Dynamic sequencing based uav swarm takeoff and landing control method and system

Abstract

The application relates to a dynamic sequencing-based unmanned aerial vehicle group landing control method, which comprises the following steps: acquiring power data and task urgency of unmanned aerial vehicles to be sequenced, determining priority coefficients of the unmanned aerial vehicles to be sequenced according to the power data and the task urgency, the unmanned aerial vehicles to be sequenced including unmanned aerial vehicles requesting landing in an approach and departure circle and unmanned aerial vehicles requesting taking off on the ground, constructing an approach and landing sequencing model with the minimum total weighted delay time as the target based on the priority coefficients and delay times of the unmanned aerial vehicles, solving the sequencing model by combining a sliding time window algorithm and a genetic algorithm to obtain a sequencing strategy, and instructing the unmanned aerial vehicles to execute approach or departure procedures based on the sequencing strategy. Through the application, the problem of low unmanned aerial vehicle approach and landing scheduling efficiency is solved, and the sequencing strategy is optimized according to the priority coefficients and the delay times. The double concentric circle layout of the approach and departure circle and the waiting circle realizes the orderly guidance of traffic flow and avoids the disordered flight of the approach unmanned aerial vehicles in the terminal area.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent control of unmanned aerial vehicles, and in particular to a method and system for take-off and landing control of a group of unmanned aerial vehicles based on dynamic sequencing. BACKGROUND

[0002] Currently, unmanned aerial vehicles have not been operated on a large scale, and there is no clear and unified take-off and landing procedure and scheduling rule for large-scale unmanned aerial vehicles. The core work of current sequencing of multiple unmanned aerial vehicles mainly uses a hash table for rapid time conflict detection. The system allocates a planned take-off and landing time for each unmanned aerial vehicle, and attempts to store this time as a "key" in the hash table. If the "key" already exists, it means that a time conflict has occurred. At this time, the system will solve the conflict according to a set of fixed, pre-set simple rules: for unmanned aerial vehicles to be taken off, their time will be postponed in order; for unmanned aerial vehicles to be landed, their time will be advanced. This process will be repeated until a conflict-free time point is found for the unmanned aerial vehicle. The ultimate goal is to efficiently eliminate direct conflicts in time sequencing and simplify complex logical judgments.

[0003] This binary (yes / no) judgment mechanism cannot achieve multi-objective optimization; secondly, this scheduling method is a passive adjustment, lacks prediction of future traffic flow, leads to inefficient scheduling, and is prone to cause chain delays; and the fixed scheduling rule of "postponing take-off and advancing landing" cannot adapt to complex dynamic environments and may cause safety risks.

[0004] Therefore, how to design an unmanned aerial vehicle take-off and landing procedure and efficiently and safely complete the take-off and landing of multiple unmanned aerial vehicles has become a key problem to be solved. SUMMARY

[0005] Embodiments of the present application provide a method and system for take-off and landing control of a group of unmanned aerial vehicles based on dynamic sequencing, an electronic device and a storage medium, to at least solve the problem of low efficiency of unmanned aerial vehicle take-off and landing scheduling in related technologies.

[0006] In a first aspect, embodiments of the present application provide a method for take-off and landing control of a group of unmanned aerial vehicles based on dynamic sequencing, which is applied to a system for take-off and landing control of a group of unmanned aerial vehicles based on dynamic sequencing, and the method comprises:

[0007] obtaining power data and task urgency of a to-be-sequenced unmanned aerial vehicle, determining a priority coefficient of the to-be-sequenced unmanned aerial vehicle according to the power data and the task urgency, the to-be-sequenced unmanned aerial vehicle including an unmanned aerial vehicle requesting landing in a take-off and landing circle and an unmanned aerial vehicle requesting take-off on the ground;

[0008] construct a take-off and landing sequencing model aiming at minimizing total weighted delay time based on the priority coefficient and delay time of the UAV, wherein the delay time is a time difference between actual take-off and landing time and predicted take-off and landing time, and constraint conditions of the take-off and landing sequencing model include approach and departure time interval constraint and approach and departure advance or delay time constraint;

[0009] Solve the sequencing model by combining sliding time window algorithm and genetic algorithm to obtain a target sequencing strategy, and instruct the UAV to perform approach and departure procedures based on the target sequencing strategy.

[0010] In some embodiments, the control airspace of the UAV group take-off and landing control system includes an approach and departure circle and a waiting circle, the planar area range of the approach and departure circle is greater than that of the waiting circle, the center projections of the approach and departure circle and the waiting circle coincide, and the waiting circle is located directly below the approach and departure circle,

[0011] The approach and departure circle is provided with approach and departure positions, the approach and departure positions include approach and departure points, and the maximum number of UAVs that can be accommodated in the approach and departure circle is equal to the number of approach and departure positions;

[0012] The waiting circle is provided with approach waiting points, the number of approach waiting points is less than the number of approach and departure positions, and a UAV requesting landing enters the approach and departure circle from an external public route to reach an approach and departure point to wait for sequencing.

