WO2020186919A1 - 无人机集群系统及起飞控制方法、装置、系统和可读介质 - Google Patents

无人机集群系统及起飞控制方法、装置、系统和可读介质 Download PDF

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Publication number
WO2020186919A1
WO2020186919A1 PCT/CN2020/071995 CN2020071995W WO2020186919A1 WO 2020186919 A1 WO2020186919 A1 WO 2020186919A1 CN 2020071995 W CN2020071995 W CN 2020071995W WO 2020186919 A1 WO2020186919 A1 WO 2020186919A1
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Prior art keywords
drones
take
flight
drone
distance
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PCT/CN2020/071995
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English (en)
French (fr)
Inventor
张波
巴航
沙承贤
郑龙飞
陈宇楠
Original Assignee
北京京东尚科信息技术有限公司
北京京东世纪贸易有限公司
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Application filed by 北京京东尚科信息技术有限公司, 北京京东世纪贸易有限公司 filed Critical 北京京东尚科信息技术有限公司
Priority to US17/440,553 priority Critical patent/US20220147062A1/en
Priority to EP20773566.3A priority patent/EP3944052B1/en
Priority to JP2021552740A priority patent/JP7270758B2/ja
Publication of WO2020186919A1 publication Critical patent/WO2020186919A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C39/00—Aircraft not otherwise provided for
    • B64C39/02—Aircraft not otherwise provided for characterised by special use
    • B64C39/024—Aircraft not otherwise provided for characterised by special use of the remote controlled vehicle type, i.e. RPV
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U70/00—Launching, take-off or landing arrangements
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/04—Control of altitude or depth
    • G05D1/06—Rate of change of altitude or depth
    • G05D1/0607—Rate of change of altitude or depth specially adapted for aircraft
    • G05D1/0653—Rate of change of altitude or depth specially adapted for aircraft during a phase of take-off or landing
    • G05D1/0661—Rate of change of altitude or depth specially adapted for aircraft during a phase of take-off or landing specially adapted for take-off
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/102—Simultaneous control of position or course in three dimensions specially adapted for aircraft specially adapted for vertical take-off of aircraft
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts
    • B64U10/13—Flying platforms
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • B64U2201/10—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
    • B64U2201/102—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS] adapted for flying in formations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U80/00—Transport or storage specially adapted for UAVs
    • B64U80/70—Transport or storage specially adapted for UAVs in containers

Definitions

  • the present disclosure relates to the field of electronic technology, and more specifically, to an unmanned aerial vehicle cluster system and a takeoff control method, device, system and readable medium.
  • the inventor found that there are at least the following problems in the prior art: when a drone formation is used to perform tasks, it is usually necessary to make the drones take off from a designated position and assemble to form a designated formation. Perform follow-up tasks. Due to cost control and technical limitations, UAVs usually use a preset script trajectory to achieve formation flying. Considering that the takeoff environment is more complicated and there are more interferences, the first problem to be solved by UAVs is to avoid collisions as much as possible. At present, to solve the collision problem, it is usually considered from the perspective of the initial placement of the UAV on the ground. Specifically, the collision problem is solved by placing the drones on the ground according to the relative position when they are assembled in the specified number sequence. At the same time, it is necessary to appropriately increase the distance between two adjacent drones so that there is sufficient safety space during the takeoff of the drone.
  • each drone needs to be assigned a number manually. Therefore, when the number of drones in the formation is large, the manual assignment of numbers by aircraft is time-consuming. When a drone fails and needs to be replaced, it is also necessary to continue to assign numbers to the replaced drones. Furthermore, there are more restrictions on the placement of drones. On the one hand, the designated number of drones needs to be placed in the designated position, and if there is an incorrect placement, it may cause collisions between drones, which will result in the failure of the formation takeoff mission. On the other hand, the placement of drones is greatly affected by the constraints of ground space, environment, etc. Therefore, the placement of drones is often difficult to meet the requirements of assembly formation.
  • the present disclosure provides an unmanned aerial vehicle cluster and takeoff control method, device, system, and readable medium that can effectively reduce labor time and site requirements.
  • An aspect of the present disclosure provides a take-off control method for a drone cluster, wherein the drone cluster includes multiple drones located in a take-off area.
