Path planning method, device, equipment, storage medium and computer program product

Abstract

The application discloses a path planning method and device, equipment, storage medium and computer program product, to solve the problems of insufficient coverage of business demand points and lack of active avoidance ability for signal weak areas in existing unmanned aerial vehicle signal space measurement path planning. The method comprises the following steps: obtaining target position corresponding to a path planning task, at least one business demand point data, and state information of an unmanned aerial vehicle executing the path planning task; determining a first potential field pointing to the target position according to the target position and the position information; determining a second potential field pointing to the business demand point according to the business demand point data; determining a third potential field according to the signal strength; generating a composite potential field according to the first potential field, the second potential field and the third potential field, and determining the flight path of the unmanned aerial vehicle according to the composite potential field.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a path planning method, apparatus, device, storage medium, and computer program product. Background Technology

[0002] As wireless communication networks evolve towards higher density and wider coverage, signal quality testing has become a crucial aspect of ensuring network performance. Existing technologies primarily achieve automated signal testing from two dimensions: path planning and equipment deployment. On one hand, the Artificial Potential Field (APF) method is used to construct UAV path planning models, leveraging the interaction of gravity and repulsion to guide flight trajectories. On the other hand, the design of UAV-mounted testing equipment enables real-time acquisition and analysis of wireless signals. These solutions provide technical support for efficient testing of wireless networks.

[0003] In terms of path planning, existing methods typically use the current coordinates, target point coordinates, and a fixed gravity coefficient as input parameters to calculate the flight path from the starting point to the destination. Existing technologies have the following main problems: First, path planning only considers a single target point, neglecting specific needs in the business scenario, resulting in key testing areas such as user complaint hotspots not being effectively covered, affecting the data acquisition effect of signal aerial testing; second, the obstacle avoidance mechanisms of existing methods only target static obstacles and cannot proactively predict dynamic risks, lacking predictive avoidance of potentially dangerous areas such as weak GPS signals, posing flight safety hazards.

[0004] Therefore, how to improve the relevance and safety of testing while ensuring the safety of drone flight has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides a path planning method to address the problems of insufficient coverage of service demand points and lack of proactive avoidance capability for weak signal areas in existing UAV signal aerial survey path planning.

[0006] This application also provides a path planning device to solve the problems of insufficient coverage of service demand points and lack of active avoidance capability for weak signal areas in existing UAV signal aerial survey path planning.

[0007] This application also provides a path planning device to solve the problems of insufficient coverage of service demand points and lack of active avoidance capability for weak signal areas in existing UAV signal aerial survey path planning.

[0008] This application also provides a computer-readable storage medium to address the problems of insufficient coverage of service demand points and lack of proactive avoidance capability for weak signal areas in existing UAV signal aerial survey path planning.

[0009] A computer program product designed to address the problems of insufficient coverage of service demand points and lack of proactive avoidance capability for weak signal areas in existing UAV signal aerial survey path planning.

[0010] The embodiments of this application adopt the following technical solutions: A path planning method includes: acquiring a target location corresponding to a path planning task, at least one business demand point data, and status information of a drone executing the path planning task, wherein the business demand point is determined based on customer complaint data, and the status information includes the drone's location information and the drone's signal strength; determining a first potential field pointing towards the target location based on the target location and the location information; determining a second potential field pointing towards the business demand point based on the business demand point data; determining a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area; generating a composite potential field based on the first potential field, the second potential field, and the third potential field, and determining the drone's flight path based on the composite potential field.

[0011] A path planning device includes: a data acquisition unit, configured to acquire a target location corresponding to a path planning task, at least one business demand point data, and status information of a drone performing the path planning task, wherein the business demand point is determined based on customer complaint data, and the status information includes the location information and signal strength of the drone; a potential field determination unit, configured to determine a first potential field pointing towards the target location based on the target location and the location information; a potential field determination unit, configured to determine a second potential field pointing towards the business demand point based on the business demand point data; a potential field determination unit, configured to determine a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area; and a path planning unit, configured to generate a composite potential field based on the first, second, and third potential fields, and determine the flight path of the drone based on the composite potential field.