[0013] In some embodiments, instructing the UAV to perform approach procedures based on the target sequencing strategy includes:

[0014] For a UAV requesting landing, instruct the UAV to fly along a preset route, descend from the approach and departure point, and enter a corresponding approach waiting point on the waiting circle in the order corresponding to the target sequencing strategy, and enter a waiting landing state;

[0015] Receive a landing request sent by a UAV on the waiting circle, and issue a landing permission to the UAV in the waiting circle based on the landing request, the target sequencing strategy, and the idle condition of the take-off and landing channel;

[0016] Instruct the UAV receiving the landing permission to complete landing through the take-off and landing channel and enter a ground parking position.

[0017] In some embodiments, instructing the UAV to perform departure procedures based on the target sequencing strategy includes:

[0018] For a UAV requesting take-off, receive a take-off request sent by a UAV on the ground, and issue a take-off permission to the UAV based on the take-off request, the target sequencing strategy, and the idle condition of the take-off and landing channel;

[0019] The UAVs indicating receiving take-off permission take off through the take-off and landing channel, enter the preset flight route, and reach the approach and departure point to join the external public flight route.

[0020] In some embodiments, the approach and departure advance or delay time constraint comprises:

[0021] The time difference between the actual approach time and the expected approach time of the UAV cannot exceed a first time difference threshold range, wherein the approach time is the time for the UAV to reach the approach and departure airspace through the approach and departure circle; and / or

[0022] The time difference between the actual departure time and the expected departure time of the UAV cannot exceed a second time difference threshold range, wherein the departure time is the time for the UAV to leave the approach and departure airspace through the approach and departure circle.

[0023] In some embodiments, the approach and departure time interval constraint comprises:

[0024] The time interval between the approach times or the departure times of the UAVs entering or leaving the same approach and departure point in sequence must be greater than a preset time interval, wherein the approach time is the time for the UAV to reach the approach and departure airspace through the approach and departure circle, and the departure time is the time for the UAV to leave the approach and departure airspace through the approach and departure circle.

[0025] In some embodiments, the constraint condition further comprises an interval constraint and an actual take-off and landing time constraint for the UAVs on a single take-off and landing flight route,

[0026] The interval constraint for the UAVs on the single take-off and landing flight route comprises: the time interval between the take-off times or the landing times of the UAVs taking off or landing in sequence on the single take-off and landing flight route must satisfy a single flight route interval model constraint.

[0027] The actual take-off and landing time constraint comprises: the actual take-off and landing time of each UAV is not earlier than the expected take-off and landing time.

[0028] In a second aspect, the embodiments of the present application provide a UAV group take-off and landing control system based on dynamic sequencing, which comprises:

[0029] A priority determination module is configured to acquire power data and task urgency of a UAV to be sequenced, and determine a priority coefficient of the UAV to be sequenced according to the power data and the task urgency, wherein the UAV to be sequenced comprises a UAV requesting landing in an approach and departure circle and a UAV requesting take-off on the ground.

[0030] The model construction module is configured to construct a take-off and landing sequencing model aiming at minimizing total weighted delay time based on the priority coefficient and delay time of the UAV, wherein the delay time is a time difference between actual take-off and landing time and predicted take-off and landing time, and constraint conditions of the take-off and landing sequencing model include approach and departure time interval constraint and approach and departure advance or delay time constraint.

[0031] The sequencing module is configured to solve the sequencing model by combining a sliding time window algorithm and a genetic algorithm to obtain a target sequencing strategy, and instruct the UAV to perform an approach / departure procedure based on the target sequencing strategy.

[0032] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the dynamic sequencing based UAV group take-off and landing control method according to the first aspect.

[0033] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program executable by a processor to implement the dynamic sequencing based UAV group take-off and landing control method according to the first aspect.

[0034] Compared with the related art, the dynamic sequencing based UAV group take-off and landing control method provided by the embodiment of the present application constructs a take-off and landing sequencing model according to a priority coefficient and delay time, solves a target sequencing strategy, and schedules the UAV based on the target sequencing strategy, thereby solving the problem of low take-off and landing scheduling efficiency of the UAV. Further, the approach and departure circle and the waiting circle separate the two key stages of "sequencing in progress" and "sequencing after take-off and landing execution" of the UAV requesting landing, the approach and departure circle focuses on processing sequencing of the UAV newly entering the airspace, and the waiting circle focuses on the UAVs whose sequencing has been determined, thereby preventing the unsequenced UAVs from being mixed with the sequenced UAVs in the same region, leading to confusion of scheduling instructions and potential conflict risks. BRIEF DESCRIPTION OF DRAWINGS

[0035] The accompanying drawings, which are included to provide a further understanding of the application and constitute a part of this application, illustrate certain illustrative embodiments of the application and together with the description serve to explain the application. In the drawings:

[0036] Figure 1 is a flowchart of the dynamic sequencing based UAV group take-off and landing control method according to an embodiment of the present application;

[0037] Figure 2 is a schematic diagram of a controlled airspace according to an embodiment of the present application;

[0038] Figure 3is an air space control overhead view according to an embodiment of the application;

[0039] Figure 4 is a sorting method schematic diagram combining a sliding time window algorithm and a genetic algorithm according to an embodiment of the application;

[0040] Figure 5 is a sorting method flow chart combining a sliding time window algorithm and a genetic algorithm according to an embodiment of the application;

[0041] Figure 6 is a take-off and landing point physical protection zone schematic diagram according to an embodiment of the application;

[0042] Figure 7 is a structure block diagram of a dynamic sorting based UAV group take-off and landing control system according to an embodiment of the application;

[0043] Figure 8 is an internal structure schematic diagram of an electronic device according to an embodiment of the application. DETAILED DESCRIPTION

[0044] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application is described and explained below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application.

