A method, system, device and storage medium for demonstrating unmanned aerial vehicles (UAVs)

Abstract

The application provides a UAV display method, system, device and storage medium, relates to the technical field of UAV cluster management, and the method comprises the following steps: determining the storage area of a target UAV according to the basic information of the target UAV; acquiring the first storage position and the first flight plan of a first UAV and the second storage position and the second flight plan of a second UAV which are stored in the storage area; determining the initial storage position of the target UAV in the storage area in combination with the first storage position and the second storage position; acquiring the target flight plan of the target UAV; and determining the target storage position of the target UAV from the initial storage position in combination with the first flight plan, the second flight plan and the target flight plan, and parking the target UAV at the target storage position. The application has the technical effect that the storage requirements among UAVs in different states are effectively coordinated.

Description

Technical Field

[0001] This application relates to the field of drone swarm management technology, specifically to a drone display method, system, device, and storage medium. Background Technology

[0002] With the rapid development and widespread application of drone technology, the scale of drone swarms is constantly expanding. How to efficiently manage the storage locations of multiple drones within a limited storage area and ensure that drones can perform tasks safely and orderly has become a key issue that urgently needs to be addressed in the current operation and management of drone swarms.

[0003] Existing technologies typically employ a fixed partitioning management approach, dividing the storage area into multiple independent parking zones, with each drone assigned to a pre-defined storage location based on its mission type. While this method can generally meet the storage needs of drones, its static storage management strategy cannot be adjusted in real time according to the dynamic operational characteristics of the drone swarm, resulting in an inflexible storage layout and an inability to effectively coordinate the storage needs of drones in different states. Summary of the Invention

[0004] This application provides a drone display method, system, device, and storage medium for effectively coordinating the storage needs of drones in different states.

[0005] In a first aspect, this application provides a method for demonstrating a drone, the method comprising: acquiring basic information of a target drone; determining a storage area for the target drone based on the basic information; acquiring a first storage location and a first flight plan of a first drone stored in the storage area, and a second storage location and a second flight plan of a second drone, wherein the first drone is in a standby state and parked at the first storage location, and the second drone is in a mission execution state and not parked at the second storage location; determining an initial storage location of the target drone in the storage area by combining the first storage location and the second storage location; acquiring a target flight plan of the target drone; determining a target storage location of the target drone from the initial storage location by combining the first flight plan, the second flight plan, and the target flight plan, and controlling the target drone to park at the target storage location.

[0006] By employing the aforementioned technical solution, a suitable storage area is determined by acquiring the basic information of the target UAV. Furthermore, by analyzing the storage locations and flight plans of UAVs in different states within the storage area, dynamic optimization of storage location allocation is achieved. This method specifically considers the location information of parked standby UAVs and mission-performing UAVs that have temporarily left but are scheduled to return, making comprehensive decisions based on the flight plans of each UAV. This ensures safe takeoff and landing of UAVs while improving the space utilization efficiency of the storage area. For example, by comprehensively considering the actual parking location of the first UAV and the expected storage needs of the second UAV upon its return, the system can select the optimal storage location for the target UAV, avoiding the storage space waste and takeoff / landing path conflicts inherent in traditional fixed-zone management methods, and effectively coordinating the storage needs of UAVs in different states.

[0007] Optionally, determining the initial storage location of the target UAV in the storage area by combining the first storage location and the second storage location includes: obtaining the topology of the storage area; calculating the free area of ​​the storage area based on the first coordinates of the first storage location in the topology and the second coordinates of the second storage location in the topology; selecting candidate locations that meet the size requirements of the target UAV from the free area based on preset storage priority rules and the free area; and determining the initial storage location of the target UAV in the storage area based on the path distance between the candidate locations and the entrance / exit of the storage area.

[0008] By employing the aforementioned technical solution, the system accurately calculates available storage areas by acquiring the topology of the storage region and combining it with the precise coordinates of already parked and reserved storage locations. By introducing storage priority rules to filter available areas, the system ensures that selected candidate locations not only meet the size requirements of the target UAV but also consider storage efficiency. Furthermore, by evaluating the path distance from candidate locations to the entrances and exits of the storage region, the system can select the optimal initial storage location, effectively reducing the UAV's ground taxiing distance and improving the access efficiency of the storage region. This location selection method based on topology and multi-dimensional constraints not only improves the utilization rate of storage space but also optimizes the UAV's entry and exit paths, reserving ample operational space for subsequent dynamic adjustments.

[0009] Optionally, determining the target storage location of the target UAV from the initial storage location by combining the first flight plan, the second flight plan, and the target flight plan includes: determining the storage location to be adjusted for the target UAV from the initial storage location by combining the first flight plan and the target flight plan; and determining the target storage location of the target UAV from the storage location to be adjusted according to the second flight plan.