  • the method includes: obtaining the take-off positions of multiple drones in a take-off area; obtaining a staging area corresponding to the take-off area, the staging area including multiple target positions; according to the take-off positions and multiple target positions of the multiple drones , Determine the target position of each drone among multiple drones; and control multiple drones to take off according to the take-off position of each drone in the multiple drones and the target position of each drone .
  • controlling the take-off of multiple drones according to the take-off position of each drone in the multiple drones and the target position of each drone includes: according to the take-off of each drone Position and target position of each UAV, determine the flight trajectory of each UAV; determine the first distance of any two UAVs according to the flight trajectory of any two UAVs among multiple UAVs; According to the first distance of any two drones, determine the take-off time of each drone; and control each drone to take off according to the take-off time of each drone and the flight trajectory of each drone, Among them, the first distance of any two drones is the shortest distance between the flight trajectories of any two drones.
  • the foregoing determining the take-off time of each drone based on the first distance of any two drones includes: dividing multiple drones according to the first distance of any two drones Are N flight groups, and N is an integer greater than 1; and determine the departure time of each flight group in the N flight groups.
  • each flight group includes at least one drone, and in the case that any flight group in the N flight groups includes multiple drones, any two of the multiple drones included in any flight group
  • the first distance of the drone is not less than the preset distance; the take-off time of different flight groups is different, and the take-off time of at least one drone included in each flight group is the same.
  • the above-mentioned division of multiple drones into N flight groups according to the first distance of any two drones includes the following operations performed in a loop: determining the unmanned aircraft included in the i-th flight group The number of drones; in the case that the number of drones included in the i-th flight group is greater than 1, it is determined whether the first distance of any two drones in the i-th flight group is less than the preset distance; If there are two drones in the flight group whose first distance is less than the preset distance, divide one of the two drones into the i+1th flight group; and When the first distance of any two drones in the flight group is not less than the preset distance, set i to i+1, where, before the above operations are performed in a loop, multiple drones belong to the first A flight group, 1 ⁇ i ⁇ N.
  • the foregoing determination of the target position of each of the multiple drones based on the take-off positions and multiple target positions of the multiple drones includes: according to the take-off positions of the multiple drones And multiple target positions, establish a bipartite graph; determine the flight distance of each drone relative to multiple target positions according to the take-off positions of multiple drones and multiple target positions; The maximum weight matching calculation is performed on the bipartite graph for the flight distance of each target position, and the calculation result is obtained; and the target position of each UAV is determined according to the calculation result. Among them, the calculation result is used to minimize the sum of the flying distance of each drone relative to the determined target position among the multiple drones.
  • the above-mentioned acquiring the take-off positions of the multiple drones in the take-off area includes: acquiring the positioning information of the multiple drones in the take-off area; determining the origin of coordinates in the take-off area; and according to the conversion According to the rules, the positioning information of multiple drones in the take-off area is converted into relative position information of the origin of the relative coordinate, and the relative position information is used to characterize the take-off positions of multiple drones in the take-off area.
  • the takeoff control device includes a takeoff position acquisition module, a staging area acquisition module, a target position determination module, and a takeoff control module.
  • the take-off position acquisition module is used to acquire the take-off positions of multiple drones in the take-off area.
  • the assembly area acquisition module is used to acquire the assembly area corresponding to the take-off area, and the assembly area includes multiple target positions.
  • the target position determination module is used to determine the target position of each UAV among the multiple UAVs according to the take-off positions and multiple target positions of the multiple UAVs.
  • the take-off control module is used to control the take-off of multiple drones according to the take-off position of each drone in the multiple drones and the target position of each drone.
  • the above-mentioned take-off control module includes a flight trajectory determination sub-module, a first distance determination sub-module, a take-off time determination sub-module, and a take-off control sub-module.
  • the flight trajectory determination sub-module is used to determine the flight trajectory of each UAV according to the take-off position of each UAV and the target position of each UAV.
  • the first distance determination submodule is used to determine the first distance of any two drones according to the flight trajectories of any two drones among the multiple drones.
  • the take-off time determination sub-module is used to determine the take-off time of each UAV according to the first distance of any two UAVs.
  • the take-off control sub-module is used to control the take-off of each UAV according to the take-off time of each UAV and the flight trajectory of each UAV.
