flight protection zone of a drone refers to a safe space reserved during flight to avoid collisions with other drones or obstacles. The flight protection zone can be a spherical or cubic area surrounding the current position of the drone. The flight protection zone is dynamically adjusted as the drone moves to maintain an appropriate safety distance.

[0042] For example, the distance between drones can be calculated by their coordinates in three-dimensional space. Suppose there are two drones, whose spatial coordinates are A (x1, y1, z1) and B (x2, y2, z2), and the distance d between them can be calculated by the following formula: d=sqrt{(x2-x1)^2+(y2-y1)^2+(z2-z1)^2}; Among them, sqrt{} represents the square root.

[0043] The sum of the radii of the flight protection zones of the two drones is further calculated, and then it is determined whether the distance between the drones is greater than the sum of the radii of the flight protection zones of the drones; if it is greater, it means that there is a collision risk between the drones; if it is less, it means that there is no collision risk between the drones, and the distance is determined to be a safe distance.

[0044] In one embodiment, the radius of the flight protection zone of the drone is determined based on the following method: obtaining the sum of the drone radius, system navigation error, flight technical error, and drone safety radius, and using the sum as the radius of the flight protection zone of the drone. For example, the flight protection zone of the flying drone is regarded as a sphere with a radius of R: The radius of the drone's flight protection zone R = drone radius r + system navigation error E1 + flight technical error E2 + 0.5 * drone safety radius d; Among them, the radius r of the drone refers to the physical size of the drone itself, that is, the size of the space occupied by the drone when flying. The system navigation error E1 is the accuracy error of the drone navigation system. The navigation system may cause a certain deviation between the flight trajectory and the planned route due to various factors (such as GPS signal error, inertial navigation system accuracy, etc.). The flight technical error E2 refers to the operation error or decision error of the drone pilot or autonomous flight control system. Even under ideal conditions, there may be trajectory deviations in actual flight due to environmental changes, wind speed and other factors. The drone safety radius d refers to the certain space that needs to be reserved around the drone during flight to ensure flight safety and avoid collisions with other objects or drones.

[0045] In one embodiment, to ensure safe flight, the radii of the flight protection zones of any two drones should not overlap, that is, the distance between the drones is greater than the sum of the radii of the flight protection zones of the two drones: For any time t, dist(p i (t), p j (t))>R i +R j ; Among them, p i (t) represents the spatial position coordinates of the track of the i-th UAV at time t, p j (t) represents the spatial position coordinates of the jth UAV track at time t, R i represents the radius of the flight protection zone sphere of the i-th UAV, R j Represents the radius of the flight protection zone sphere of the jth UAV.

[0046] If dist(p i (t), p j (t))>R i +R j , indicating that the actual distance between UAV i and UAV j is greater than the sum of their respective flight protection zone radii. In this case, there is no collision risk between UAV i and UAV j. It can be understood that the flight protection zone radius R i and R j The purpose of the design is to ensure that the drones have enough space to avoid collision with other drones during flight. i +R j , indicating that the relative positions between UAV i and UAV j are within their respective protection areas, and there is no overlapping area, so no collision will occur.

[0047] If dist(p i (t), p j (t)) <R i +R j , indicating that the actual distance between UAV i and UAV j is less than the sum of their respective protection zone radii, and there is an overlapping area, so there is a potential collision risk between UAV i and UAV j.

[0048] By comparing the actual distance between drones and the sum of their respective flight protection zone radii, it is possible to quickly assess whether there is a collision risk between them, thereby improving the accuracy of route planning.