[0010] By adopting the above technical solution and employing a two-stage storage location optimization strategy, the system first considers the correlation between the flight plans of the first parked UAV and the target UAV to determine the storage location to be adjusted. Then, further adjustments are made based on the flight plan of the second UAV currently performing a mission, ultimately determining the target storage location. This step-by-step optimization method enables the system to more accurately handle spatiotemporal conflicts between UAVs in different states. It ensures coordination with currently parked UAVs while also pre-considering the storage needs of UAVs returning from missions, thereby achieving precise allocation of storage locations and orderly coordination of multiple UAV takeoffs and landings.

[0011] Optionally, determining the target UAV's storage location to be adjusted from the initial storage location by combining the first flight plan and the target flight plan includes: obtaining a first flight path in the first flight plan; generating a target flight path for the target UAV to fly from multiple candidate storage locations according to the target flight plan, wherein the initial storage location includes multiple candidate storage locations, and different candidate storage locations correspond to different flight paths; removing the first candidate storage location from the multiple candidate storage locations to determine the target UAV's storage location to be adjusted, wherein the target flight path corresponding to the first candidate storage location conflicts with the first flight path.

[0012] By adopting the above technical solution, the system acquires the flight path of the first UAV and generates corresponding target flight paths for the target UAV at different candidate storage locations, thus achieving accurate identification and prevention of potential path conflicts. By analyzing the flight paths corresponding to different storage locations, the system can identify and eliminate candidate storage locations that may cause path conflicts in advance, thereby ensuring that the target UAV's storage location to be adjusted will not interfere with the flight paths of existing UAVs. This storage location optimization method based on flight path analysis not only avoids potential conflicts during multi-UAV operation in advance but also ensures the safe take-off and landing and efficient operation of UAV swarms, providing reliable path planning support for multi-UAV collaboration in complex environments.

[0013] Optionally, determining the target storage location of the target UAV from the storage locations to be adjusted according to the second flight plan includes: obtaining a second flight path in the second flight plan; removing a second candidate storage location from the storage locations to be adjusted to generate the target storage location of the target UAV, wherein the target flight path corresponding to the second candidate storage location conflicts with the storage path of the second flight path.

[0014] By adopting the above technical solution, the system further optimizes and filters the storage locations to be adjusted by analyzing the second flight path of the second UAV currently performing a mission. By identifying and eliminating storage locations that may conflict with the second flight path, the system ensures that the finally selected target storage location will not affect the second UAV's return flight path. This storage location optimization method, which considers the flight plan of the UAV performing the mission, prevents potential future path conflicts, ensuring the rationality of the current storage layout while reserving a safe return path for the UAV performing the mission, thereby improving the operational safety and scheduling efficiency of the entire storage area.

[0015] Optionally, after determining the target storage location of the target UAV from the initial storage location, the method further includes: obtaining the estimated flight energy consumption of the target UAV executing the target flight plan at the target storage location; and determining the final storage location of the target UAV at the target storage location based on the estimated flight energy consumption.

[0016] By employing the aforementioned technical solution, and calculating the estimated energy consumption of the target UAV during flight missions at the target storage location, further optimization of the storage location is achieved from an energy efficiency perspective. The system selects the final storage location based on the estimated flight energy consumption data, effectively reducing the energy consumption of the UAV during takeoff, landing, and mission execution. This energy consumption analysis-based storage location optimization method not only extends the effective operating time of the UAV but also reduces operating costs, providing crucial energy security for the long-term, efficient operation of UAV swarms. It is particularly suitable for application scenarios requiring frequent takeoffs and landings and long-term operation.

[0017] Optionally, after controlling the target drone to park at the target storage location, the method further includes: when a new drone is detected requesting to be stored in the storage area, obtaining the third flight plan of the new drone; and adjusting the target storage location based on the third flight plan to determine the final target storage location of the target drone.

[0018] By adopting the above technical solution, and by responding in real time to the storage requests of newly added UAVs and dynamically adjusting the existing storage layout in conjunction with their third flight plans, real-time optimization of storage locations is achieved. The system can reassess the storage location of target UAVs based on new constraints and make necessary adjustments, thereby ensuring that the storage area can adapt to the ever-changing storage needs of multiple UAVs. This dynamic adjustment mechanism not only improves the space utilization efficiency of the storage area but also enhances the system's responsiveness to sudden storage demands, providing reliable technical support for the flexible scheduling and safe operation of large-scale UAV swarms.

[0019] Secondly, this application provides a drone demonstration system, the system comprising: a first acquisition module, a second acquisition module, a first combination module, a third acquisition module, and a second combination module; wherein,

[0020] The first acquisition module is used to acquire basic information of the target drone and determine the storage area of ​​the target drone based on the basic information; the second acquisition module is used to acquire the first storage location and first flight plan of the first drone stored in the storage area, and the second storage location and second flight plan of the second drone, wherein the first drone is in a standby state and parked at the first storage location, and the second drone is in a mission execution state and not parked at the second storage location; the first combination module is used to combine the first storage location and the second storage location to determine the initial storage location of the target drone in the storage area; the third acquisition module is used to acquire the target flight plan of the target drone; the second combination module is used to combine the first flight plan, the second flight plan and the target flight plan to determine the target storage location of the target drone from the initial storage location, and control the target drone to park at the target storage location.

