Method, device, equipment and medium for replacing points of unmanned aerial vehicles based on artificial potential field method

Abstract

The present invention discloses a method, device, equipment and medium for replacing unmanned aerial vehicle points based on an artificial potential field method, wherein the method comprises: selecting any waypoint in the route of a faulty unmanned aerial vehicle as the planning starting point of the point-repairing unmanned aerial vehicle, and performing path planning by the artificial potential field method according to the planning starting point to obtain multiple detached reverse paths; performing path quality scoring on multiple detached reverse paths to obtain a target detached reverse path; taking the path end point corresponding to the target detached reverse path as the current position point and the take-off point of the point-repairing unmanned aerial vehicle as the planning end point, performing path planning by the artificial potential field method according to the position vector of the current position point, the position vector of the planning end point and the position vector of the unmanned aerial vehicle around the planning end point to obtain a flight replacement reverse path; determining the point-repairing replacement path according to the flight replacement reverse path and the target detached reverse path to perform point-repairing replacement on the faulty unmanned aerial vehicle. The present invention improves the success rate and real-time performance of point-repairing replacement when the unmanned aerial vehicle is abnormal.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of unmanned aerial vehicle technology, and in particular to a method, device, equipment and medium for replacing unmanned aerial vehicle points based on an artificial potential field method. Background Art

[0002] With the rapid development of drone technology, drone light shows, as a new form of visual performance, have gradually been widely used in large-scale celebrations, sports events, commercial promotions and other occasions. Existing drone formation flight algorithms mainly rely on pre-planned paths, but in actual performances, due to various reasons (such as individual drone failures or environmental interference), "empty spots" may appear in the drone formation, thus affecting the overall visual effect. In order to improve the performance of drone light shows, a solution is needed that can use backup drones to dynamically plan paths to fill the position of faulty drones under real-time conditions to ensure the integrity and aesthetics of the drone formation.

[0003] There are two main types of path planning algorithms used in existing drone formation point filling algorithms: the first type is a heuristic search algorithm based on A*. This algorithm guides the search by evaluating the estimated cost (heuristic value) from the current node to the target node. The heuristic function is usually a function that calculates the estimated distance from the current node to the target node, such as the Euclidean distance or the Manhattan distance. The advantage of this algorithm is that when the search area is small, it can efficiently find the optimal path to the target point; however, as the search area increases, a large number of nodes need to be evaluated, and the amount of calculation is large, resulting in poor performance in real time, which leads to missed opportunities for point filling. The second type is a path planning algorithm based on artificial potential fields, which guides movement by simulating the "potential field" in the physical world. The target point generates attraction, attracting drones to move toward it. The strength of attraction usually increases as the distance decreases, causing the drone to gradually approach the target point. Other drones generate repulsion, pushing the drone away to avoid collision. The strength of repulsion usually increases as the distance decreases, causing the drone to stay away from obstacles. The advantages of this algorithm are its simple calculation and rapid response, and its suitability for real-time path planning and dynamic environments. The disadvantage is that the success rate of path planning of UAVs in environments with relatively dense obstacles is not high, that is, the success rate of UAV point replacement is low. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, equipment and medium for replacing points in a UAV based on an artificial potential field method, aiming to solve the problem that the success rate and real-time performance of point replacement in existing UAVs are low when abnormalities occur.

[0005] In a first aspect, an embodiment of the present invention provides a method for replacing points of a drone based on an artificial potential field method, comprising:

[0006] Select any waypoint in the route of the faulty UAV as the planning starting point of the replacement UAV, and perform path planning based on the planning starting point by using the artificial potential field method to obtain multiple escape reverse paths;

[0007] Performing path quality scoring on the plurality of escape reverse paths to obtain a plurality of path scores, and selecting the escape reverse path with the highest path score as the target escape reverse path;

[0008] The path endpoint corresponding to the target leaving the reverse path is taken as the current position point and the take-off point of the supplementary point UAV is taken as the planned end point, and the path planning is performed by the artificial potential field method according to the position vector of the current position point, the position vector of the planned end point, and the position vectors of the UAVs around the planned end point to obtain the flight replacement reverse path;

[0009] The point-repairing replacement path of the point-repairing UAV is determined according to the flight replacement reverse path and the target departure reverse path, so that the point-repairing UAV performs point-repairing replacement for the faulty UAV according to the point-repairing replacement path.