[0049] In one embodiment, when calculating the safe distance between drones, the position of the drone is first mapped in a specific grid based on the divided airspace grid, and the safe distance between the drones is generally represented as N discretized airspace grids. On this basis, the calculation process of the safe distance between drones can be accelerated. For example, assuming that there are 5 drones in the current airspace, and it is necessary to determine whether the distance between drone A and other drones is safe, in the related art, drone A needs to calculate the safe distance with the other 4 drones respectively. In the embodiment of the present invention, if the division of the airspace grid is fine enough, it is only necessary to traverse the airspace grid corresponding to the safe distance of drone A to see whether there is a drone, and then determine whether there is a collision risk between drones. However, due to the actual situation, the division accuracy of the airspace grid may not meet the requirements. Then, it is possible to first traverse the airspace grid corresponding to the safe distance of drone A to see whether there is a drone. If so, the actual distance with the drone in the airspace grid is calculated in detail, and the calculation result is used as the final basis to evaluate whether there is a collision risk between drones. This method can avoid calculating the distance between drones separately, reduce the complexity of the algorithm, reduce the amount of calculation, and also ensure the accuracy of the calculation results.

[0050] By dividing the airspace into discrete grids, the drone only needs to calculate the distance to other drones in the grid and its adjacent grids. This can significantly reduce the number of distance logarithms that need to be calculated compared to directly calculating the distance to each drone. This method can effectively reduce the computational complexity, especially when the number of drones in the airspace increases. At the same time, through the gridding method, it is possible to quickly determine whether there are other drones in the airspace grid adjacent to or corresponding to the drone, making the decision-making process more efficient. On the other hand, the gridding method helps to design a concise and efficient collision avoidance algorithm. By pre-defining the grid size and adjacent relationship, obstacle avoidance and collision prevention measures can be implemented based on the distribution of drones within and between grids. This method is easier to implement and optimize than the obstacle avoidance algorithm in continuous space.

[0051] Step 104: determining routes for simultaneous flight of multiple drones according to the second constraint condition of the drones.

[0052] In an embodiment of the present invention, the second constraint condition includes at least one of a flight altitude, a flight range, a flight speed, and a safety distance. Optionally, the second constraint condition may also include: Flight attitude: Some missions may require specific flight attitudes, such as heading, pitch angle, yaw angle, etc.

[0053] Meteorological conditions: Meteorological factors such as wind speed, precipitation, and visibility may affect the flight safety and stability of the drone, and the impact of these conditions on the flight plan needs to be considered.

[0054] Communication and control range: The drone needs to be within communication range and under control so that the operator can monitor and intervene at any time.

[0055] Ground facilities: Some missions require consideration of the availability and adaptability of ground facilities such as take-off points, landing points, and possible mid-course resupply points.

[0056] In one embodiment, when the second constraint condition is met, the number of drones flying simultaneously is increased one by one until the distance between the drones does not meet the safety distance, thereby obtaining a route for multiple drones flying simultaneously.

[0057] For example, the performance parameters of the drone, such as flight altitude and range, and the safety distance between drones are used as constraints, the starting point and end point of the drone are considered, and an artificial intelligence algorithm (such as a multi-objective optimization algorithm) is used to develop a flight plan for the drone; the number of drones in the route is gradually increased until the drone's track does not meet the safety distance.

[0058] The steps of setting a route for a drone using a multi-objective optimization algorithm include: (1) Constraints. UAV performance parameters: including flight altitude, range, etc. UAV safety distance: Each UAV needs to maintain a certain safety distance during flight, which is a key condition to ensure flight safety.

[0059] (2) Objectives: Usually, the flight plan of a UAV involves the optimization of multiple objectives, such as reaching the destination in the shortest time, minimizing energy consumption, avoiding collisions with other UAVs, etc. These objectives may be contradictory, so a multi-objective optimization algorithm is needed to find the best solution that balances each objective.

[0060] (3) Execution process: Input parameters: The divided airspace grids are used as input. These grids reflect the discretization information of the airspace and help the algorithm plan the flight path in the airspace. Output: The algorithm will output the flight path of each drone to ensure that the flight is carried out while meeting all constraints.

[0061] (4) Algorithm selection: You can choose a multi-objective optimization algorithm that is suitable for solving this type of problem, such as genetic algorithm, particle swarm algorithm, simulated annealing algorithm, etc. These algorithms can search for the optimal solution in a complex space and can consider multiple objectives at the same time to balance the various constraints in the flight plan.