  • the first distance of any two drones is the shortest distance between the flight trajectories of any two drones.
  • the above-mentioned take-off time determination sub-module includes a division unit and a determination unit.
  • the dividing unit is used to divide multiple drones into N flight groups according to the first distance of any two drones, where N is an integer greater than 1.
  • the determining unit is used to determine the take-off time of each flight group in the N flight groups.
  • each flight group includes at least one drone, and in the case that any flight group in the N flight groups includes multiple drones, any two of the multiple drones included in any flight group
  • the first distance of the drone is not less than the preset distance; the take-off time of different flight groups is different, and the take-off time of at least one drone included in each flight group is the same.
  • the above-mentioned dividing unit is specifically configured to cyclically perform the following operations: determine the number of drones included in the i-th flight group; in the case that the number of drones included in the i-th flight group is greater than one , Determine whether the first distance of any two drones in the i-th flight group is less than the preset distance; if there are two drones in the i-th flight group whose first distance is less than the preset distance, change One of the two drones is divided into the i+1th flight group; and the first distance of any two drones in the i-th flight group is not less than the preset distance Next, set i to i+1. Among them, before the above operations are performed cyclically, multiple drones belong to the first flight group, and 1 ⁇ i ⁇ N.
  • the above-mentioned target position determination module includes a bipartite graph establishment sub-module, a flying distance determination sub-module, a calculation sub-module, and a target position determination sub-module.
  • the bipartite graph creation sub-module is used to create a bipartite graph based on the takeoff positions and multiple target positions of multiple drones.
  • the flight distance determination sub-module is used to determine the flight distance of each drone relative to multiple target positions according to the take-off positions and multiple target positions of multiple drones.
  • the calculation sub-module is used to calculate the maximum weight matching of the bipartite graph according to the flight distance of each UAV relative to multiple target positions to obtain the calculation result.
  • the target position determination sub-module is used to determine the target position of each UAV according to the calculation result. Among them, the calculation result is used to minimize the sum of the flying distance of each drone relative to the determined target position among the multiple drones.
  • the aforementioned take-off position acquisition module includes a positioning information acquisition sub-module, a coordinate origin determination sub-module, and a conversion sub-module.
  • the positioning information acquisition sub-module is used to acquire the positioning information of multiple drones in the take-off area.
  • the coordinate origin determination sub-module is used to determine the coordinate origin in the take-off area.
  • the conversion sub-module is used to convert the positioning information of multiple drones in the take-off area into relative position information of the relative coordinate origin according to the conversion rules.
  • the relative position information is used to characterize the take-off of multiple drones in the take-off area position.
  • an unmanned aerial vehicle cluster system which includes a plurality of unmanned aerial vehicles and a control device.
  • each drone includes sensors and controllers.
  • the sensor is used to obtain the location information of the UAV where it is located, and the controller is used to control the flight of the UAV where it is based on the flight signal.
  • the control device includes a memory and a processor.
  • the memory stores one or more program instructions.
  • the processor is used to perform the following operations according to one or more program instructions: determine the take-off position of multiple drones in the take-off area according to the positioning information of multiple drones; obtain the staging area corresponding to the take-off area, the staging area Including multiple target positions; according to the take-off position and multiple target positions of multiple drones, determine the target position of each drone among multiple drones; and according to the take-off position of each drone and each drone The target position of the drone sends a flight signal to the controller of each drone.
  • the above-mentioned processor is used to send a flight signal by performing the following operations: determine the flight trajectory of each drone according to the take-off position of each drone and the target position of each drone; Determine the first distance between any two drones in the flight trajectory of any two drones; and determine the take-off time of each drone based on the first distance of any two drones; and According to the take-off time of each drone and the flight trajectory of each drone, a flight signal is sent to each drone.
  • the first distance of any two drones is the shortest distance between the flight trajectories of any two drones.
  • the foregoing determining the take-off time of each drone based on the first distance of any two drones includes: dividing multiple drones according to the first distance of any two drones Are N flight groups, and N is an integer greater than 1; and determine the departure time of each flight group in the N flight groups.
  • each flight group includes at least one UAV, and in the case that any flight group in N flight groups includes multiple UAVs, any two of the multiple UAVs included in any flight group
  • the first distance of the drone is not less than the preset distance; the take-off time of different flight groups is different, and the take-off time of at least one drone included in each flight group is the same.