[0021] Thirdly, this application provides an electronic device that adopts the following technical solution: it includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to make the electronic device execute a computer program such as any of the above-described drone demonstration methods.

[0022] Fourthly, this application provides a computer-readable storage medium that stores a computer program capable of being loaded by a processor and executing any of the above-mentioned drone demonstration methods.

[0023] In summary, this application includes at least one of the following beneficial technical effects:

[0024] By acquiring basic information about the target drone, a suitable storage area is determined. Then, by analyzing the storage locations and flight plans of drones in different states within the storage area, dynamic optimization of storage location allocation is achieved. This method specifically considers the location information of parked standby drones and drones that have temporarily left but are scheduled to return for their missions. It combines this information with the flight plans of each drone to make comprehensive decisions, thereby improving the space utilization efficiency of the storage area while ensuring safe takeoff and landing of drones. For example, by comprehensively considering the actual parking location of the first drone and the expected storage needs of the second drone upon its return, the system can select the optimal storage location for the target drone, avoiding the problems of wasted storage space and conflicting takeoff and landing paths found in traditional fixed-zone management methods, and effectively coordinating the storage needs of drones in different states. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a drone demonstration method provided in an embodiment of this application;

[0026] Figure 2 This is a schematic diagram of the structure of a drone demonstration system provided in an embodiment of this application;

[0027] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0028] Explanation of reference numerals in the attached figures: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. Detailed Implementation

[0029] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0030] In the description of the embodiments in this application, words such as "illustrative," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "illustrative," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of words such as "illustrative," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0031] The applicable scenarios for this application include, but are not limited to, the following example: a large logistics park has multiple drone storage areas, each equipped with charging piles and an intelligent parking system. When a drone that has completed a remote inspection mission needs to be stored, the system first obtains basic information such as the drone's model and size, and determines the suitable storage area for it.

[0032] At this time, there are already two drones in the storage area: a Type A drone, which is waiting to charge at the charging station in the northeast corner for its next inspection mission, and a Type B drone, which has just been dispatched to perform an emergency supply delivery mission and has temporarily left its fixed parking position in the southwest corner. After obtaining the real-time topology information of the storage area, the system calculates the currently available free space and selects three candidate parking positions near the entrance and exit based on the principle of proximity.

[0033] Considering that the standby Type A drone was about to perform a patrol flight around the park, the system identified two candidate locations through path planning that might intersect with the takeoff path of Type A drone, and therefore eliminated these two locations. Simultaneously, the system analyzed the return route of the Type B drone during its mission, predicting that its return landing process would not interfere with the remaining candidate locations. Finally, the system comprehensively evaluated the charging facilities at the remaining candidate locations and the expected energy consumption of the drone's subsequent mission, selecting the optimal parking location and guiding the drone to a precise landing.

[0034] After the drones have finished parking, the system continues to monitor the drone scheduling status in the park in real time. When a new drone storage request is detected, it can quickly reassess and dynamically adjust the storage location to ensure that the storage management of multiple drones in the park is always in the optimal state.

[0035] Figure 1 This is a flowchart illustrating a drone demonstration method provided in an embodiment of this application. Figure 1 As shown, the method includes S101-S105:

[0036] S101: Obtain basic information about the target drone and determine its storage area based on the basic information.

[0037] In a specific embodiment, after receiving a new target drone access request, the drone display system first needs to obtain the basic information of the target drone. This basic information includes, but is not limited to: the drone's dimensions (length, width, height), weight, model, maximum takeoff weight, maximum payload, energy type (e.g., lithium battery, fuel), mission type (e.g., transportation, inspection, rescue), and estimated parking duration. This basic information is crucial for determining a suitable storage area.

[0038] Based on the acquired basic information, the system determines the storage area for the target drone using preset matching rules. Specifically, the preset matching rules include multiple admission criteria for storage areas, each corresponding to a different combination of basic drone information features. For example, for large transport drones, the system will match storage areas with sufficient space and load-bearing capacity; for drones performing emergency rescue missions, the system will prioritize matching fast-response storage areas near entrances and exits; for drones requiring long-term storage, the system will match storage areas with charging or refueling facilities.

[0039] The system compares the basic information of the target drone with the admission criteria of each storage area. When the matching degree between the admission criteria of a storage area and the basic information features of the target drone reaches a preset threshold, the storage area is determined as the storage area for the target drone. If there are multiple storage areas that meet the criteria, the system will select the most suitable storage area according to preset priority rules (such as the nearest principle, the optimal resource utilization principle, etc.).

[0040] S102, obtain the first storage location and first flight plan of the first UAV stored in the storage area, and the second storage location and second flight plan of the second UAV, wherein the first UAV is in standby state and parked in the first storage location, and the second UAV is in mission execution state and not parked in the second storage location.