[0062] For example, the specific implementation steps are: Input: Provide the starting point and end point of each drone, as well as related performance parameters and constraints (such as flight altitude, safety distance, etc.); Algorithm execution: The algorithm operates on the divided airspace grid, trying to find the optimal flight path for each drone to avoid collisions with other drones and meet flight efficiency and safety requirements; Optimization process: Through multiple iterations and simulations, the algorithm gradually optimizes the flight path of each drone until the predetermined optimization goal is reached or an acceptable solution is found.

[0063] Through the above method, it is possible to effectively plan routes for a large number of drones flying simultaneously in complex environments, ensure that they can perform tasks safely and efficiently in low-altitude airspace, avoid collisions with other drones or ground obstacles, and ensure the normal operation of communication, navigation and surveillance equipment.

[0064] The route planning method for a drone provided in an embodiment of the present invention determines the initial routes of multiple drones according to the first constraint of the drone; divides each initial route into a time-space grid to obtain multiple airspace grids; determines the safety distance between each drone, and the safety distance is expressed as multiple airspace grids; determines the routes for multiple drones to fly simultaneously according to the second constraint of the drone; the second constraint includes the safety distance between the drones. The present invention realizes the route planning for a large number of drones to fly simultaneously, improves the utilization rate of the airspace, and realizes the maximum utilization of the route airspace resources. At the same time, within the designated route range, the low-altitude air traffic control system can sense, monitor, and control the flight of the drone in real time to prevent unsafe situations such as communication loss and loss of control. By finely dividing the route airspace, the flight density of drones is increased under the premise of safe flight, and the route airspace resources are utilized to the maximum extent to improve economic benefits.

[0065] In order to further analyze and explain the route planning method of the UAV proposed in the present invention, refer to Figure 2 and the following examples.

[0066] In order to efficiently utilize the flight airspace and meet the requirements of high-density flight of low-altitude unmanned aerial vehicles, the embodiment of the present invention proposes a route planning method for low-altitude airspace unmanned aerial vehicles, which mainly includes the following contents: 1. According to the designated available low-altitude flight airspace, routes are drawn taking into account constraints such as buildings, residential areas, controlled areas, meteorological data, etc. in the area. Low-altitude aircraft fly within the routes. Communication, navigation, surveillance equipment and other equipment can be kept intact within the routes. The low-altitude air traffic control system can control and monitor the flight of drones.

[0067] 2. Use GeoHash algorithm to divide the route into time and space grids, discretize the route airspace, and subdivide the continuous airspace into multiple basic airspace units. This unit can be used as a spatial index for organizing and managing air traffic operation data, as a benchmark for physical information mapping of aircraft operations, and as an airspace component for various different needs.

[0068] 3. Consider the drone protection zone in flight as a sphere with a radius of R: The radius of the drone's flight protection zone R = drone radius r + system navigation error E1 + flight technical error E2 + 0.5 * drone safety radius d; To ensure safe flight, the radii of the protection zones of any two drones should not overlap, that is, the distance between the drones should be greater than the sum of the radii of the two drone protection zones: For any time t, dist(p i (t), p j (t))>R i +R j ; Among them, p i (t) represents the spatial position coordinates of the track of the i-th UAV at time t, p j (t) represents the spatial position coordinates of the jth UAV track at time t, R i represents the radius of the flight protection zone sphere of the i-th UAV, R j Represents the radius of the flight protection zone sphere of the jth UAV.

[0069] When calculating, the space-time grid defined in Part 2 can be used, that is, the safe distance between drones should be represented as N discretized airspace grids.

[0070] 4. Take the performance parameters of the drone, such as flight altitude and range, and the safe distance between drones in Part 3 as constraints, consider the starting and ending points of the drone, and use an artificial intelligence algorithm to develop a flight plan for the drone; gradually increase the number of drones in the route until the drone's track does not meet the safe distance.

[0071] In the embodiment of the present invention, within the scope of the designated route, the low-altitude air traffic control system can sense, monitor and control the flight of drones in real time to prevent unsafe situations such as loss of communication and loss of control. By finely dividing the route airspace, the flight density of drones can be increased under the premise of safe flight, and the route airspace resources can be utilized to the maximum extent to improve economic benefits.