[0045] Obviously, the accompanying drawings in the following description are only some examples or embodiments of the present application, and for those of ordinary skill in the art, the present application can be applied to other similar scenarios without creative labor on the basis of these drawings. In addition, it can be understood that although the efforts made in this development process can be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present application, some design, manufacture or production changes based on the technical content disclosed in the present application are only routine technical means and should not be understood as insufficient disclosure of the present application.

[0046] In the present application, "embodiment" means that the specific features, structures or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily mean the same embodiment, nor is it an independent or alternative embodiment to other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in the present application can be combined with other embodiments without conflict.

[0047] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0048] This embodiment provides a method for controlling the takeoff and landing of unmanned aerial vehicle (UAV) swarms based on dynamic sorting. Figure 1 This is a flowchart of a drone swarm takeoff and landing control method based on dynamic sorting according to an embodiment of this application, as shown below. Figure 1 As shown, the process includes the following steps:

[0049] Step S101: Obtain the battery data and mission urgency of the drones to be sorted. Based on the battery data and mission urgency, determine the priority coefficient of the drones to be sorted. The drones to be sorted include drones requesting to land within the entry / exit zone and drones requesting to take off on the ground.

[0050] Figure 2 This is a schematic diagram of a controlled airspace according to an embodiment of this application, such as... Figure 2 As shown, the controlled airspace consists of takeoff and landing channels and arrival / departure airspace. The arrival / departure circle and the holding circle are two virtual concentric circles whose central projections coincide with the center of the takeoff and landing area. The arrival / departure circle connects the airway airspace (external airspace) with the arrival / departure airspace, and the holding circle connects the arrival / departure airspace with the takeoff and landing channels. The arrival / departure point is located on the arrival / departure circle, and the holding point is located on the holding circle. The radii of the arrival / departure circle and the holding circle are R1 and R2, respectively, where R1 > R2.

[0051] In some embodiments, the control airspace of the UAV group take-off and landing control system includes an approach and departure circle and a waiting circle, the planar area of the approach and departure circle is larger than that of the waiting circle, the center projections of the approach and departure circle and the waiting circle coincide, and the waiting circle is located directly below the approach and departure circle,

[0052] The approach and departure circle is provided with approach and departure positions, the approach and departure positions include approach entry points and approach exit points, and the maximum number of UAVs that can be accommodated in the approach and departure circle is equal to the number of approach and departure positions;

[0053] The waiting circle is provided with approach waiting points, the number of approach waiting points is less than the number of approach and departure positions, and the UAVs requesting to land enter the approach and departure circle from an external public route to reach the approach entry points to wait for sequencing.

[0054] The approach and departure circle is provided with a plurality of approach entry points (a portal for UAVs to enter the terminal area) and departure points (an exit for UAVs to leave the terminal area). The approach and departure points and the waiting points are uniformly distributed on the approach and departure circle and the waiting circle at a minimum safety distance.

[0055] Figure 3 A plan view of the control airspace according to an embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, the approach UAVs enter the approach and departure circle from the air route airspace to wait for sequencing, and enter the waiting circle from the approach and departure circle according to the sequencing results. Figure 3

[0056] The double concentric circle layout realizes the orderly guidance of traffic flow through the clear "outer circle entry and inner circle waiting" process, and avoids the disordered flight of the approach UAVs in the terminal area. Vertical layering is the core of realizing safety isolation. It ensures that the UAVs in different stages (approach, waiting, take-off and landing) are completely separated in the vertical dimension, fundamentally eliminating the conflict risk caused by mixed heights.

[0057] The departure UAVs wait for take-off on the ground according to the sequencing results and the use of the take-off and landing channel.

[0058] In view of the problem of large airspace flow in the UAV take-off and landing field, the UAVs in the terminal area are divided into two different types of take-off and landing according to the final destination, U={u1,u2,...,u N N represents the total number of UAVs; the approach state is numbered as 0, the departure state is numbered as 1, and L i represents the current approach and departure state of the UAV i, L i ∈{0,1}.

[0059] The priority coefficient calculation formula of the UAV in the embodiment is as follows:

[0060]

[0061] Wherein, f​i is a priority coefficient, E i represents the percentage of consumed power of the UAV i, E i ∈ [0%, 100%]. Q i represents the urgency of the task currently performed by the UAV i, Q i ∈ {1, 2, 3}. Table 1 is a table of coefficients corresponding to the urgency of the task according to an embodiment of the application.

[0062] Table 1

[0063]

[0064] With reference back to Figure 1 After obtaining the priority coefficient of the UAV, step S102 is performed.

[0065] In step S102, a take-off and landing sequencing model with the minimum total weighted delay time as the target is constructed based on the priority coefficient and the delay time of the UAV, wherein the delay time is the time difference between the actual take-off and landing time and the predicted take-off and landing time, and the constraint conditions of the take-off and landing sequencing model include the interval constraint of the arrival and departure time and the constraint of the advance or delay time of the arrival and departure.

[0066] The objective function of the take-off and landing sequencing model is:

[0067]

[0068] wherein ATOT i and ETOT i represent the actual take-off / landing time and the predicted take-off / landing time of the UAV i.