[0012] A path planning device, comprising: The processor; and a memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the following operations: acquiring a target location corresponding to a path planning task, at least one business demand point data, and status information of a drone performing the path planning task, wherein the business demand point is determined based on customer complaint data, and the status information includes the location information of the drone and the signal strength of the drone; determining a first potential field pointing to the target location based on the target location and the location information; determining a second potential field pointing to the business demand point based on the business demand point data; determining a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area; generating a composite potential field based on the first potential field, the second potential field, and the third potential field, and determining the flight path of the drone based on the composite potential field.

[0013] A computer-readable storage medium stores one or more programs that, when executed by an electronic device including multiple applications, cause the electronic device to perform the following operations: acquire a target location corresponding to a path planning task, at least one business demand point data, and status information of a drone performing the path planning task, wherein the business demand point is determined based on customer complaint data, and the status information includes the location information of the drone and the signal strength of the drone; determine a first potential field pointing to the target location based on the target location and the location information; determine a second potential field pointing to the business demand point based on the business demand point data; determine a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area; generate a composite potential field based on the first potential field, the second potential field, and the third potential field, and determine the flight path of the drone based on the composite potential field.

[0014] A computer program product includes a computer program that, when executed by a processor, performs the following: acquiring a target location corresponding to a path planning task, at least one business demand point data, and status information of a drone performing the path planning task, wherein the business demand point is determined based on customer complaint data, and the status information includes the drone's location information and the drone's signal strength; determining a first potential field pointing towards the target location based on the target location and the location information; determining a second potential field pointing towards the business demand point based on the business demand point data; determining a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area; generating a composite potential field based on the first potential field, the second potential field, and the third potential field, and determining the drone's flight path based on the composite potential field.

[0015] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects: Using the path planning method provided in this application embodiment, when performing UAV path planning, the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the UAV executing the path planning task can be obtained. Based on the target location and the location information, a first potential field pointing to the target location is determined; based on the business requirement point data, a second potential field pointing to the business requirement point is determined; and based on the signal strength, a third potential field is determined. Finally, based on the first potential field, the second potential field, and the third potential field, a composite potential field is generated, and based on the composite potential field, the flight path of the UAV is determined. The path planning method provided in this application has two main aspects. First, while acquiring the target location corresponding to the path planning task, it also acquires at least one business demand point data determined based on customer complaint data. Then, based on the business demand point data, a second potential field pointing towards the business demand point is determined. This allows the UAV to be attracted by the gravitational pull of the business demand point as it flies towards the target location, actively approaching key business areas such as customer complaint hotspots for signal acquisition. Compared to existing technologies that rely solely on the gravitational field of a single target point, this invention integrates business demands into the path planning in the form of a potential field, ensuring that the test path can dynamically cover high-priority business areas and significantly improving the targeting and effectiveness of aerial test data acquisition. Second, by acquiring the UAV's signal strength (e.g., GPS signal strength) and determining a third potential field based on the signal strength, when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area. This allows the UAV to feel the repulsive force away from the weak signal area before entering it or just as it enters the boundary of the weak signal area, thereby actively adjusting its flight path to avoid risks. Compared to the passive or even non-responsive approach to dynamic risks (such as signal attenuation areas) in existing technologies, this invention achieves predictive proactive avoidance based on real-time signal feedback, effectively reducing safety risks such as drone crashes caused by GPS signal loss. Finally, by generating a composite potential field from the first, second, and third potential fields, and determining the drone's flight path based on the composite potential field, the resultant force direction of this composite potential field is the vector superposition of the target point's gravity, the business requirement point's gravity, and the repulsive force of the weak signal area. Compared to the path planning methods based on the single target point's gravity in existing technologies, this invention improves the effectiveness and safety of the mission without sacrificing flight efficiency, demonstrating a significant multi-objective collaborative optimization effect. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1This is a schematic diagram illustrating a specific process of a path planning method provided in an embodiment of this application; Figure 2 A schematic diagram of the specific structure of a path planning device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the specific structure of a path planning device provided in an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] This application provides a path planning method to address the problems of insufficient coverage of service demand points and lack of proactive avoidance capability for weak signal areas in existing UAV signal aerial survey path planning.

[0019] To facilitate understanding of the embodiments of this application, the terminology involved in the embodiments of this application will be briefly explained below.