[0010] In a second aspect, an embodiment of the present invention further provides a UAV point replacement device based on an artificial potential field method, comprising:

[0011] A first path planning unit is used to select any waypoint in the route of the faulty UAV as a planning starting point, and perform path planning based on the planning starting point by using an artificial potential field method to obtain multiple escape reverse paths;

[0012] A path scoring unit, configured to perform path quality scoring on the plurality of escape reverse paths to obtain a plurality of path scores, and select the escape reverse path with the highest path score as a target escape reverse path;

[0013] A second path planning unit is used to take the path endpoint corresponding to the target leaving the reverse path as the current position point, and perform path planning by the artificial potential field method according to the position vector of the current position point, the position vector of the planned endpoint, and the position vectors of the drones around the planned endpoint to obtain a flight replacement reverse path;

[0014] A determination replacement unit is used to determine a point-replacing replacement path of the point-replacing UAV according to the flight replacement reverse path and the target departure reverse path, so that the point-replacing UAV can replace the faulty UAV according to the point-replacing replacement path.

[0015] In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above method when executing the computer program.

[0016] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program can implement the above method when executed by a processor.

[0017] The embodiment of the present invention provides a method, device, equipment and medium for replacing unmanned aerial vehicle points based on an artificial potential field method. The method includes: selecting any waypoint in the route of a faulty unmanned aerial vehicle as the planning starting point of the point-repairing unmanned aerial vehicle, and performing path planning according to the planning starting point by using the artificial potential field method to obtain multiple escape reverse paths; performing path quality scoring on the multiple escape reverse paths to obtain multiple path scores, and selecting the escape reverse path with the highest path score as the target escape reverse path; taking the path end point corresponding to the target escape reverse path as the current position point and the take-off point of the point-repairing unmanned aerial vehicle as the planning end point, performing path planning according to the position vector of the current position point, the position vector of the planning end point and the position vectors of the unmanned aerial vehicles around the planning end point by using the artificial potential field method to obtain a flight replacement reverse path; determining the point-repairing replacement path of the point-repairing unmanned aerial vehicle according to the flight replacement reverse path and the target escape reverse path, so that the point-repairing unmanned aerial vehicle performs point-repairing replacement on the faulty unmanned aerial vehicle according to the point-repairing replacement path. The technical solution of the embodiment of the present invention selects any waypoint in the route of the faulty UAV as the planning starting point of the point-repairing UAV, and takes the take-off point of the point-repairing UAV as the planning end point, performs path planning through the artificial potential field method according to the planning starting point and the planning end point to obtain the target departure inverse path and the flight replacement path, and determines the point-repairing replacement path of the point-repairing UAV according to the flight replacement inverse path and the target departure inverse path, so that the point-repairing UAV replaces the faulty UAV according to the point-repairing replacement path. In the whole point-repairing replacement process, because the point-repairing replacement path is planned in reverse, the problem of low success rate of path planning of UAV in dense obstacle environment is effectively solved, and the success rate and real-time performance of point-repairing replacement when the UAV is abnormal are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0019] Figure 1 A flowchart of a method for replacing points on a drone based on an artificial potential field method provided by an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of a sub-flow chart of a method for replacing points in a drone based on an artificial potential field method provided by an embodiment of the present invention;

[0021] Figure 3 A schematic diagram of another sub-flow of a method for replacing points in a drone based on an artificial potential field method provided by an embodiment of the present invention;

[0022] Figure 4 A schematic diagram of another sub-process of a method for replacing points on a drone based on an artificial potential field method provided by an embodiment of the present invention;

[0023] Figure 5 A schematic diagram of another sub-process of a method for replacing points on a drone based on an artificial potential field method provided by an embodiment of the present invention;

[0024] Figure 6 A schematic block diagram of a UAV point replacement device based on an artificial potential field method provided by an embodiment of the present invention;

[0025] Figure 7 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments 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.

[0027] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0028] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0029] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0030] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0031] See also Figure 1 , Figure 1 1 is a flow chart of a method for replacing points in a drone based on an artificial potential field method provided by an embodiment of the present invention. The method for replacing points in a drone based on an artificial potential field method is described in detail below. Figure 1 As shown, the method includes the following steps S110-S140.