[0069] In step S103, the sequencing model is solved by combining the sliding time window algorithm and the genetic algorithm to obtain a target sequencing strategy, and the UAV is instructed to enter the waiting circle to wait for the system to issue a take-off or landing permission based on the target sequencing strategy.

[0070] The sliding time window sequencing algorithm is a method of reordering the take-off and landing queue of the UAV by the minimum time interval constraint on the basis of the first come first served (FCFS). In this embodiment, the minimum delay time is taken as the target to find the optimal take-off and landing combination order of the UAV. Compared with the dynamic sequencing algorithm, the sliding time window algorithm only considers adjusting the take-off and landing order of the UAV within a fixed length window, thereby reducing the calculation complexity. In this embodiment, a sliding time window model is established, the number of aircraft w is selected as the initial window, the genetic algorithm is used to sequence the w aircraft in the window, then the window is moved back by a certain s steps, and the new window is sequenced until all the take-off and landing sequencing of the UAV is completed.

[0071] This invention combines a sliding time window algorithm with a genetic algorithm to improve computation speed and reduce the total takeoff and landing time of UAVs. Based on a genetic algorithm function library, selection, crossover, and mutation functions from the genetic algorithm are designed, and a sliding time window constraint is added to the constraints.

[0072] Figure 4 This is a schematic diagram of a sorting method combining a sliding time window algorithm and a genetic algorithm according to an embodiment of this application, as shown below. Figure 4 As shown, during execution, the sliding time window step size s and window size w are set. Genetic algorithm parameters are set, including the number of individuals in the initial population, crossover probability, mutation probability, and the maximum number of iterations per time window, to balance the algorithm's accuracy and running time. Figure 5 This is a flowchart of a sorting method combining a sliding time window algorithm and a genetic algorithm according to an embodiment of this application.

[0073] The individual fitness of this algorithm is calculated as: 1 / (the delay time of a single individual divided by the delay time of that individual in FCFS plus 1).

[0074] That is, the individual fitness function is:

[0075]

[0076] Where f(x) represents the drone delay time when using the traditional FCFS strategy.

[0077] Through the above steps, a takeoff and landing sequencing model is constructed based on priority coefficients and delay times. The target sequencing strategy is then obtained, and UAV takeoff and landing scheduling is performed based on this strategy, solving the problem of low efficiency in UAV takeoff and landing scheduling. Furthermore, the UAV takeoff and landing airspace is divided into an arrival / departure circle and a waiting circle, separating the two key stages of "sequencing" and "sequencing and awaiting takeoff / landing" for incoming UAVs. The arrival / departure circle focuses on processing the sequencing of newly entering UAVs, while the waiting circle focuses on UAVs with confirmed sequencing, preparing for the final takeoff and landing operations. This prevents unsequential UAVs from mixing with sequenced UAVs in the same area, avoiding scheduling command confusion and potential conflict risks.

[0078] To address the sequencing challenges under high-density traffic conditions, this embodiment proposes combining a sliding time window algorithm with a genetic algorithm for dynamic coordinated takeoff and landing sequencing of UAV swarms in vertical takeoff and landing (VTOL) environments. By integrating physical space design with access control of takeoff and landing airspaces, mutually exclusive access to critical controlled airspace resources is ensured. The sliding time window decomposes the complex global sequencing problem into a series of local optimization problems, ensuring foresight while controlling computational complexity. The genetic algorithm then efficiently searches for the optimal takeoff and landing sequence within each window, addressing multiple objective functions. This combined algorithm is the core of achieving efficient and intelligent scheduling.

[0079] In some embodiments, the approach-departure advance or delay time constraints include:

[0080] The time difference between the actual approach time and the expected approach time of the UAV cannot exceed a first time difference threshold range, wherein the approach time is the time for the UAV to arrive at the approach-departure airspace via the approach-departure circuit.

[0081] The time difference between the actual departure time and the expected departure time of the UAV cannot exceed a second time difference threshold range, wherein the departure time is the time for the UAV to leave the approach-departure airspace via the approach-departure circuit.

[0082] STA i and STD i respectively represent the actual approach time and the actual departure time of the UAV i in the approach-departure airspace, ETA i and ETD i respectively represent the expected approach time and the expected departure time in the approach-departure airspace.

[0083] The maximum advance time constraint for the UAV i, i.e., the approach-departure actual time cannot exceed the maximum advance time:

[0084]

[0085] wherein AAT max and ADT max respectively represent the maximum advance approach time and the maximum advance departure time of the UAV in the approach-departure airspace.

[0086] The maximum delay time constraint for the UAV i, i.e., its approach-departure actual time cannot exceed the maximum delay time:

[0087]

[0088] wherein DAT max and DDT max respectively represent the maximum delay approach time and the maximum delay departure time of the UAV in the approach-departure airspace.

[0089] In some embodiments, the approach-departure time interval constraints include:

[0090] The time interval between the approach time or the departure time of the UAVs entering or leaving the same approach-departure point in sequence should be greater than a preset time interval, wherein the approach time is the time for the UAV to arrive at the approach-departure airspace via the approach-departure circuit, and the departure time is the time for the UAV to leave the approach-departure airspace via the approach-departure circuit.