[0072] The route planning device for a UAV provided by the present invention is described below. The route planning device for a UAV described below and the route planning method for a UAV described above can be referred to each other.

[0073] refer to Figure 3 The route planning device for a UAV provided by the present invention includes a first route determination module 301, a grid division module 302, a safety distance determination module 303 and a second route determination module 304.

[0074] A first route determination module 301, configured to determine initial routes of a plurality of drones according to a first constraint condition of the drones; A grid division module 302 is used to perform time-space grid division on each of the initial routes to obtain a plurality of airspace grids; A safety distance determination module 303 is used to determine a safety distance between each of the drones, wherein the safety distance is represented by a plurality of airspace grids; The second route determination module 304 is used to determine the routes for the simultaneous flight of multiple drones according to the second constraint condition of the drones; the second constraint condition includes the safe distance between the drones.

[0075] The route planning device for a drone provided in an embodiment of the present invention determines the initial routes of multiple drones according to the first constraint of the drone; divides each initial route into time and space grids to obtain multiple airspace grids; determines the safety distance between each drone, and the safety distance is expressed as multiple airspace grids; determines the routes for multiple drones to fly simultaneously according to the second constraint of the drone; the second constraint includes the safety distance between the drones. The present invention realizes the route planning for a large number of drones to fly simultaneously, improves the utilization rate of the airspace, and realizes the maximum utilization of the route airspace resources. At the same time, within the designated route range, the low-altitude air traffic control system can sense, monitor, and control the flight of the drone in real time to prevent unsafe situations such as communication loss and loss of control. By finely dividing the route airspace, the flight density of drones is increased under the premise of safe flight, and the route airspace resources are utilized to the maximum extent to improve economic benefits.

[0076] In one embodiment, the first constraint condition includes at least one of building information, residential areas, control areas, meteorological data, communication equipment information, navigation equipment information and surveillance equipment information.

[0077] In one embodiment, the first route determination module 301 is specifically configured to: According to the flight mission of each drone, the starting point and the end point of each drone are obtained; Determine the flight area of ​​each drone according to the starting point and the end point of each drone; Determine initial routes of the plurality of UAVs according to the flight area and the first constraint condition.

[0078] In one embodiment, the safety distance determination module 303 is specifically configured to: Obtaining the radius of the flight protection zone of each of the drones; Determining the distance between the drones according to the spatial position coordinates of the drones; If the distance is smaller than the sum of the radii of the flight protection zone of the UAV, the distance is determined to be the safety distance.

[0079] In one embodiment, the safety distance determination module 303 is further used to: The sum of the UAV radius, the system navigation error, the flight technical error and the UAV safety radius is obtained, and the sum is used as the radius of the flight protection zone of the UAV.

[0080] In one embodiment, the second constraint condition includes at least one of the flight altitude, the flight range, the flight speed and the safety distance; the second route determination module 304 is specifically used to: When the second constraint condition is met, the number of the drones flying simultaneously is increased one by one until the distance between the drones does not meet the safety distance, thereby obtaining a route in which the multiple drones fly simultaneously.

[0081] In one embodiment, the grid division module 302 is specifically used to: Determining the boundary coordinates of each of the initial routes; Using the set encoding precision, convert each of the boundary coordinates into a corresponding encoding string; Each of the coded strings is used as the spatial grid, wherein each of the coded strings represents a spatial unit.

[0082] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the route planning method of the drone, the method comprising: determining the initial routes of multiple drones according to the first constraint of the drone; performing spatiotemporal grid division on each of the initial routes to obtain multiple airspace grids; determining the safety distance between each of the drones, the safety distance being represented as multiple airspace grids; determining the routes of the multiple drones flying simultaneously according to the second constraint of the drone; the second constraint includes the safety distance between the drones.