[0032] S110, selecting any waypoint in the route of the faulty UAV as the planning starting point of the replacement UAV, and performing path planning based on the planning starting point by using an artificial potential field method to obtain multiple escape reverse paths.

[0033] In the embodiment of the present invention, by analyzing the case where the artificial potential field method fails, it is found that when the point-filling drone approaches the picture point, there are a large number of other drones nearby. These drones, as obstacles, will generate a large repulsive force, thereby offsetting the gravitational force of the picture point on the point-filling drone, causing the point-filling drone to wander at the picture point, wherein the picture point is any waypoint in the route of the faulty drone. In the actual application scenario, the take-off point of the point-filling drone is an open area and the picture point is an area with dense obstacles. Therefore, the planning starting point and the planning end point can be exchanged, that is, the picture point is used as the planning starting point, that is, any waypoint in the route of the faulty drone is selected as the planning starting point of the point-filling drone, and the take-off point of the point-filling drone is used as the planning end point for path planning, thereby avoiding the situation where dense obstacles appear near the end point.

[0034] It should be noted that, in this embodiment, any waypoint in the route of the faulty drone is selected as the planning starting point of the point-repairing drone, and the path planning with the take-off point of the point-repairing drone as the planning end point can be divided into two stages: the first stage is to find the direction of departure, take the departure direction as the position end point, and use the artificial potential field method to perform path planning, and the position end point of the path is as far away from the dense area as possible; the second stage is to use the artificial potential field method to plan the path between the current position point and the planning end point of the point-repairing drone after leaving the dense area. Understandably, how to choose the best departure direction when executing the first stage is crucial to improving the success rate of path planning.

[0035] It should also be noted that, in this embodiment, Figure 2As shown, step S110 may specifically include steps S111-S112:

[0036] S111, establishing a sphere with a preset radius using the planned starting point as the center, and uniformly sampling a preset number of position endpoints on the sphere;

[0037] S112. For each of the position endpoints, path planning is performed using the artificial potential field method according to the position vector of the planning starting point, the position vector of the position endpoint, and the position vectors of the drones around the position endpoint to obtain the escape reverse path.

[0038] In this embodiment, a sphere of a preset radius is established with the planning starting point as the center, and a preset number of position endpoints are uniformly sampled on the sphere, wherein the preset radius is 10 meters and the preset number is 200. It is understandable that in other embodiments, the preset radius and the preset number can be set according to actual needs and are not specifically limited here. For each of the position endpoints, the path planning is performed using the artificial potential field method based on the position vector of the planning starting point, the position vector of the position endpoint, and the position vector of the drone around the position endpoint to obtain the escaped reverse path. It is understandable that, that is, until the paths of all position endpoints are planned, a plurality of escaped reverse paths are obtained. It should be noted that, in this embodiment, for each of the position endpoints, the time for executing the path planning of the artificial potential field is 2 seconds.

[0039] For ease of understanding, the artificial potential field method is introduced in detail as follows:

[0040] The gravity formula is as follows:

[0041] F g =-k g (q cur -q goal )

[0042] In the gravitational formula, F g represents the gravity of the drone at the end point, k g represents the gravitational coefficient, q cur Represents the position vector of the drone at the starting point, q goal Represents the position vector of the drone at the end point.

[0043] The repulsive force formula is as follows:

[0044]

[0045] In the repulsive force formula, F ri represents the repulsive force exerted by obstacle i on the drone, q obsiRepresents the position vector of obstacle i, d0 represents the minimum effective distance of repulsion, and when the distance between the drone and the obstacle is greater than the minimum effective distance, the repulsion generated is considered to be 0. r is the total repulsive force on the drone.

[0046] The position update formula is as follows:

[0047] V next =V cur +(F r +F g )·dt;P next =P cur +V cur ·dt

[0048] Among them, in the position update formula, V next is the flight speed of the drone at the next moment, V cur is the current flight speed of the drone, P next is the flight position of the drone at the next moment, P cur is the current flight position of the UAV, and dt is the time step of path planning. In this embodiment, dt is set to 0.05 seconds. It can be understood that in other embodiments, dt can also be set according to actual needs.