[0020] Dynamic Weighted Artificial Potential Field (DW-APF): A path planning method that combines traditional artificial potential fields, gravitational fields of business demand points, and repulsive fields of safety constraint points. By dynamically adjusting the weights of demand points and the repulsive gains of constraint points, it enables intelligent path optimization for UAVs in complex environments.

[0021] Business Requirement Point (BRP): refers to the areas or target points that need to be prioritized for coverage in path planning, such as customer complaint hotspots. Its weight is dynamically adjusted according to the frequency of complaints, and the range of gravitational influence is controlled by an exponential decay function to guide drones to prioritize coverage of high-value areas.

[0022] Safety Constraint Point (SCP): This refers to dangerous areas that need to be avoided during flight, such as areas with weak GPS signals. Sensors detect signal strength in real time and trigger the generation of dynamic obstacles to ensure that the drone avoids the risk of navigation failure.

[0023] Repulsion gain: This describes the strength of the repulsion force exerted by the safety constraint point on the drone. Its value is inversely proportional to the GPS signal strength. The weaker the signal, the greater the repulsion gain, thus enhancing the drone's ability to avoid dangerous areas.

[0024] Dynamic gravitational field: A gravitational field composed of multiple business demand points, whose weights are dynamically adjusted according to the complaint density, and superimposed on the traditional artificial potential field to form a composite potential field in order to achieve dynamic optimization of the path.

[0025] Protection mechanisms include a GPS weak signal area detection module and a repulsion gain adjustment module. The former is used to detect GPS signal strength in real time and generate dynamic obstacles, while the latter dynamically adjusts the repulsion coefficient according to the signal strength to ensure the safe flight of the UAV in complex environments.

[0026] The execution subject of the path planning method provided in this application embodiment may be, but is not limited to, at least one of a path planning server, a mapping server, and a drone scheduling server; in addition, the execution subject of the method may also be the system or application (APP) itself running on these servers.

[0027] For ease of description, the following description uses a path planning system as the execution subject to illustrate the implementation of this method. It should be understood that using a path planning system as the execution subject is merely an illustrative example and should not be construed as a limitation of the method.

[0028] Based on the aforementioned path planning system, a schematic diagram illustrating the specific implementation process of the path planning method provided in this application is shown below. Figure 1 As shown, the main steps include the following: Step 11: Obtain the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the UAV executing the path planning task; Specifically, in this embodiment, before or during drone takeoff, the target location (i.e., the coordinates of the test endpoint) of a pre-set signal aerial test task is acquired. Simultaneously, at least one business demand point data is acquired, which can be determined based on customer complaint data. For example, recent user complaint records are extracted from the network operation and maintenance system, and the geographical location of the complaint is used as the business demand point, with each business demand point associated with its complaint frequency. Furthermore, real-time status information is acquired through the drone's onboard sensors. This status information includes the drone's location information, such as the drone's three-dimensional coordinates obtained through a GPS receiver, and the drone's signal strength. In one embodiment, this signal strength may refer to the drone's GPS signal strength.

[0029] Step 12: Based on the target location and location information obtained by executing step 11, determine the first potential field pointing to the target location; In this embodiment, the first potential field is the gravitational potential field in the traditional artificial potential field method. Assume the current position of the UAV is q = (x, y, z), and the target position is q0. goal = (x goal , y goal , z goal Then, the gravitational potential field can be determined according to the following formula [1]: [1] Among them, K att This is the gravitational gain coefficient, which controls the strength of the UAV's pull towards the target point; This represents the Euclidean distance between the target location and the current location of the UAV. The corresponding gravitational vector F att The negative gradient of the potential field function can be determined according to the following formula [2] in this embodiment: [2] The direction of this gravitational vector points from the drone's current position to the target position, and its magnitude is linearly positively correlated with the distance. As the drone approaches the target point, the gravitational force gradually decreases to zero.

[0030] Step 13: Determine the second potential field pointing to the business requirement point based on the business requirement point data; In this embodiment of the application, the path planning system can determine the second potential field based on the complaint location information and the current location information of the UAV; and determine the gravitational intensity of each business demand point in the second potential field based on the weight information corresponding to each business demand point.