[0041] After determining the storage area for the target drone, the system needs to obtain the status information of existing drones within that storage area to rationally plan the storage location of the target drone. The system mainly focuses on two types of drones: the first drone in a standby state and the second drone in a mission execution state. The standby state refers to the drone currently parked in the storage area and awaiting a mission, indicating that the first drone has been assigned a specific mission and will execute it according to the first flight plan; the mission execution state refers to the drone currently performing a flight mission and temporarily detached from the storage area.

[0042] Specifically, the system first acquires the first storage location and the first flight plan of the first UAV. The first storage location is represented by the coordinate system of the storage area, including specific spatial coordinate information (such as X, Y, and Z axis coordinate values) and the storage unit number. The first flight plan contains the definite mission information that the UAV will perform, such as the planned takeoff time, the expected flight path, and the mission duration. Since the first UAV is in a standby state and its specific flight plan has been determined, its takeoff time and flight path are fixed. This information has a significant impact on subsequent storage location planning, as it is necessary to ensure that the storage location of newly added UAVs will not affect the first UAV's planned takeoff and mission execution.

[0043] Simultaneously, the system also needs to obtain the second storage location and second flight plan of the second drone. Although the second drone is not currently parked at the second storage location, its estimated return time and second storage location information are equally important for planning the storage location of the target drone. The return time, landing path, and other information contained in the second flight plan will directly affect the allocation of spatial resources in the storage area.

[0044] Based on the above embodiments, as an optional implementation, in S102, determining the initial storage location of the target UAV in the storage area by combining the first storage location and the second storage location specifically includes S21-S24:

[0045] S21, obtain the topology of the storage area.

[0046] The first step is to obtain the topology of the storage area, which is a digital model containing information such as spatial layout, obstacle distribution, and channel connections. The topology is represented using a three-dimensional coordinate system, which can accurately describe the spatial attributes and accessibility characteristics of each location within the storage area.

[0047] S22, calculate the free area of ​​the storage region based on the first coordinate of the first storage location in the topology and the second coordinate of the second storage location in the topology.

[0048] After acquiring the topology, the system needs to determine the actual available free areas. By reading the first coordinates of the first storage location and the second coordinates of the second storage location, the system can mark occupied or reserved spaces in the topology. The first coordinate represents the current location of the first UAV, and the second coordinate is the reserved return location coordinate for the second UAV currently performing a mission. The system marks these coordinate points and their surrounding necessary safety buffer zones as occupied areas; the remaining areas are the available free areas. The calculation of free areas needs to consider the movement space requirements of the UAVs, ensuring that each potential storage location has sufficient operational space.

[0049] S23, based on preset storage priority rules and free areas, selects candidate locations from the free areas that meet the size requirements of the target UAV.

[0050] After identifying available areas, the system evaluates and filters these areas according to preset storage priority rules. These rules are a set of standards for evaluating the suitability of storage locations, including multiple evaluation dimensions such as location accessibility, space utilization efficiency, and maintenance convenience. The system matches the target UAV's size parameters with the available areas, filtering out candidate locations that meet the size requirements. For example, if the target UAV's unfolded dimensions are 3 meters × 3 meters, the effective space of the candidate locations needs to consider additional operational margins, potentially requiring an actual space of 4 meters × 4 meters.

[0051] S24. Determine the initial storage location of the target UAV in the storage area based on the path distance between the candidate location and the entrance / exit of the storage area.

[0052] Finally, the system determines the final initial storage location by calculating the path distance from each candidate location to the entrance / exit of the storage area. The path distance is calculated using the distance of actual feasible passageways, rather than a simple straight-line distance. The system considers constraints such as passageway width and turning radius to generate the optimal path from each candidate location to the entrance / exit and calculates the corresponding path length. For example, a candidate location may be relatively close in a straight line, but if it requires multiple turns to reach the entrance / exit, its actual path distance may be longer. The system ultimately selects the candidate location with the shortest path distance that also satisfies other constraints as the initial storage location.

[0053] S103, combining the first storage location and the second storage location, determine the initial storage location of the target UAV in the storage area.

[0054] After obtaining the storage location information of the first and second UAVs, the system needs to determine the initial storage location for the target UAV. The purpose of this step is to find the most suitable location for the target UAV while ensuring the rational use of storage space resources. The initial storage location refers to a temporary storage location determined solely based on spatial layout, without considering the impact of flight plans.

[0055] Specifically, the system first acquires the topology of the storage area, which includes spatial information such as the planar layout, obstacle distribution, and channel width. The system marks the first and second storage locations in the topology as occupied areas, with the first location being actually occupied (because the first drone is currently parked there) and the second location reserved (because the second drone will return to that location). By calculating the remaining space in the topology after removing the occupied areas, the system can obtain the free areas of the storage area.

[0056] The system evaluates available areas based on preset storage priority rules. These rules include multiple evaluation criteria, such as space utilization (prioritizing locations that maximize space utilization), accessibility (ensuring easy access for drones), and safe distance (maintaining sufficient safe distance from other drones). The system matches the target drone's size requirements with available areas, filtering out candidate locations that meet the size requirements.