  • the above-mentioned division of multiple drones into N flight groups according to the first distance of any two drones includes the following operations performed in a loop: determining the unmanned aircraft included in the i-th flight group The number of drones; in the case that the number of drones included in the i-th flight group is greater than 1, it is determined whether the first distance of any two drones in the i-th flight group is less than the preset distance; If there are two drones in the flight group whose first distance is less than the preset distance, divide one of the two drones into the i+1th flight group; and If the first distance of any two drones in the flight group is not less than the preset distance, set i to i+1.
  • multiple drones belong to the first flight group, and 1 ⁇ i ⁇ N.
  • the foregoing determination of the target position of each of the multiple drones based on the take-off positions and multiple target positions of the multiple drones includes: according to the take-off positions of the multiple drones And multiple target positions, establish a bipartite graph; determine the flight distance of each drone relative to multiple target positions according to the take-off positions of multiple drones and multiple target positions; The maximum weight matching calculation is performed on the bipartite graph for the flight distance of each target position, and the calculation result is obtained; and the target position of each UAV is determined according to the calculation result. Among them, the calculation result is used to minimize the sum of the flying distance of each drone relative to the determined target position among the multiple drones.
  • the above-mentioned determining the take-off position of the multiple drones in the take-off area based on the positioning information of the multiple drones includes: determining the origin of the coordinates in the take-off area; The positioning information of the man-machine is converted into the relative position information of the relative coordinate origin. The relative position information is used to characterize the take-off positions of multiple drones in the take-off area.
  • control device is provided in any one of the multiple drones.
  • a takeoff control system for an unmanned aerial vehicle cluster which includes: one or more processors; a storage device for storing one or more programs, wherein when all the one or more programs are When executed by one or more processors, one or more processors are caused to execute the aforementioned takeoff control method for the drone cluster.
  • Another aspect of the present disclosure provides a computer-readable storage medium having executable instructions stored thereon, and when the instructions are executed by a processor, the processor executes the above-mentioned takeoff control method for a drone cluster.
  • Another aspect of the present disclosure provides a computer program that includes computer executable instructions, which when executed are used to implement the above-mentioned takeoff control method for a drone cluster.
  • the take-off position of multiple drones is determined
  • the target position of the UAV according to the take-off position and the target position to control the UAV take-off control method, reduce the manual process of assigning numbers to each aircraft, reduce labor time, and reduce the requirements for the take-off site.
  • Fig. 1 schematically shows an application scenario of a drone cluster and take-off control method, device, system, and readable medium according to an embodiment of the present disclosure
  • Fig. 2 schematically shows a flowchart of a takeoff control method for a drone cluster according to an embodiment of the present disclosure
  • FIG. 3 schematically shows a flowchart of obtaining the take-off position of a drone according to an embodiment of the present disclosure
  • Fig. 4 schematically shows a flow chart of determining the target position of each UAV according to an embodiment of the present disclosure
  • Figure 5 schematically shows a flow chart of controlling the take-off of a drone according to an embodiment of the present disclosure
  • FIG. 6A schematically shows a flowchart of determining the take-off time of multiple drones according to an embodiment of the present disclosure
  • FIG. 6B schematically shows a flowchart of dividing multiple drones into N flight groups according to an embodiment of the present disclosure
  • FIG. 7 schematically shows a schematic diagram of the effect of a drone gathering in a gathering area after taking off according to an embodiment of the present disclosure
  • Fig. 8 schematically shows a structural block diagram of a take-off control device for a drone cluster according to an embodiment of the present disclosure
  • FIG. 9 schematically shows a block diagram of a take-off control system suitable for implementing a take-off control method of a drone cluster according to an embodiment of the present disclosure
  • FIG. 10A schematically shows a schematic diagram of an unmanned aerial vehicle cluster system according to the first exemplary embodiment of the present disclosure.
  • Fig. 10B schematically shows a schematic diagram of an unmanned aerial vehicle cluster system according to the second exemplary embodiment of the present disclosure.
  • At least one of the “systems” shall include but not limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and/or systems having A, B, C, etc. ).