[0091] The safety time interval between the two UAVs in sequence should satisfy:

[0092]

[0093] θ ij denotes the safety time interval between the front and rear UAVs on the same take-off / landing route.d ij denotes the actual time interval between the front and rear UAVs on the same take-off / landing route, and the time interval between the front and rear UAVs in the actual problem should satisfy d ij ≥θ ij

[0094] In some embodiments, the constraint further includes an interval constraint of the UAVs on a single take-off / landing route and an actual take-off / landing time constraint.

[0095] The interval constraint of the UAVs on a single take-off / landing route includes: the UAVs taking off or landing in front of and behind each other on a single take-off / landing route, and the time interval of the take-off or landing time of the UAVs should satisfy the single-route interval model.

[0096] The interval requirement that the aircraft taking off in front of and behind each other on a single take-off / landing route should satisfy is as follows:

[0097]

[0098] wherein M is a positive integer large enough; P ij denotes the relative take-off order of the UAVs i and j, and if i is in front of j, then P ij =1, and otherwise equal to 0, P ij ∈{0,1}; L i denotes the current departure or arrival state of the UAV i, L i ∈{0,1}.

[0099] The actual take-off / landing time constraint includes: the actual take-off / landing time of each UAV is not earlier than the expected take-off / landing time.

[0100] To ensure that the actual take-off / landing time is not earlier than the expected take-off / landing time: ATOT i ≥ETOT i .

[0101] In addition, to ensure the effectiveness of the minimum sequence i, j, it should also satisfy:

[0102]

[0103] In some embodiments, the step S103 of instructing the UAV to enter the waiting circle to wait for the system to issue a take-off or landing permission based on the target sequencing strategy includes:

[0104] In step S1031, for the UAV requesting to land, the UAV is instructed to fly along the preset route, descend from the approach entry point, and enter the corresponding approach waiting point on the waiting circle, and enter the waiting landing state in the order corresponding to the target sequencing strategy.

[0105] Step S1032, receiving the unmanned aerial vehicle on the waiting circle sending landing request, based on the landing request, target sorting strategy and idle condition of the take-off and landing channel, the landing permission is issued to the unmanned aerial vehicle in the waiting circle.

[0106] Step S1033, instructing the unmanned aerial vehicle receiving the landing permission to complete the landing through the take-off and landing channel and enter the ground parking position.

[0107] The approach (landing) procedure of the unmanned aerial vehicle:

[0108] Step S201, the unmanned aerial vehicle flies from the external route to the terminal area, enters the control airspace at the pre-designated approach approach point on the approach-departure circle, and the system sorts the unmanned aerial vehicle on the approach approach point according to the sorting mechanism.

[0109] Step S202, according to the sorting result, the unmanned aerial vehicle flies along the preset route, descends from the approach-departure circle and enters the corresponding approach waiting point on the waiting circle, and enters the hovering or circling waiting state.

[0110] Step S203, the unmanned aerial vehicle at the waiting point applies for landing to the system.

[0111] Step S204, the system issues a landing permission to the unmanned aerial vehicle after confirming that the take-off and landing channel is available.

[0112] Step S205, the unmanned aerial vehicle obtaining the permission immediately descends from the waiting altitude layer and completes the landing through the take-off and landing channel.

[0113] It should be noted that one take-off point corresponds to multiple approach-departure positions (approach approach point and departure point), and each position is separated by a certain angle (such as at least 45 degrees) in space. This allows multiple routes of unmanned aerial vehicles to enter the terminal area in parallel without interference, greatly improving the traffic capacity of the entrance.

[0114] At the same time, the maximum number of unmanned aerial vehicles that can be accommodated in the entire approach-departure airspace is equal to the number of approach-departure positions, in order to prevent traffic congestion in the entrance area.

[0115] Receiving the landing permission and then landing ensures that the target parking apron and the narrow airspace directly above it are absolutely safe in the critical stage of the last landing, and no other unmanned aerial vehicle will mistakenly enter.

[0116] Step S1034, for the unmanned aerial vehicle requesting take-off, receiving the unmanned aerial vehicle on the ground sending take-off request, based on the take-off request, target sorting strategy and idle condition of the take-off and landing channel, the take-off permission is issued to the unmanned aerial vehicle.

[0117] Step S1035, the UAV indicating receiving the take-off permission takes off through the take-off and landing channel, enters the approach and departure circle along the preset flight route to reach the approach and departure point, and then merges into the external public flight route.

[0118] The departure (take-off) procedure is the reverse process of the approach procedure, and also follows strict steps and safety mechanisms:

[0119] Step S301, the UAV on the ground apron initiates a departure request, and the system sorts the UAVs requesting to depart according to a sorting mechanism.

[0120] Step S302, according to the sorting result, the UAV applies for take-off to the system.

[0121] Step S303, the system issues a take-off permission to the UAV after confirming that the take-off and landing channel is available.

[0122] Step S304, the UAV obtaining the permission passes through the take-off and landing channel to reach the designated departure point on the approach and departure circle, and then merges into the external public flight route through the departure point to complete the departure.

[0123] It should be noted that the approach UAVs and the departure UAVs are sorted together in the sorting process.

[0124] In this embodiment, there can be multiple take-off and landing channels in the take-off and landing area. The take-off permission and the landing permission for a single take-off and landing channel are exclusive, and the system will only issue one permission for one take-off and landing channel at any time, which means that only one UAV is allowed to use one take-off and landing channel at the same time. This mutual exclusion access mechanism based on logical locks realizes safe and conflict-free scheduling of critical channel resources with extremely low complexity.