[0057] After determining the candidate locations, the system calculates the path distance from each candidate location to the entrance / exit of the storage area. The path distance includes not only the straight-line distance but also the length of the actual travel path, as the drone needs to follow preset traffic rules when entering and exiting the storage area. The system sorts the candidate locations based on the path distance and selects the optimal location as the initial storage location for the target drone.

[0058] S104, Obtain the target flight plan of the target UAV.

[0059] Specifically, the target flight plan mainly includes information such as the planned takeoff time, estimated execution duration, flight path planning, and mission type. Among them, the planned takeoff time indicates the initial time period during which the target UAV needs to be parked in the storage area; the estimated execution duration determines the approximate time for the UAV to return to the storage area; the flight path planning includes a complete airspace usage plan, including the climb path during takeoff, the activity range of the mission area, and the landing path during the return phase; the mission type determines the specific operational requirements during the UAV's takeoff and landing process, such as cargo UAVs needing to reserve space for loading and unloading cargo, and reconnaissance UAVs needing a specific takeoff angle, etc.

[0060] In the specific process of acquiring the target flight plan, the system first interacts with the mission scheduling center to obtain the mission information assigned to the target UAV. Next, the system automatically generates a standardized flight plan data structure based on the mission information. This data structure integrates time information, spatial information, and mission requirements to form a standardized data format suitable for subsequent analysis. Simultaneously, the system also needs to verify the feasibility of the target flight plan, ensuring that all parameters in the plan meet the performance limitations of the UAV and airspace management requirements.

[0061] S105, combining the first flight plan, the second flight plan and the target flight plan, determines the target storage location of the target UAV from the initial storage location, and controls the target UAV to park at the target storage location.

[0062] The system first compares and analyzes the target UAV's flight plan with the first UAV's flight plan in both time and space. Since the first UAV is in a standby state and about to execute a mission, its flight plan has a higher priority. The system generates multiple candidate storage locations based on the initial storage location and simulates the target UAV's takeoff and landing trajectory for each candidate location. If the target flight path corresponding to a candidate storage location intersects or overlaps with the first flight path in time and space, the system marks that location as a path conflict location and removes it from the candidate set. Through this round of filtering, the system obtains a set of storage locations to be adjusted after the first round of adjustments.

[0063] Next, the system matches the storage location to be adjusted with the second flight plan of the second UAV. Although the second UAV is currently performing a mission, its return landing path also needs to be taken into consideration. The system further analyzes whether each storage location to be adjusted will affect the return operation of the second UAV. If there is a potential conflict, the corresponding storage location will be eliminated. For example, if the expected takeoff time of the target UAV is close to the return time of the second UAV, and their flight paths intersect, then this storage location is not suitable as the final target storage location.

[0064] After the two rounds of optimization and screening, the system selects the optimal location from the remaining candidate locations as the target storage location. The selection criteria include multiple factors such as the safe distance from other drones, the availability of take-off and landing channels, and the impact on the overall passage efficiency of the storage area. After determining the target storage location, the system initiates an automatic scheduling program, using a precise navigation and positioning system to control the target drone to move to the target storage location according to a preset path and complete parking.

[0065] Based on the above embodiments, as an optional implementation, in S105, determining the target storage location of the target UAV from the initial storage location by combining the first flight plan, the second flight plan, and the target flight plan specifically includes S51-S52:

[0066] S51, combining the first flight plan and the target flight plan, determines the target UAV's storage location to be adjusted from the initial storage location.

[0067] In the first phase of optimization, the system focuses on the coordination between the initial storage location and the operation of the first UAV. Since the first UAV is in a standby state and has a defined initial flight plan, its takeoff time and flight path are known, providing clear constraints for location optimization. The system first extracts key spatiotemporal information from the initial flight plan, including takeoff time, climb path, and mission airspace. Simultaneously, the system analyzes relevant information in the target flight plan, assessing the overlap between the two flight plans in time and space. If the initial storage location would cause the target UAV's takeoff and landing trajectory to conflict with the initial flight plan, the system generates multiple alternative locations around the initial storage location and verifies the feasibility of each alternative location using a path planning algorithm. After this round of optimization and selection, the system selects a set of locations that will not conflict with the initial flight plan and identifies them as the storage locations to be adjusted.

[0068] Based on the above embodiments, as an optional implementation, in S51, determining the target UAV's storage location to be adjusted from the initial storage location by combining the first flight plan and the target flight plan specifically includes S511-S513:

[0069] S511, Obtain the first flight path in the first flight plan.

[0070] First, the system needs to obtain the first flight path from the first flight plan. The first flight path is the complete flight trajectory of the first UAV from its current storage location to the completion of the mission, including the climb path during takeoff, the flight path during mission execution, and the landing path during the return phase. The system converts this path information into standard four-dimensional trajectory data (three-dimensional spatial coordinates plus a time dimension) for subsequent accurate path conflict analysis. For example, the first flight path may include detailed trajectory information of vertically climbing from the storage location to an altitude of 50 meters and then flying towards the mission area according to a preset flight path.