[0031] Specifically, assume that there are n business needs identified based on customer complaint hotspots, and the position of the i-th business need is q. ci Its weight K Ci The value of K can be dynamically determined based on the frequency of customer complaints at this point; the higher the complaint frequency, the higher the K value. Ci The larger the value, the greater the potential field. In order to enable the UAV to be attracted to the vicinity of the complaint hotspot for signal collection during flight, in this embodiment of the application, the composite gravitational potential field generated by the business demand point is constructed as shown in the following formula [3]: [3] Here, σ is the attenuation coefficient of the gravitational field at the complaint point, used to control the range of gravitational influence. By adjusting the value of σ, the attenuation range of the gravitational field can be effectively controlled, avoiding unnecessary interference to path planning caused by complaint points that are too far away.

[0032] The negative gradient of the potential field is obtained by applying the following formula [4] to the i-th business demand point to the UAV: [4] The total gravitational force of the second potential field is the sum of the gravitational forces at each business demand point. This gravitational force points towards the corresponding business demand point and increases as the distance decreases.

[0033] Step 14: Determine the third potential field based on the signal strength; The third potential field is used to avoid weak signal areas, that is, areas where the GPS signal strength is lower than a preset threshold. In this embodiment, when the signal strength is lower than the preset signal strength threshold, the third potential field generates a repulsive force between the current position and the weak signal area, pointing away from the weak signal area.

[0034] Specifically, the path planning system can determine the third potential field by following these sub-steps: Sub-step 1401: Obtain the second location information of the UAV when the signal strength is less than a preset signal strength threshold; Specifically, the path planning system can monitor the drone's current GPS signal strength S in real time. gps(q) When S gps(q) Less than the preset signal strength threshold S threshold When the signal strength is -130dBm, record the current location of the drone as the center q of the weak signal area. gps .

[0035] Sub-step 1402: Based on the second location information, determine the weak signal area and the radius of influence of the weak signal area; With q gps Let ρ be the center, and set an influence radius. gps In the embodiments of this application, ρ gps It can be a preset fixed value (such as 50 meters), or it can be dynamically adjusted according to the degree of signal attenuation. For example, the weaker the signal, the higher the ρ value. gps The larger the value, the less likely it is to be misjudged.

[0036] Sub-step 1403: Determine the first distance between the current third position information of the UAV and the weak signal area; During subsequent flight, the drone's current position q and the center of the weak signal area q are calculated in real time. gps The Euclidean distance between them is d(q, q gps ) = ||q - q gps ||.

[0037] Sub-step 1404: When the first distance is less than the radius of influence, determine the third potential field based on the difference between the first distance and the radius of influence.

[0038] When d(q, q) gps )<ρ gps At this time, a repulsive potential field is triggered, as shown in the following formula [5]: [5] Among them, K gps This is the repulsion gain coefficient, used to control the intensity of the repulsion force.

[0039] Furthermore, this embodiment also includes adjusting the repulsive force gain coefficient based on the difference between the signal strength and a preset signal strength threshold, wherein the difference is positively correlated with the gain.

[0040] Specifically, in the embodiments of this application, K gps It is not a fixed value, but can be dynamically adjusted according to the current GPS signal strength according to the following formula [6]: [6] Among them, K base The repulsive force base gain coefficient. When S gps(q) Far lower than S threshold When the value inside the parentheses increases, K gps This increases the repulsive force, ensuring that the drone can quickly avoid areas with severe signal weakness.

[0041] Step 15: Generate a composite potential field based on the first, second, and third potential fields, and determine the flight path of the UAV based on the composite potential field.

[0042] In this embodiment of the application, the potential field vectors corresponding to the first potential field, the second potential field, and the third potential field can be vector-added according to the following formula [7] to generate a composite potential field: [7] The corresponding total resultant force vector is the sum of the component forces, as shown in the following formula [8]: [8] Furthermore, the path planning system can determine the resultant force vector, F, corresponding to the UAV based on the composite potential field. total The flight direction and speed of the UAV are determined based on the resultant force vector; the flight path is then determined based on the flight direction and speed.