[0049] The judgment of reaching the end point is as follows:

[0050] |P next -goal|<0.01

[0051] Among them, goal is the coordinates of the end point of path planning, and P is calculated. next The Euclidean distance to the goal. If the Euclidean distance is less than 0.01 meters, it means that the destination has been reached and the path planning is completed. It is understandable that in other embodiments, the goal can also be set to other values ​​according to actual needs.

[0052] Further, based on the artificial potential field method described above, step S112 may specifically include the following steps: calculating the gravitational force exerted on the point-filling UAV according to the position vector of the planning starting point and the position vector of the position end point. It can be understood that the planning starting point is the starting point in the artificial potential field method, and the position end point is the end point in the artificial potential field method; calculating the repulsive force exerted on the point-filling UAV according to the position vector of the planning starting point and the position vector of the UAVs around the position end point; obtaining the current flight speed and flight position of the point-filling UAV to obtain the current flight speed and current flight position; performing path planning according to the current flight speed, the current flight position, the gravitational force, the repulsive force and the end point coordinates of the position end point to obtain the escape reverse path. The path planning according to the current flight speed, the current flight position, the gravity, the repulsion and the endpoint coordinates of the position end point to obtain the escape inverse path includes: calculating the flight speed of the filling-point UAV at the next moment according to the current flight speed, the gravity and the repulsion to obtain the next flight speed; calculating the flight position of the filling-point UAV at the next moment according to the next flight speed and the current flight position to obtain the next flight position; and performing path planning according to the next flight position and the endpoint coordinates of the position end point to obtain the escape inverse path.

[0053] S120: Perform path quality scoring on the multiple escape reverse paths to obtain multiple path scores, and select the escape reverse path with the highest path score as the target escape reverse path.

[0054] In the embodiment of the present invention, after obtaining the plurality of the escaped reverse paths, path quality scores are performed on the plurality of the escaped reverse paths to obtain a plurality of path scores, specifically, as follows: Figure 3 As shown, step S120 may specifically include steps S121-S124: S121. For each of the reverse paths deviated from, calculate the minimum distance between the point-filling UAV and other UAVs at the path end point according to the position coordinates of the path end point corresponding to the reverse path deviated from and the position coordinates of other UAVs at the time point corresponding to the path end point; S122. Calculate the distance from the path start point of the deviated reverse path to the planned end point to obtain the starting distance; S123. Calculate the distance from the path end point to the planned end point to obtain the ending distance; S124. Calculate the path quality score of the deviated reverse path according to the minimum distance, the starting distance and the ending distance to obtain the path score. More specifically, as Figure 4As shown, step S124 may specifically include steps S1241-S1243: S1241, calculating the quotient of the minimum distance and the preset minimum safety distance to obtain the obstacle density; S1242, calculating the difference between the starting distance and the ending distance to obtain the distance difference; S1243, calculating the path quality score of the path leaving the reverse path according to the obstacle density, the distance difference, the obstacle density weight and the distance weight to obtain the path score. It should be noted that, in this embodiment, the path quality score of the path leaving the reverse path is calculated according to the obstacle density, the distance difference, the obstacle density weight and the distance weight through the path quality score formula to obtain the path score, wherein the path quality score formula is as follows:

[0055] path_score=0.6*cur_dist / safe_dist+0.4*(begin_dist-end_dist)

[0056] Among them, in the path quality scoring formula, path_score represents the path score, and the higher the path score, the better the path quality; cur_dist represents the minimum distance between the supplementary point UAV and other UAVs at the end of the path. Specifically, the Euclidean distance from the supplementary point UAV to each surrounding UAV is calculated according to the position coordinates of the path end point and the position coordinates of other UAVs at the corresponding time point of the path end point, and the smallest Euclidean distance is found from multiple calculated Euclidean distances as the minimum distance; safe_dist represents the preset minimum safety distance for UAV cluster flight, which is set to 1.5 meters in this embodiment; begin_dist represents the starting distance from the path starting point of the said departure from the path to the planned end point, and the Euclidean distance is calculated according to the path starting point coordinates and the planned end point coordinates of the supplementary point UAV to obtain the starting distance; end_dist represents the ending distance from the path end point to the planned end point, and the Euclidean distance is calculated according to the path end point coordinates and the planned end point coordinates of the supplementary point UAV to obtain the ending distance. It should be noted that, in this embodiment, cur_dist / safe_dist is the obstacle density, (begin_dist-end_dist) is the distance difference, 0.6 is the obstacle density weight, and 0.4 is the distance weight. It should also be noted that, in this embodiment, after calculating the path score, the escape reverse path with the highest path score is selected as the target escape reverse path. The path scores of multiple escape reverse paths are obtained by evaluating the escape path based on the obstacle density near the path end point corresponding to each escape path and the distance from the planned end point.