[0125] To ensure the absolute safety of the entire take-off and landing procedure, in addition to the mechanisms embedded in the above processes, additional physical protection zones are designed.

[0126] Figure 6 is a schematic diagram of a take-off and landing point physical protection zone according to an embodiment of the present application, as shown in Figure 6 The take-off and landing point physical protection zone includes a surrounding protection area of the take-off and landing point and an upper protection area of the take-off and landing point.

[0127] The surrounding protection area of the take-off and landing point is a circular truncated cone-shaped obstacle-free area with the take-off and landing point as the center and upward opening. Optionally, the angle between the inner wall and the vertical line of the take-off and landing site center is 30 degrees. The surrounding protection area of the take-off and landing point ensures that the UAV has enough clearance when entering and exiting at low altitude, and will not collide with surrounding buildings or obstacles.

[0128] An overhead protection area is a cylindrical "no-fly zone" above the landing site at a certain distance (e.g., 20 meters). Its function is to prohibit any unrelated aircraft from flying directly above the landing site, avoiding the potential threat of high-altitude falling objects or aircraft failure to the landing area below.

[0129] The terminal area UAV group coordination (integrated sequencing) unifies the landing and take-off sequence of the UAVs through efficient scheduling, and allocates the landing and take-off time slots, so that the UAVs finally complete landing and take-off, improving the UAV operation efficiency and the utilization rate of the apron resources.

[0130] It should be noted that the steps shown in the above process or the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.

[0131] The embodiment also provides a UAV group landing control system based on dynamic sequencing, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the terms "module", "unit", "sub-unit" and the like can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware or a combination of software and hardware is also possible and is conceived.

[0132] Figure 7 is a structural block diagram of the UAV group landing control system based on dynamic sequencing according to the embodiment of the application, as shown in Figure 7 , the system comprises:

[0133] The priority determination module 71 is configured to obtain power data and task urgency of the UAVs to be sequenced, and determine a priority coefficient of the UAVs to be sequenced according to the power data and the task urgency, the UAVs to be sequenced including the UAVs requesting to land in the landing and taking-off circle and the UAVs requesting to take off on the ground.

[0134] The model construction module 72 is configured to construct a landing and taking-off sequencing model with the minimum total weighted delay time as the target based on the priority coefficient and the delay time of the UAVs, wherein the delay time is the time difference between the actual landing and taking-off time and the predicted landing and taking-off time, and the constraint conditions of the landing and taking-off sequencing model include the landing and taking-off time interval constraint and the landing and taking-off advance or delay time constraint.

[0135] The sequencing module 73 is configured to solve the sequencing model by combining the sliding time window algorithm and the genetic algorithm to obtain a target sequencing strategy, and instruct the UAVs to execute the approach / take-off procedure based on the target sequencing strategy.

[0136] In some embodiments, the controlled airspace of the UAV group take-off and landing control system includes a departure and arrival circle and a waiting circle, the planar area of the departure and arrival circle is larger than that of the waiting circle, the centers of the departure and arrival circle and the waiting circle are projected to coincide, and the waiting circle is located directly below the departure and arrival circle.

[0137] The departure and arrival circle is provided with departure and arrival positions, the departure and arrival positions include approach arrival positions and approach departure positions, and the number of UAVs that can be accommodated in the departure and arrival circle is equal to the number of the departure and arrival positions.

[0138] The waiting circle is provided with approach waiting positions, the number of the approach waiting positions is less than the number of the departure and arrival positions, and a UAV requesting landing enters the departure and arrival circle from an external public air route to reach the approach arrival positions to wait for sequencing.

[0139] In some embodiments, the model construction module 72 includes:

[0140] A landing waiting module configured to, for a UAV requesting landing, instruct the UAV to fly along a preset air route, descend from the approach arrival positions, and enter corresponding approach waiting positions on the waiting circle in a sequence corresponding to a target sequencing strategy, and enter a waiting landing state.

[0141] A landing permission module configured to receive a landing request sent by a UAV on the waiting circle, issue a landing permission to the UAVs in the waiting circle based on the landing request, a target sequencing strategy, and a free condition of a take-off and landing channel, and instruct a UAV receiving the landing permission to complete landing through the take-off and landing channel and enter a ground parking position.

[0142] In some embodiments, the model construction module 72 includes:

[0143] A take-off module configured to, for a UAV requesting take-off, receive a take-off request sent by a UAV on the ground, issue a take-off permission to the UAV based on the take-off request, a target sequencing strategy, and a free condition of a take-off and landing channel, and instruct a UAV receiving the take-off permission to take off through the take-off and landing channel and enter the departure and arrival circle to reach the approach departure positions and then join the external public air route.

[0144] In some embodiments, the departure and arrival advance or delay time constraint includes:

[0145] A time difference between an actual approach time of the UAV and a predicted approach time cannot exceed a first time difference threshold range, wherein the approach time is a time for the UAV to reach a departure and arrival airspace through the departure and arrival circle.

[0146] A time difference between an actual departure time of the UAV and a predicted departure time cannot exceed a second time difference threshold range, wherein the departure time is a time for the UAV to leave the departure and arrival airspace through the departure and arrival circle.