[0043] Specifically, the desired flight direction of the drone is F. total The unit vector is shown in the following formula [9]: d desired = F total / ||F total || [9] The flight speed v can be set to be proportional to the magnitude of the resultant force, as shown in the following formula

[10] : v = min(v max k v ·||F total ||)

[10] Where, k v v is the proportionality coefficient. max To achieve the maximum safe flight speed. Furthermore, this can be determined based on the current position q(t) and the desired direction d. desired Given the velocity v, determine the position at the next moment. Repeat the above steps, continuously updating the state information and recalculating the potential fields and resultant forces, until the UAV reaches the target position.

[0044] Using the path planning method provided in this application embodiment, when performing UAV path planning, the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the UAV executing the path planning task can be obtained. Based on the target location and the location information, a first potential field pointing to the target location is determined; based on the business requirement point data, a second potential field pointing to the business requirement point is determined; and based on the signal strength, a third potential field is determined. Finally, based on the first potential field, the second potential field, and the third potential field, a composite potential field is generated, and based on the composite potential field, the flight path of the UAV is determined. The path planning method provided in this application has two main aspects. First, while acquiring the target location corresponding to the path planning task, it also acquires at least one business demand point data determined based on customer complaint data. Then, based on the business demand point data, a second potential field pointing towards the business demand point is determined. This allows the UAV to be attracted by the gravitational pull of the business demand point as it flies towards the target location, actively approaching key business areas such as customer complaint hotspots for signal acquisition. Compared to existing technologies that rely solely on the gravitational field of a single target point, this invention integrates business demands into the path planning in the form of a potential field, ensuring that the test path can dynamically cover high-priority business areas and significantly improving the targeting and effectiveness of aerial test data acquisition. Second, by acquiring the UAV's signal strength (e.g., GPS signal strength) and determining a third potential field based on the signal strength, when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area. This allows the UAV to feel the repulsive force away from the weak signal area before entering it or just as it enters the boundary of the weak signal area, thereby actively adjusting its flight path to avoid risks. Compared to the passive or even non-responsive approach to dynamic risks (such as signal attenuation areas) in existing technologies, this invention achieves predictive proactive avoidance based on real-time signal feedback, effectively reducing safety risks such as drone crashes caused by GPS signal loss. Finally, by generating a composite potential field from the first, second, and third potential fields, and determining the drone's flight path based on the composite potential field, the resultant force direction of this composite potential field is the vector superposition of the target point's gravity, the business requirement point's gravity, and the repulsive force of the weak signal area. Compared to the path planning methods based on the single target point's gravity in existing technologies, this invention improves the effectiveness and safety of the mission without sacrificing flight efficiency, demonstrating a significant multi-objective collaborative optimization effect.

[0045] In one embodiment, this application also provides a path planning device to address the problems of insufficient coverage of service demand points and lack of proactive avoidance capability for weak signal areas in existing UAV signal aerial survey path planning. A schematic diagram of the specific structure of the path planning device is shown below. Figure 2 As shown, it includes: a data acquisition unit 21, a potential field determination unit 22, and a path planning unit 23.

[0046] The data acquisition unit 21 is used to acquire the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the drone executing the path planning task. The business requirement point is determined based on customer complaint data, and the status information includes the location information of the drone and the signal strength of the drone. Potential field determination unit 22 is used to determine a first potential field pointing to the target position based on the target position and the position information; Potential field determination unit 22 is used to determine a second potential field pointing to the business demand point based on the business demand point data; Potential field determination unit 22 is used to determine a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal region between the current position and the weak signal region; The path planning unit 23 is used to generate a composite potential field based on the first potential field, the second potential field and the third potential field, and to determine the flight path of the UAV based on the composite potential field.

[0047] In one implementation, the business demand point data includes complaint location information corresponding to customer complaint data and weight information determined based on the frequency of customer complaints. Then, the potential field determination unit 22 is specifically used to: determine the second potential field based on the complaint location information and the current location information of the UAV; and determine the gravitational intensity corresponding to each business demand point in the second potential field based on the weight information corresponding to each business demand point.

[0048] In one embodiment, the potential field determination unit 22 is specifically configured to: acquire second position information of the UAV when the signal strength is less than the preset signal strength threshold; determine a weak signal region based on the second position information and determine the influence radius of the weak signal region; determine a first distance between the current third position information of the UAV and the weak signal region; when the first distance is less than the influence radius, determine the third potential field based on the difference between the first distance and the influence radius, wherein the third potential field generates a repulsive force pointing away from the weak signal region.