[0057] S130, taking the path endpoint corresponding to the target leaving the reverse path as the current position point and the take-off point of the filling-point UAV as the planned end point, performing path planning through the artificial potential field method according to the position vector of the current position point, the position vector of the planned end point and the position vectors of the UAVs around the planned end point to obtain the flight replacement reverse path.

[0058] In an embodiment of the present invention, after determining that the target has deviated from the reverse path, the path endpoint corresponding to the target deviating from the reverse path is used as the current position point and the take-off point of the point-filling UAV is used as the planning endpoint. The artificial potential field method is used to perform path planning based on the position vector of the current position point, the position vector of the planning endpoint, and the position vectors of the UAVs around the planning endpoint to obtain the flight replacement reverse path. Specifically, based on the artificial potential field method described above, the gravitational force on the point-filling UAV is calculated based on the position vector of the current position point and the position vector of the planning endpoint; the repulsive force on the point-filling UAV is calculated based on the position vector of the current position point and the position vectors of the UAVs around the planning endpoint; the flight speed and flight position of the point-filling UAV at the current moment are obtained to obtain the current flight speed and current flight position; the path planning is performed based on the current flight speed, the current flight position, the gravitational force, the repulsive force, and the endpoint coordinates of the planning endpoint to obtain the flight replacement reverse path. The step of performing path planning according to the current flight speed, the current flight position, the gravity, the repulsion and the endpoint coordinates of the planned endpoint to obtain the flight replacement inverse path includes: calculating the flight speed of the filling-point UAV at the next moment according to the current flight speed, the gravity and the repulsion to obtain the next flight speed; calculating the flight position of the filling-point UAV at the next moment according to the next flight speed and the current flight position to obtain the next flight position; performing path planning according to the next flight position and the endpoint coordinates of the planned endpoint to obtain the flight replacement inverse path. It should be noted that the current position point is the starting point in the artificial potential field method, and the planned endpoint is the endpoint in the artificial potential field method.

[0059] S140: Determine a point-repairing replacement path of the point-repairing UAV according to the flight replacement reverse path and the target departure reverse path, so that the point-repairing UAV performs a point-repairing replacement for the faulty UAV according to the point-repairing replacement path.

[0060] In an embodiment of the present invention, after the flight replacement path and the target escape path are planned by the artificial potential field method, the point-filling replacement path of the point-filling UAV is determined according to the flight replacement reverse path and the target escape reverse path. Specifically, Figure 5As shown, step S140 may specifically include steps S141-S142: S141, reversely arranging the flight replacement reverse path to obtain a flight replacement path; S142, reversely arranging the target departure reverse path to obtain a departure path, and using the flight replacement path and the departure path as the point-repairing replacement path of the point-repairing UAV. It can be understood that when the point-repairing UAV replaces the faulty UAV, the point-repairing UAV flies along the flight replacement path and the departure path in sequence to achieve point-repairing replacement of the faulty UAV.

[0061] In summary, in this embodiment, any waypoint in the route of the faulty UAV is selected as the planning starting point of the point-repairing UAV, and the path planning is performed by the artificial potential field method according to the planning starting point to obtain multiple escape reverse paths, and the path quality scores are performed on the multiple escape reverse paths to obtain the target escape reverse path; the path end point corresponding to the target escape reverse path is used as the current position point and the take-off point of the point-repairing UAV is used as the planning end point to perform path planning by the artificial potential field method to obtain the flight replacement reverse path, and the point-repairing replacement path of the point-repairing UAV is determined according to the flight replacement reverse path and the target escape reverse path, so that the point-repairing UAV can replace the faulty UAV according to the point-repairing replacement path. In the whole point-repairing replacement process, the point-repairing replacement path is planned in reverse, that is, first through The artificial potential field method path plans the target escape reverse path, and then plans the flight replacement reverse path through the artificial potential field method path. In actual flight, the flight replacement path is first flown according to the flight replacement path arranged in reverse order, and then the escape path is flown according to the target escape reverse path arranged in reverse order. That is, any waypoint in the route of the faulty UAV is selected as the planning starting point of the replacement UAV, and the path is planned with the take-off point of the replacement UAV as the planning end point, thereby avoiding the situation of dense obstacles near the end point, effectively solving the problem of low success rate of path planning of UAVs in dense obstacle environments, improving the success rate and real-time performance of replacement of replacement points when the UAV is abnormal, ensuring the integrity and aesthetics of the UAV formation, and improving the performance of the UAV light show.