[0071] S512 generates the target flight path of the target UAV from multiple candidate storage locations according to the target flight plan. The initial storage location includes multiple candidate storage locations, and different candidate storage locations correspond to different flight paths.

[0072] Next, based on the target flight plan, the system generates a corresponding target flight path for each candidate storage location. A candidate storage location refers to a set of optional locations around the initial storage location that meet the basic storage conditions. The system plans takeoff and landing paths for each candidate storage location, taking into account the UAV's performance parameters (such as maximum rate of climb, turning radius, etc.) and airspace restrictions. Because each candidate storage location has a different spatial position, its corresponding takeoff and landing trajectories will also differ. For example, a candidate location located at the edge of the storage area may require a more complex takeoff path to join the main flight path, while a candidate location closer to the main passage may have a more direct takeoff path.

[0073] S513, the first candidate storage location is eliminated from multiple candidate storage locations to determine the target UAV's storage location to be adjusted. The target flight path corresponding to the first candidate storage location has a path conflict with the first flight path.

[0074] After generating all possible target flight paths, the system performs path conflict detection. Path conflict refers to the situation where the flight trajectories of different UAVs overlap or are too close in time and space. The system compares the target flight path corresponding to each candidate storage location with the first flight path to check for potential conflict points. If it finds that the target flight path corresponding to a certain candidate storage location (i.e., the first candidate storage location) intersects, overlaps, or has insufficient safety distance with the first flight path, the system marks that location as a conflict location and removes it from the candidate set.

[0075] For example, in a certain storage area, the system generates five candidate storage locations for the target drone. Path analysis reveals that the takeoff paths of two of these locations (the first candidate storage locations) intersect with the flight path of the first drone at an altitude of 100 meters within a specific time period. In this case, even slight adjustments to the flight time cannot completely eliminate the safety hazard. Therefore, the system eliminates these two locations and identifies the remaining three locations that will not cause path conflicts as the storage locations to be adjusted.

[0076] S52, according to the second flight plan, determines the target storage location of the target UAV from the storage locations to be adjusted.

[0077] In the second phase of optimization, the system matches the storage locations to be adjusted with the second flight plan of the second UAV. Although the second UAV is not currently within the storage area, its return landing process still requires sufficient space and time. The system extracts return information from the second flight plan, focusing on the expected return time and landing path. For each storage location to be adjusted, the system simulates the spatiotemporal relationship between the target UAV's takeoff and landing at that location and the second UAV's return process. If a storage location to be adjusted might affect the normal return of the second UAV, or if the activity spaces of the two UAVs overlap within a specific time period, that location will be eliminated. After this round of screening, the system selects the optimal location from the remaining storage locations to be adjusted as the final target storage location.

[0078] Based on the above embodiments, as an optional implementation, in S52, determining the target storage location of the target UAV from the storage locations to be adjusted according to the second flight plan specifically includes S521-S522:

[0079] S521, Obtain the second flight path in the second flight plan.

[0080] S522, the second candidate storage location is removed from the storage locations to be adjusted, and the target storage location of the target UAV is generated. The target flight path corresponding to the second candidate storage location conflicts with the storage path of the second flight path.

[0081] The system first needs to acquire the second flight path from the second flight plan. The second flight path mainly includes the complete flight trajectory of the second UAV from the mission area back to the storage area, especially the landing path after entering the storage area airspace. The system converts the second flight path into standard four-dimensional trajectory data, including spatial coordinates and time information. For example, the second flight path might show that the second UAV will enter the airspace above the storage area from the northeast at a specific altitude at a predetermined time, then gradually descend along a pre-set circling corridor, and finally land at the second storage location.

[0082] After acquiring the second flight path, the system needs to analyze the spatiotemporal relationship between the target flight path and the second flight path for each storage location to be adjusted. The system focuses on two types of potential conflicts: spatial conflicts, i.e., whether the take-off and landing path of the target UAV will intersect or be too close to the return path of the second UAV in space; and temporal conflicts, i.e., whether the two UAVs will use the same or adjacent airspace within the same time period. If any of the above conflicts are found between the target flight path and the second flight path corresponding to a storage location to be adjusted (i.e., the second candidate storage location), the location will be marked by the system and removed from the set of storage locations to be adjusted.

[0083] For example, in a scenario, a second drone plans to return at 10:00 AM and needs to use the main landing ramp on the west side of the storage area. System analysis reveals that while two alternative storage locations on the west side (second candidate storage locations) meet the coordination requirements with the first drone, if the target drone takes off at 9:30 AM, its climb path will intersect with the second drone's landing path at an altitude of 80 meters. Considering flight safety margin requirements, the system eliminates these two storage locations. Ultimately, the system selects an alternative storage location on the east side, which can use an independent takeoff and landing ramp, as the target storage location.

[0084] After determining the target storage location of the target UAV from the initial storage location, the specific steps also include S106-S107:

[0085] S106, Obtain the estimated flight energy consumption of the target UAV when executing the target flight plan at the target storage location.

[0086] S107, based on the expected flight energy consumption, determine the final storage location of the target UAV within the target storage location.