[0049] In one embodiment, the potential field determining unit 22 is further configured to: adjust the gain coefficient of the repulsive force according to the difference between the signal strength and the preset signal strength threshold, wherein the difference is positively correlated with the gain.

[0050] In one embodiment, the path planning unit 23 is specifically used to vector-add the potential field vectors corresponding to the first potential field, the second potential field, and the third potential field to generate the composite potential field.

[0051] In one embodiment, the path planning unit 23 is specifically used to: determine the resultant force vector corresponding to the UAV based on the composite potential field; determine the flight direction and flight speed of the UAV based on the resultant force vector; and determine the flight path based on the flight direction and the flight speed.

[0052] Using the path planning device provided in this application embodiment, when performing UAV path planning, it can acquire the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the UAV executing the path planning task. Based on the target location and the location information, it determines a first potential field pointing to the target location; based on the business requirement point data, it determines a second potential field pointing to the business requirement point; and based on the signal strength, it determines a third potential field. Finally, based on the first potential field, the second potential field, and the third potential field, it generates a composite potential field and determines the flight path of the UAV based on the composite potential field. The path planning device provided in this application has two advantages. First, while acquiring the target location corresponding to the path planning task, it also acquires at least one business demand point data determined based on customer complaint data. Then, based on the business demand point data, a second potential field pointing towards the business demand point is determined. This allows the UAV to be attracted by the gravitational force generated by the business demand point during its flight towards the target location, actively approaching key business areas such as customer complaint hotspots for signal acquisition. Compared to existing technologies that rely solely on the gravitational field of a single target point, this invention integrates business demands into path planning in the form of a potential field, ensuring that the test path can dynamically cover high-priority business areas and significantly improving the targeting and effectiveness of aerial test data acquisition. Second, by acquiring the UAV's signal strength (e.g., GPS signal strength) and determining a third potential field based on the signal strength, when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area. This allows the UAV to feel the repulsive force away from the weak signal area before entering or just entering the boundary of the weak signal area, thereby actively adjusting its flight path to avoid risks. Compared to the passive or even non-responsive approach to dynamic risks (such as signal attenuation areas) in existing technologies, this invention achieves predictive proactive avoidance based on real-time signal feedback, effectively reducing safety risks such as drone crashes caused by GPS signal loss. Finally, by generating a composite potential field from the first, second, and third potential fields, and determining the drone's flight path based on the composite potential field, the resultant force direction of this composite potential field is the vector superposition of the target point's gravity, the business requirement point's gravity, and the repulsive force of the weak signal area. Compared to the path planning methods based on the single target point's gravity in existing technologies, this invention improves the effectiveness and safety of the mission without sacrificing flight efficiency, demonstrating a significant multi-objective collaborative optimization effect.

[0053] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Please refer to it. Figure 3At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for other business operations.

[0054] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0055] Memory is used to store programs. Specifically, programs may include program code, which includes computer operation instructions. Memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0056] The processor reads the corresponding computer program from non-volatile memory into main memory and then runs it, forming a path planning mechanism at the logical level. The processor executes the program stored in memory and specifically performs the following operations: The system acquires the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the UAV executing the path planning task. The business requirement point is determined based on customer complaint data, and the status information includes the UAV's location information and signal strength. Based on the target location and the location information, a first potential field pointing towards the target location is determined. Based on the business requirement point data, a second potential field pointing towards the business requirement point is determined. Based on the signal strength, a third potential field is determined, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area. Based on the first, second, and third potential fields, a composite potential field is generated, and based on the composite potential field, the flight path of the UAV is determined.

[0057] The above is as stated in this application. Figure 3The path planning electronic device method disclosed in the illustrated embodiments can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0058] Of course, in addition to software implementation, the electronic device of this application does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0059] This application also proposes a computer-readable storage medium that stores one or more programs, the programs including instructions that, when executed by a portable electronic device including multiple applications, enable the portable electronic device to perform... Figure 1 The path planning method shown in the embodiment is specifically used to perform the following operations: The system acquires the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the UAV executing the path planning task. The business requirement point is determined based on customer complaint data, and the status information includes the UAV's location information and signal strength. Based on the target location and the location information, a first potential field pointing towards the target location is determined. Based on the business requirement point data, a second potential field pointing towards the business requirement point is determined. Based on the signal strength, a third potential field is determined, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal area between the current location and the weak signal area. Based on the first, second, and third potential fields, a composite potential field is generated, and based on the composite potential field, the flight path of the UAV is determined.