[0062] Figure 6 FIG. 2 is a schematic block diagram of a UAV point replacement device 200 based on an artificial potential field method provided by an embodiment of the present invention. Figure 6 As shown, corresponding to the above-mentioned drone point replacement method based on artificial potential field method, the present invention also provides a drone point replacement device 200 based on artificial potential field method. The drone point replacement device 200 based on artificial potential field method includes a unit for executing the above-mentioned drone point replacement method based on artificial potential field method, and the device can be configured in a computer device. Specifically, please refer to Figure 6The drone point-filling replacement device 200 based on the artificial potential field method includes a first path planning unit 201, a path scoring unit 202, a second path planning unit 203 and a determination replacement unit 204.

[0063] Among them, the first path planning unit 201 is used to select any waypoint in the route of the faulty drone as the planning starting point, and perform path planning through the artificial potential field method according to the planning starting point to obtain multiple escape reverse paths; the path scoring unit 202 is used to perform path quality scoring on the multiple escape reverse paths to obtain multiple path scores, and select the escape reverse path with the highest path score as the target escape reverse path; the second path planning unit 203 is used to take the path end point corresponding to the target escape reverse path as the current position point, and perform path planning through the artificial potential field method according to the position vector of the current position point, the position vector of the planning end point, and the position vector of the drones around the planning end point to obtain a flight replacement reverse path; the determination replacement unit 204 is used to determine the point-replacing replacement path of the point-replacing drone according to the flight replacement reverse path and the target escape reverse path, so that the point-replacing drone performs point-replacing replacement on the faulty drone according to the point-replacing replacement path.

[0064] In some embodiments, such as the present embodiment, the second path planning unit 203 includes a sampling establishment unit and a path planning subunit.

[0065] Among them, the sampling unit is used to establish a sphere with a preset radius with the planning starting point as the center, and uniformly sample a preset number of position endpoints on the sphere; the path planning subunit is used to perform path planning for each position endpoint according to the position vector of the planning starting point, the position vector of the position endpoint, and the position vectors of the drones around the position endpoint through the artificial potential field method to obtain the escape inverse path.

[0066] In some embodiments, such as this embodiment, the path scoring unit 202 includes a first calculation unit, a second calculation unit, a third calculation unit, and a fourth calculation unit.

[0067] Among them, the first calculation unit is used to calculate the minimum distance between the filling point UAV and other UAVs at the path end point of each of the deviated reverse paths according to the position coordinates of the path end point corresponding to the deviated reverse path and the position coordinates of other UAVs at the time point corresponding to the path end point; the second calculation unit is used to calculate the distance from the path starting point of the deviated reverse path to the planned end point to obtain the starting distance; the third calculation unit is used to calculate the distance from the path end point to the planned end point to obtain the ending distance; the fourth calculation unit is used to calculate the path quality score of the deviated reverse path according to the minimum distance, the starting distance and the ending distance to obtain the path score.

[0068] In some embodiments, such as this embodiment, the fourth computing unit includes a first computing subunit, a second computing subunit, and a third computing subunit.

[0069] Among them, the first calculation subunit is used to calculate the quotient of the minimum distance and the preset minimum safety distance to obtain the obstacle density; the second calculation subunit is used to calculate the difference between the starting distance and the ending distance to obtain the distance difference; the third calculation subunit is used to calculate the path quality score of the departure from the reverse path according to the obstacle density, the distance difference, the obstacle density weight and the distance weight to obtain the path score.

[0070] In some embodiments, such as this embodiment, the determining replacement unit 204 includes a first reverse order arrangement unit and a second reverse order arrangement unit.