[0147] In some embodiments, the arrival-departure time interval constraint comprises:

[0148] The time interval between the arrival time or the departure time of the UAVs entering or leaving the same approach point in sequence needs to be greater than a preset time interval, wherein the arrival time is the time when the UAVs enter the arrival-departure airspace through the arrival-departure circle, and the departure time is the time when the UAVs leave the arrival-departure airspace through the arrival-departure circle.

[0149] In some embodiments, the constraint condition further comprises an interval constraint and an actual take-off and landing time constraint of the UAVs on a single take-off and landing route,

[0150] The interval constraint of the UAVs on a single take-off and landing route comprises: the time interval between the take-off or landing times of the UAVs taking off or landing in sequence on a single take-off and landing route needs to satisfy a single route interval model constraint.

[0151] The actual take-off and landing time constraint comprises: the actual take-off and landing time of each UAV is not earlier than the expected take-off and landing time.

[0152] Through the above system, a take-off and landing sequencing model is constructed according to the priority coefficient and the delay time, a target sequencing strategy is obtained by solving, and the UAVs are dispatched based on the target sequencing strategy, thereby solving the problem of low efficiency of UAV take-off and landing scheduling. Further, the UAV take-off and landing airspace is divided into an arrival-departure circle and a waiting circle, and the two key stages of “sequencing in progress” and “sequencing after execution of take-off and landing” of the arrival UAVs are separated, the arrival-departure circle focuses on processing the sequencing of the UAVs newly entering the airspace, and the waiting circle focuses on the UAVs whose sequencing has been determined, and prepares for the final take-off and landing operation, thereby preventing the unsequenced UAVs from being mixed with the sequenced UAVs in the same area, causing confusion of scheduling instructions and potential conflict risks.

[0153] It should be noted that each of the above modules can be a functional module or a program module, and can be implemented by software or hardware. For the modules implemented by hardware, each of the above modules can be located in the same processor; or each of the above modules can be located in different processors in any combination.

[0154] The embodiment also provides an electronic device including a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program to perform the steps in any of the above method embodiments.

[0155] Optionally, the electronic device can further include a transmission device and an input and output device, wherein the transmission device is connected with the processor, and the input and output device is connected with the processor.

[0156] Optionally, in the embodiment, the processor can be configured to execute the following steps through the computer program:

[0157] S1, acquire power data and task urgency of the unmanned aerial vehicles to be sorted, determine priority coefficients of the unmanned aerial vehicles to be sorted according to the power data and the task urgency, the unmanned aerial vehicles to be sorted including unmanned aerial vehicles requesting landing in the approach and departure circle and unmanned aerial vehicles requesting taking off on the ground.

[0158] S2, construct a take-off and landing sorting model with the minimum total weighted delay time as the target based on the priority coefficients and delay times of the unmanned aerial vehicles, wherein the delay time is the time difference between the actual take-off and landing time and the predicted take-off and landing time, and the constraint conditions of the take-off and landing sorting model include approach and departure time interval constraints and approach and departure advance or delay time constraints.

[0159] S3, combine the sliding time window algorithm and the genetic algorithm to solve the sorting model, obtain a target sorting strategy, and instruct the unmanned aerial vehicles to enter the waiting circle to wait for the system to issue take-off or landing permission based on the target sorting strategy.

[0160] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation manners, and this embodiment will not be described here.

[0161] In one embodiment, Figure 8 is a schematic diagram of the internal structure of an electronic device according to an embodiment of the present application, as Figure 8 indicated, an electronic device is provided, which can be a server, and the internal structure diagram of the electronic device can be as Figure 8 indicated. The electronic device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control ability. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with the external terminal through the network connection. The computer program is executed by the processor to implement a dynamic sorting-based unmanned aerial vehicle group take-off and landing control method.

[0162] Those skilled in the art can understand that Figure 8 the structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0163] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments of each method. Any reference to memory, storage, database or other medium used in each embodiment provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0164] Those skilled in the art should understand that each technical feature of the above-mentioned embodiments can be combined arbitrarily, and in order to make the description simple, each technical feature in the above-mentioned embodiments is not described all possible combinations, however, as long as the combination of these technical features does not exist contradictory, it should be considered as the scope of the present application.

[0165] The above-mentioned embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of protection of the patent of the present application should be subject to the appended claims.

Claims

1. A dynamic ranking based UAV swarm take-off and landing control method, characterized in that, The method is applied to a dynamic sequencing-based unmanned aerial vehicle (UAV) group landing and taking-off control system, and the method comprises the following steps: obtaining power data and task urgency of a UAV to be sequenced, and determining a priority coefficient of the UAV to be sequenced according to the power data and the task urgency, wherein the UAV to be sequenced comprises a UAV requesting landing in a landing and taking-off circle and a UAV requesting taking-off on the ground; constructing a landing and taking-off sequencing model aiming at minimizing total weighted delay time based on the priority coefficient and delay time of the UAV, wherein the delay time is a time difference between actual landing and taking-off time and predicted landing and taking-off time, and constraint conditions of the landing and taking-off sequencing model comprise landing and taking-off time interval constraint and landing and taking-off advance or delay time constraint; solving the sequencing model by combining a sliding time window algorithm and a genetic algorithm to obtain a target sequencing strategy, and instructing the UAV to perform approach / landing procedures based on the target sequencing strategy; a priority coefficient calculation formula of the UAV is as follows: wherein f i is a priority coefficient, E i represents the percentage of consumed electric quantity of the UAV i, E i ∈ [0%, 100%], E max = 100%, Q i represents the urgency degree of the task currently performed by the UAV i, Q i ∈ {1, 2, 3}, Q max = 3.