[0060] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0061] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0064] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0065] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0066] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0067] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0068] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0069] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A path planning method, characterized in that, include: The system acquires the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the drone executing the path planning task. The business requirement point is determined based on customer complaint data, and the status information includes the location information of the drone and the signal strength of the drone. Based on the target location and the location information, a first potential field pointing to the target location is determined; Based on the business requirement data, a second potential field pointing to the business requirement is determined; Based on the signal strength, a third potential field is determined, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal region between the current position and the weak signal region; A composite potential field is generated based on the first potential field, the second potential field, and the third potential field, and the flight path of the UAV is determined based on the composite potential field.

2. The method according to claim 1, characterized in that, The business demand data includes complaint location information corresponding to customer complaint data and weight information determined based on the frequency of customer complaints; The step of determining the second potential field pointing to the business requirement point based on the business requirement point data specifically includes: The second potential field is determined based on the complaint location information and the current location information of the drone; Based on the weight information corresponding to each of the aforementioned business demand points, the gravitational strength corresponding to each of the aforementioned business demand points in the second potential field is determined.

3. The method according to claim 1, characterized in that, The step of determining the third potential field based on the signal strength specifically includes: Obtain the second location information of the UAV when the signal strength is less than the preset signal strength threshold; Based on the second location information, the weak signal area is determined, and the radius of influence of the weak signal area is determined. Determine the first distance between the current third location information of the UAV and the weak signal area; When the first distance is less than the radius of influence, the third potential field is determined based on the difference between the first distance and the radius of influence, wherein the third potential field generates a repulsive force pointing away from the weak signal region.

4. The method according to claim 3, characterized in that, Also includes: The gain coefficient of the repulsive force is adjusted based on the difference between the signal strength and the preset signal strength threshold, wherein the difference is positively correlated with the gain.

5. The method according to claim 1, characterized in that, The step of generating a composite potential field based on the first potential field, the second potential field, and the third potential field specifically includes: The potential field vectors corresponding to the first potential field, the second potential field, and the third potential field are vector-added together to generate the composite potential field.

6. The method according to claim 1, characterized in that, Determining the flight path of the UAV based on the composite potential field specifically includes: Based on the composite potential field, determine the resultant force vector corresponding to the UAV; The flight direction and speed of the UAV are determined based on the resultant force vector; The flight path is determined based on the direction of travel and the flight speed.

7. A path planning device, characterized in that, include: The data acquisition unit is used to acquire the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the drone executing the path planning task. The business requirement point is determined based on customer complaint data, and the status information includes the location information of the drone and the signal strength of the drone. A potential field determination unit is used to determine a first potential field pointing to the target position based on the target position and the position information. The potential field determination unit is used to determine a second potential field pointing to the business demand point based on the business demand point data. A potential field determination unit is used to determine a third potential field based on the signal strength, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal region between the current position and the weak signal region; The path planning unit is used to generate a composite potential field based on the first potential field, the second potential field, and the third potential field, and to determine the flight path of the UAV based on the composite potential field.

8. A path planning device, comprising: processor; as well as A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the following operations: The system acquires the target location corresponding to the path planning task, at least one business requirement point data, and the status information of the drone executing the path planning task. The business requirement point is determined based on customer complaint data, and the status information includes the location information of the drone and the signal strength of the drone. Based on the target location and the location information, a first potential field pointing to the target location is determined; Based on the business requirement data, a second potential field pointing to the business requirement is determined; Based on the signal strength, a third potential field is determined, wherein when the signal strength is less than a preset signal strength threshold, the third potential field generates a repulsive force pointing away from the weak signal region between the current position and the weak signal region; A composite potential field is generated based on the first potential field, the second potential field, and the third potential field, and the flight path of the UAV is determined based on the composite potential field.

9. A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including a plurality of applications, cause the electronic device to perform the path planning method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the path planning method as described in any one of claims 1-6.

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