[0087] After determining the target storage location, the system also needs to perform a final optimization of the storage location from an energy efficiency perspective. This optimization process mainly considers the energy consumption of the target UAV when executing the target flight plan, to ensure that the selected storage location can support the UAV's efficient operation to the greatest extent. Expected flight energy consumption refers to the total amount of energy that the UAV is expected to consume throughout the entire process from takeoff to returning home after completing the mission. This indicator directly affects the UAV's endurance and mission execution efficiency.

[0088] The system first needs to obtain the estimated flight energy consumption of the target UAV when executing its flight plan at the target storage location. Energy consumption calculation needs to consider multiple factors, including climb energy consumption during takeoff, level flight energy consumption during cruise, maneuver energy consumption during mission execution, and energy consumption during return landing. The system establishes an accurate energy consumption prediction model based on the target UAV's performance parameters (such as empty weight, payload, and engine efficiency) and environmental factors (such as wind speed, temperature, and air density). For example, if the target storage location is located at the edge of the storage area, it may require a longer taxi distance and more turning maneuvers to reach the main flight path, resulting in additional energy consumption.

[0089] After acquiring the projected flight energy consumption data, the system further optimizes the target storage location to determine the final storage location. The optimization process mainly considers the following aspects: First, the system analyzes the differences in takeoff and landing energy consumption corresponding to different storage locations. For example, some storage locations may require longer ground taxiing distances or more complex takeoff paths, both of which increase energy consumption. Second, the system evaluates the energy consumption of the flight path between the storage location and the mission area. If a storage location can provide a more direct flight path, it can significantly reduce energy consumption during flight.

[0090] After controlling the target drone to park at the target storage location, the process also includes S108-S109:

[0091] S108: When a new drone request is detected to be stored in the storage area, the third flight plan of the new drone is obtained.

[0092] When the system detects a storage request from a new drone, it first needs to obtain its third flight plan. The third flight plan contains complete mission information for the new drone, such as planned takeoff time, estimated mission duration, and flight path planning. This information is crucial for assessing the potential impact between the new drone and existing drones. For example, if the new drone plans to take off at 6:00 AM to perform an inspection mission, while the target drone plans to take off at 7:00 AM to perform a delivery mission, the system needs to assess airspace usage around these two times.

[0093] S109, based on the third flight plan, adjusts the target storage location and determines the final target storage location of the target UAV.

[0094] After acquiring the third flight plan, the system needs to dynamically adjust the storage location of the target UAV based on new constraints. The adjustment process mainly considers the following aspects: First, the system analyzes whether there are potential conflicts between the flight path in the third flight plan and the current storage location of the target UAV. If it is found that the target storage location may affect the normal take-off and landing of newly added UAVs, the system will generate multiple alternative adjustment schemes. Second, the system evaluates the impact of each adjustment scheme on the overall storage layout, including the impact on other parked UAVs and the efficiency of access to the storage area.

[0095] By comprehensively analyzing these factors, the system selects the optimal adjustment plan to determine the final target storage location of the drone. For example, in a drone operation center, when a new drone scheduled to perform an emergency medical transport mission requests entry into the storage area, the system detects that the drone needs to use the fast lane near the medical equipment loading area. After analysis, the system decides to relocate the target drone, which was originally parked near that area, to the other side of the storage area. This not only reserves the optimal take-off and landing path for the new drone but also ensures the normal execution of the target drone's mission.

[0096] Based on the above method, this application also discloses a drone demonstration system, such as... Figure 2 As shown, Figure 2 This is a schematic diagram of the structure of a drone demonstration system provided in an embodiment of this application. The system includes: a first acquisition module, a second acquisition module, a first combination module, a third acquisition module, and a second combination module; wherein,

[0097] The first acquisition module is used to acquire basic information of the target UAV and determine the storage area of ​​the target UAV based on the basic information; the second acquisition module is used to acquire the first storage location and first flight plan of the first UAV stored in the storage area, and the second storage location and second flight plan of the second UAV, wherein the first UAV is in a standby state and parked in the first storage location, and the second UAV is in a mission execution state and not parked in the second storage location; the first combination module is used to combine the first storage location and the second storage location to determine the initial storage location of the target UAV in the storage area; the third acquisition module is used to acquire the target flight plan of the target UAV; the second combination module is used to combine the first flight plan, the second flight plan and the target flight plan to determine the target storage location of the target UAV from the initial storage location, and control the target UAV to park in the target storage location.

[0098] It should be noted that the system provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0099] Please see Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, and at least one communication bus 1002.

[0100] The communication bus 1002 is used to realize the connection and communication between these components.

[0101] The user interface 1003 may include a display screen and a camera. Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0102] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0103] The processor 1001 may include one or more processing cores. The processor 1001 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and by calling data stored in the memory 1005. Optionally, the processor 1001 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 1001 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 1001 and may be implemented as a separate chip.

[0104] The memory 1005 may include random access memory (RAM) or read-only memory. Optionally, the memory 1005 may include a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 1005 may also be at least one storage device located remotely from the aforementioned processor 1001. Figure 3 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application for a drone demonstration method.