[0071] Among them, the first reverse arrangement unit is used to reversely arrange the flight replacement reverse path to obtain a flight replacement path; the second reverse arrangement unit is used to reversely arrange the target departure reverse path to obtain a departure path, and use the flight replacement path and the departure path as the point-filling replacement path of the point-filling UAV.

[0072] The above-mentioned UAV point replacement device based on the artificial potential field method can be implemented in the form of a computer program. The computer program can be used in the following manner: Figure 7 Runs on the computer device shown.

[0073] See also Figure 7 , Figure 7 300 is a schematic block diagram of a computer device provided by an embodiment of the present invention. The computer device 300 is a device having a UAV point replacement function based on an artificial potential field method.

[0074] See also Figure 7The computer device 300 includes a processor 302 , a memory and a network interface 305 connected via a system bus 301 , wherein the memory may include a non-volatile storage medium 303 and an internal memory 304 .

[0075] The non-volatile storage medium 303 can store an operating system 3031 and a computer program 3032. When the computer program 3032 is executed, the processor 302 can execute a method for replacing points of a drone based on an artificial potential field method.

[0076] The processor 302 is used to provide computing and control capabilities to support the operation of the entire computer device 300 .

[0077] The internal memory 304 provides an environment for the operation of the computer program 3032 in the non-volatile storage medium 303. When the computer program 3032 is executed by the processor 302, the processor 302 can execute a drone point replacement method based on the artificial potential field method.

[0078] The network interface 305 is used to communicate with other devices over the network. Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device 300 to which the solution of the present invention is applied. The specific computer device 300 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0079] The processor 302 is used to run a computer program 3032 stored in the memory to implement any embodiment of the above-mentioned drone point replacement method based on the artificial potential field method.

[0080] It should be understood that in the embodiment of the present invention, the processor 302 may be a central processing unit (CPU), and the processor 302 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0081] It is understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0082] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program. When the computer program is executed by a processor, the processor executes any embodiment of the above-mentioned drone point replacement method based on the artificial potential field method.

[0083] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0084] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0085] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0086] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention 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.

[0087] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially 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, and the computer software product is stored in a storage medium, including several instructions for a computer device to execute all or part of the steps of the method described in each embodiment of the present invention.

[0088] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0089] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0090] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for replacing points on a drone based on an artificial potential field method, characterized in that: include: Select any waypoint in the route of the faulty UAV as the planning starting point of the replacement UAV, and perform path planning based on the planning starting point by using the artificial potential field method to obtain multiple escape reverse paths; Performing path quality scoring on the plurality of escape reverse paths to obtain a plurality of path scores, and selecting the escape reverse path with the highest path score as the target escape reverse path; The path endpoint corresponding to the target leaving the reverse path is taken as the current position point and the take-off point of the supplementary point UAV is taken as the planned end point, and the path planning is performed by the artificial potential field method according to the position vector of the current position point, the position vector of the planned end point, and the position vectors of the UAVs around the planned end point to obtain the flight replacement reverse path; Determine a point-replacing path of the point-replacing UAV according to the flight replacement reverse path and the target departure reverse path, so that the point-replacing UAV performs point-replacing for the faulty UAV according to the point-replacing path; The step of performing path planning based on the planned starting point by using an artificial potential field method to obtain multiple escape reverse paths includes: A sphere with a preset radius is established with the planned starting point as the center, and a preset number of position endpoints are uniformly sampled on the sphere; For each of the position endpoints, the escape inverse path is obtained by performing path planning using the artificial potential field method according to the position vector of the planning starting point, the position vector of the position endpoint, and the position vectors of the drones around the position endpoint.

2. The method according to claim 1, characterized in that: The step of performing path planning according to the position vector of the planning starting point, the position vector of the position end point, and the position vectors of the drones around the position end point by using the artificial potential field method to obtain the escape inverse path comprises: Calculate the gravitational force on the point-filling UAV according to the position vector of the planning starting point and the position vector of the position end point; Calculate the repulsive force on the supplementary point UAV according to the position vector of the planning starting point and the position vectors of the UAVs around the position end point; Obtaining the current flight speed and flight position of the point-filling UAV to obtain the current flight speed and current flight position; Performing path planning according to the current flight speed, the current flight position, the gravitational force, the repulsive force, and the end point coordinates of the end point of the position to obtain the escape reverse path; The step of performing path planning according to the position vector of the current position point, the position vector of the planned endpoint, and the position vectors of the drones around the planned endpoint by using the artificial potential field method to obtain a flight replacement inverse path includes: Calculate the gravitational force on the point-filling UAV according to the position vector of the current position point and the position vector of the planned end point; Calculate the repulsive force on the supplementary point UAV according to the position vector of the current position point and the position vectors of the UAVs around the planned end point; Obtaining the current flight speed and flight position of the point-filling UAV to obtain the current flight speed and current flight position; The flight replacement inverse path is obtained by performing path planning according to the current flight speed, the current flight position, the gravitational force, the repulsive force and the endpoint coordinates of the planned endpoint.