2. The method of claim 1, wherein, a control airspace of the UAV group landing and taking-off control system comprises a landing and taking-off circle and a waiting circle, a planar area range of the landing and taking-off circle is greater than that of the waiting circle, a center projection of the landing and taking-off circle and the waiting circle is coincident, and the waiting circle is located directly below the landing and taking-off circle, an approach and departure point is arranged on the landing and taking-off circle, the approach and departure point comprises an approach landing point and an approach departure point, and a maximum number of UAVs that can be accommodated in the landing and taking-off circle is equal to a number of approach and departure points; an approach waiting point is arranged on the waiting circle, a number of the approach waiting points is less than the number of approach and departure points, and a UAV requesting landing enters the landing and taking-off circle from an external public route to reach the approach landing point to wait for sequencing.

3. The method of claim 2, wherein, the step of instructing the UAV to perform approach procedures based on the target sequencing strategy comprises the following steps: for the UAV requesting landing, instructing the UAV to fly along a preset route, descend from the approach landing point and enter a corresponding approach waiting point on the waiting circle in a sequence corresponding to the target sequencing strategy, and enter a waiting landing state; receiving a landing request sent by a UAV on the waiting circle, issuing a landing permission to the UAV in the waiting circle based on the landing request, the target sequencing strategy and idle condition of a landing and taking-off channel; and instructing the UAV receiving the landing permission to complete landing through the landing and taking-off channel and enter a ground parking position.

4. The method of claim 2, wherein, the step of instructing the UAV to perform approach procedures based on the target sequencing strategy comprises the following steps: for the UAV requesting taking-off, receiving a taking-off request sent by a UAV on the ground, issuing a taking-off permission to the UAV based on the taking-off request, the target sequencing strategy and idle condition of the landing and taking-off channel; and instructing the UAV receiving the taking-off permission to take off through the landing and taking-off channel and enter the landing and taking-off circle to reach the approach departure point and then join the external public route.

5. The method of claim 1, wherein, the landing and taking-off advance or delay time constraint comprises the following steps: a time difference between actual approach time and predicted approach time of the UAV cannot exceed a first time difference threshold, wherein the approach time is time for the UAV to reach a landing and taking-off airspace through the landing and taking-off circle; and / or A time difference between an actual departure time of the UAV and a scheduled departure time cannot exceed a second time difference threshold range, wherein the departure time is a time when the UAV leaves the arrival-departure airspace via the arrival-departure circle.

6. The method of claim 2, wherein, The arrival-departure time interval constraint comprises: For UAVs entering or leaving the same approach point in sequence, a time interval between an approach time and a departure time of the UAVs needs to be greater than a preset time interval, wherein the approach time is a time when the UAV enters the arrival-departure airspace via the arrival-departure circle, and the departure time is a time when the UAV leaves the arrival-departure airspace via the arrival-departure circle.

7. The method of claim 1, wherein, The constraint condition further comprises an interval constraint and an actual take-off and landing time constraint of the UAVs on a single take-off and landing route, The interval constraint of the UAVs on the single take-off and landing route comprises: for UAVs taking off or landing in sequence on a single take-off and landing route, a time interval between a take-off time and a landing time of the UAVs needs to satisfy a single-route interval model constraint. The actual take-off and landing time constraint comprises: an actual take-off and landing time of each UAV is not earlier than a scheduled take-off and landing time.

8. A dynamic ranking based UAV swarm take-off and landing control system, characterized in that, The system comprises: A priority determination module configured to acquire power data and task urgency of UAVs to be sequenced, and determine a priority coefficient of the UAVs to be sequenced according to the power data and the task urgency, wherein the UAVs to be sequenced comprise UAVs requesting landing in an arrival-departure circle and UAVs requesting taking off on the ground; A priority coefficient calculation formula of the UAVs is as follows: wherein f i is a priority coefficient, E i represents the percentage of consumed electric quantity of the UAV i, E i ∈ [0%, 100%], E max = 100%, Q i represents the urgency degree of the task currently performed by the UAV i, Q i ∈ {1, 2, 3}, Q max = 3; A model construction module configured to construct a take-off and landing sequencing model with a minimum total weighted delay time as a target based on the priority coefficient and a delay time of the UAVs, wherein the delay time is a time difference between an actual take-off and landing time and a scheduled take-off and landing time, and constraint conditions of the take-off and landing sequencing model comprise an arrival-departure time interval constraint and an arrival-departure advance or delay time constraint; A sequencing module configured to solve the sequencing model by combining a sliding time window algorithm and a genetic algorithm, to obtain a target sequencing strategy, and instruct the UAVs to perform an approach / departure procedure based on the target sequencing strategy.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the dynamic sequencing-based UAV group take-off and landing control method in any one of claims 1 to 7.

10. A storage medium having stored thereon a computer program, characterized in that The program is executed by the processor to implement the dynamic sequencing-based UAV group take-off and landing control method in any one of claims 1 to 7.

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