[0105] exist Figure 3 In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 1001 can be used to call an application stored in the memory 1005 for a drone demonstration method. When executed by one or more processors, the electronic device performs one or more of the methods described in the above embodiments.

[0106] An electronic device readable storage medium stores instructions that, when executed by one or more processors, cause the electronic device to perform one or more of the methods described in the above embodiments.

[0107] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0108] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some service interfaces; indirect couplings or communication connections between devices or units may be electrical or other forms.

[0110] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0111] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0112] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0113] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for drone demonstration, the method comprising: The method comprises: obtaining basic information of a target UAV, and determining a storage area of the target UAV according to the basic information; obtaining a first storage position and a first flight plan of a first UAV stored in the storage area, and a second storage position and a second flight plan of a second UAV, wherein the first UAV is in a standby state and is parked at the first storage position, and the second UAV is in a task execution state and is not parked at the second storage position; determining an initial storage position of the target UAV in the storage area in combination with the first storage position and the second storage position, comprising: obtaining a topological structure of the storage area; calculating an idle area of the storage area according to a first coordinate of the first storage position in the topological structure and a second coordinate of the second storage position in the topological structure; selecting a candidate position meeting a size requirement of the target UAV from the idle area based on a preset storage priority rule and the idle area; determining the initial storage position of the target UAV in the storage area according to a path distance between the candidate position and an entrance of the storage area; obtaining a target flight plan of the target UAV; determining a target storage position of the target UAV from the initial storage position in combination with the first flight plan, the second flight plan and the target flight plan, and controlling the target UAV to be parked at the target storage position.

2. The drone display method of claim 1, wherein, The method comprises: determining an adjusted storage position of the target UAV from the initial storage position in combination with the first flight plan and the target flight plan; determining the target storage position of the target UAV from the adjusted storage position according to the second flight plan.

3. The drone display method of claim 2, wherein, The method comprises: obtaining a first flight path in the first flight plan; generating a target flight path of the target UAV flying from a plurality of candidate storage positions according to the target flight plan, wherein the initial storage position comprises a plurality of candidate storage positions, and different candidate storage positions correspond to different flight paths; eliminating a first candidate storage position from the plurality of candidate storage positions to determine the adjusted storage position of the target UAV, wherein the target flight path corresponding to the first candidate storage position has a path conflict with the first flight path.

4. The drone display method of claim 3, wherein, The method comprises: obtaining a second flight path in the second flight plan; eliminating a second candidate storage position from the adjusted storage position to generate the target storage position of the target UAV, wherein the target flight path corresponding to the second candidate storage position has a storage path conflict with the second flight path.

5. The drone display method of claim 1, wherein, After determining the target storage location of the target UAV from the initial storage location, the method further includes: obtaining an estimated flight energy consumption of the target UAV in executing the target flight plan at the target storage location; and determining a final storage location of the target UAV in the target storage location according to the estimated flight energy consumption.

6. The drone display method of claim 1, wherein, After controlling the target UAV to be parked at the target storage location, the method further includes: obtaining a third flight plan of a newly added UAV when it is detected that the newly added UAV requests to be parked in the storage area; and determining a final target storage location of the target UAV by adjusting the target storage location based on the third flight plan.

7. A drone display system, comprising: The system includes a first obtaining module, a second obtaining module, a first combining module, a third obtaining module, and a second combining module. The first obtaining module is configured to obtain basic information of a target UAV and determine a storage area of the target UAV according to the basic information. The second obtaining module is configured to obtain a first storage location and a first flight plan of a first UAV stored in the storage area and a second storage location and a second flight plan of a second UAV, wherein the first UAV is in a standby state and is parked at the first storage location, and the second UAV is in a task execution state and is not parked at the second storage location. The first combining module is configured to combine the first storage location and the second storage location to determine an initial storage location of the target UAV in the storage area, including: obtaining a topological structure of the storage area; calculating an idle area of the storage area according to a first coordinate of the first storage location in the topological structure and a second coordinate of the second storage location in the topological structure; selecting a candidate location that meets a size requirement of the target UAV from the idle area based on a preset storage priority rule and the idle area; and determining the initial storage location of the target UAV in the storage area according to a path distance between the candidate location and an entrance of the storage area. The third obtaining module is configured to obtain a target flight plan of the target UAV. The second combining module is configured to combine the first flight plan, the second flight plan, and the target flight plan to determine a target storage location of the target UAV from the initial storage location and control the target UAV to be parked at the target storage location.

8. An electronic device, comprising: An electronic device includes a processor, a memory, a user interface, and a network interface. The memory is configured to store instructions. The user interface and the network interface are configured to communicate with other devices. The processor is configured to execute the instructions stored in the memory to cause the electronic device to perform the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, A computer program is stored and can be loaded and executed by a processor to perform the method of any one of claims 1-6. A computer program is stored and can be loaded and executed by a processor to perform the method of any one of claims 1-6.

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