[0083] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0084] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the route planning method for a drone provided by the above-mentioned methods, the method including: determining the initial routes of multiple drones according to a first constraint condition of the drone; performing spatiotemporal grid division on each of the initial routes to obtain multiple airspace grids; determining a safe distance between each of the drones, the safe distance being represented as multiple airspace grids; determining the routes for simultaneous flight of multiple drones according to a second constraint condition of the drone; the second constraint condition includes the safe distance between the drones.

[0085] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the route planning method for a drone provided by the above-mentioned methods, the method comprising: determining the initial routes of multiple drones according to a first constraint condition of the drones; performing spatiotemporal grid division on each of the initial routes to obtain multiple airspace grids; determining a safe distance between each of the drones, the safe distance being represented as multiple airspace grids; determining the routes for simultaneous flight of multiple drones according to a second constraint condition of the drones; the second constraint condition includes the safe distance between the drones.

[0086] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0087] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A route planning method for an unmanned aerial vehicle, characterized in that: include: Determining initial routes of a plurality of the drones according to the first constraint condition of the drones; Performing space-time grid division on each of the initial routes to obtain a plurality of airspace grids; Determine a safe distance between each of the drones, wherein the safe distance is represented by a plurality of airspace grids; According to the second constraint condition of the drones, the routes for the simultaneous flight of the multiple drones are determined; the second constraint condition includes a safe distance between the drones.

2. The method for planning a route for an unmanned aerial vehicle according to claim 1, characterized in that: The first constraint condition includes at least one of building information, residential areas, control areas, meteorological data, communication equipment information, navigation equipment information and monitoring equipment information.

3. The method for planning a route for an unmanned aerial vehicle according to claim 1, characterized in that: The step of determining the initial routes of the plurality of drones according to the first constraint condition of the drones includes: According to the flight mission of each drone, the starting point and the end point of each drone are obtained; Determine the flight area of ​​each drone according to the starting point and the end point of each drone; Determine initial routes of the plurality of UAVs according to the flight area and the first constraint condition.

4. The method for planning a route for an unmanned aerial vehicle according to claim 1, characterized in that: The step of determining a safe distance between the drones comprises: Obtaining the radius of the flight protection zone of each of the drones; Determining the distance between the drones according to the spatial position coordinates of the drones; If the distance is smaller than the sum of the radii of the flight protection zone of the UAV, the distance is determined to be the safety distance.

5. The method for planning a route for an unmanned aerial vehicle according to claim 4, characterized in that: The radius of the drone's flight protection zone is determined based on the following: The sum of the UAV radius, the system navigation error, the flight technical error and the UAV safety radius is obtained, and the sum is used as the radius of the flight protection zone of the UAV.

6. The method for planning a route for an unmanned aerial vehicle according to claim 1, characterized in that: The second constraint condition includes at least one of a flight altitude, a flight range, a flight speed and the safety distance; The step of determining, according to the second constraint condition of the drone, routes for simultaneous flight of the plurality of drones comprises: When the second constraint condition is met, the number of the drones flying simultaneously is increased one by one until the distance between the drones does not meet the safety distance, thereby obtaining a route in which the multiple drones fly simultaneously.

7. The method for planning a route for an unmanned aerial vehicle according to claim 1, characterized in that: The time-space grid division of each of the initial routes is performed to obtain a plurality of airspace grids, including: Determining the boundary coordinates of each of the initial routes; Using the set encoding precision, convert each of the boundary coordinates into a corresponding encoding string; Each of the coded strings is used as the spatial grid, wherein each of the coded strings represents a spatial unit.

8. A route planning device for an unmanned aerial vehicle, characterized in that: include: A first route determination module, used to determine initial routes of a plurality of drones according to a first constraint condition of the drones; A grid division module, used for performing time-space grid division on each of the initial routes to obtain a plurality of airspace grids; A safety distance determination module, used to determine the safety distance between the drones, wherein the safety distance is represented by a plurality of airspace grids; The second route determination module is used to determine the routes for the simultaneous flight of multiple drones according to the second constraint condition of the drones; the second constraint condition includes the safe distance between the drones.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the route planning method for the unmanned aerial vehicle as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the route planning method for a drone as described in any one of claims 1 to 7 is implemented.

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