3. The method according to claim 2, characterized in that The performing path planning according to the current flight speed, the current flight position, the gravitational force, the repulsive force, and the end point coordinates of the position end point / the planned end point to obtain the escape reverse path / the flight replacement reverse path includes: Calculate the flight speed of the point-filling UAV at the next moment according to the current flight speed, the gravitational force and the repulsive force to obtain the next flight speed; Calculate the flight position of the point-filling UAV at the next moment according to the next flight speed and the current flight position to obtain the next flight position; The path planning is performed according to the next flight position and the end point coordinates of the position end point / the planned end point to obtain the escape reverse path / the flight replacement reverse path.

4. The method according to claim 1, characterized in that The performing path quality scoring on the plurality of the deviating reverse paths to obtain a plurality of path scores includes: For each of the reverse paths that are separated, the minimum distance between the supplementary point UAV and other UAVs at the path end point is calculated according to the position coordinates of the path end point corresponding to the reverse path that is separated and the position coordinates of other UAVs at the time point corresponding to the path end point; Calculating the distance from the starting point of the path that deviates from the reverse path to the planned end point to obtain a starting distance; Calculate the distance from the end point of the path to the planned end point to obtain the end distance; The path score is obtained by calculating the path quality score of the deviated reverse path according to the minimum distance, the starting distance and the ending distance.

5. The method according to claim 4, characterized in that The calculating the path quality score of the path departing from the reverse path according to the minimum distance, the starting distance, and the ending distance to obtain the path score includes: Calculating the quotient of the minimum distance and the preset minimum safety distance to obtain the obstacle density; Calculating the difference between the starting distance and the ending distance to obtain a distance difference; The path score is obtained by calculating the path quality score of the path that deviates from the reverse path according to the obstacle density, the distance difference, the obstacle density weight, and the distance weight.

6. The method according to claim 1, characterized in that The step of determining the point-filling replacement path of the point-filling UAV according to the flight replacement reverse path and the target departure reverse path includes: Arranging the flight replacement reverse path in reverse order to obtain a flight replacement path; The target departure reverse path is arranged in reverse order to obtain a departure path, and the flight replacement path and the departure path are used as the point-filling replacement path of the point-filling UAV.

7. A UAV point replacement device based on artificial potential field method, characterized in that: include: A first path planning unit is used to select any waypoint in the route of the faulty UAV as a planning starting point, and perform path planning based on the planning starting point by using an artificial potential field method to obtain multiple escape reverse paths; A path scoring unit, configured to perform path quality scoring on the plurality of escape reverse paths to obtain a plurality of path scores, and select the escape reverse path with the highest path score as a target escape reverse path; A second path planning unit is used to take the path endpoint corresponding to the target leaving the reverse path as the current position point, and perform path planning by the artificial potential field method according to the position vector of the current position point, the position vector of the planned endpoint, and the position vectors of the drones around the planned endpoint to obtain a flight replacement reverse path; a determination replacement unit, configured to determine a point-replacing replacement path of the point-replacing UAV according to the flight replacement reverse path and the target departure reverse path, so that the point-replacing UAV performs a point-replacing replacement for the faulty UAV according to the point-replacing replacement path; Wherein, the first path planning unit includes: Establishing a sampling unit, used to establish a sphere with a preset radius using the planned starting point as the center of the sphere, and uniformly sampling a preset number of position end points on the sphere; The path planning subunit is used to perform path planning for each of the position endpoints according to the position vector of the planning starting point, the position vector of the position endpoint, and the position vectors of the drones around the position endpoint through the artificial potential field method to obtain the escape inverse path.

8. A computer device, characterized in that: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 can be implemented.

Images