  • At least one of the “systems” shall include but not limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and/or systems having A, B, C, etc. ).
  • the embodiments of the present disclosure provide a takeoff control method, device, system and readable medium of an unmanned aerial vehicle cluster.
  • the drone cluster includes multiple drones located in the take-off area.
  • the take-off control method of the drone cluster includes: obtaining the take-off positions of multiple drones in the take-off area; obtaining the assembly area corresponding to the take-off area.
  • the staging area includes multiple target positions; according to the take-off position and multiple target positions of multiple drones, determine the target position of each of the multiple drones; and according to each of the multiple drones.
  • the take-off position of the man-machine and the target position of each UAV control multiple UAVs to take off.
  • FIG. 1 schematically shows an application scenario of a drone cluster and takeoff control method, device, system and readable medium according to an embodiment of the present disclosure.
  • FIG. 1 is only an example of application scenarios in which the embodiments of the present disclosure can be applied to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used for other applications.
  • a take-off area 10 is provided in the application scenario, and a drone cluster composed of drones 101 to 105 is placed in the take-off area 10.
  • the take-off area 10 may be, for example, a certain flat area on the ground to serve as a take-off site for the drone.
  • the take-off area 10 corresponds to a gathering area 20 according to its geographic location (for example, longitude, latitude, and altitude, etc.), which is used to limit the spatial range of the gathering of drone clusters after take-off.
  • the assembly area 20 may have a predetermined target position, for example, it may be the target positions 201-205.
  • the number of target locations is the same as the number of drones in the drone cluster, so that after the drone clusters fly to the target location in the staging area, they can form a formation corresponding to the mission.
  • the setting position of the target position depends on the formation of the drone cluster in the assembly area. It is understandable that, referring to the setting position of the target position in FIG. 1 and the formation of the drone cluster in the assembly area are only examples to facilitate the understanding of the present disclosure, the position and formation can be set according to specific tasks. .
  • the drone cluster can also be placed in a "D" formation, a "flying bird” formation, an oval formation, and a diamond formation in the assembly area, which is not limited in the present disclosure.
  • the UAVs 101 to 105 may specifically be multi-rotor UAVs, unmanned helicopters or fixed-wing UAVs.
  • the multi-rotor drone has the advantages of accurate positioning, flexible position tracking, and ability to hover
  • the drones 101 to 105 in the embodiments of the present disclosure are preferably multi-rotor drones.
  • the take-off control method of the drone cluster specifically first determines the assembly area 20 according to the take-off area 10, and determines the number and distribution of target positions included in the assembly area according to mission requirements; and then according to the drone cluster in the take-off area Each drone is assigned an appropriate target position within the take-off position, and each drone is controlled to take off, so that when each drone flies to the assigned target position, the drone cluster is assembled The shape corresponding to the task requirements is placed in the area.
  • the flight trajectory is determined in real time according to the take-off position of the drone.
  • the take-off control method when placing drones, there is no need to restrict the placement of drone clusters in the take-off area. As long as the placement of drones meets the basic take-off conditions (for example, any The distance between the two drones is about 0.5 to 1m). And therefore, it can reduce the space environment requirements of the take-off site for the UAV cluster take-off to facilitate the execution of the formation mission.
  • the take-off area, assembly area, the number of drones included in the drone cluster in Figure 1 the placement position of the drone in the take-off area, the number of target positions, and the target position in the assembly area
  • the distribution locations within are only schematic. According to implementation needs, it can have any position of take-off area, assembly area, any number of drones and target positions.
  • Fig. 2 schematically shows a flow chart of a takeoff control method for a drone cluster according to an embodiment of the present disclosure.
  • the takeoff control method of the drone cluster in the embodiment of the present disclosure includes operation S210 to operation S240.
  • the UAV cluster may include multiple UAVs located in the take-off area, for example, includes UAVs 101 to 105 located in the take-off area 10 with reference to FIG. 1.
  • the drone may also be placed in the take-off area by the staff.
  • specific take-off areas can be selected according to the conditions of the take-off site, and multiple drones can be placed as evenly as possible in the selected take-off area.
  • the distance between two adjacent drones after placement only needs to be able to meet the minimum requirements for drone takeoff, for example, the interval between any two adjacent drones is 0.5m-1m.
  • the take-off positions of multiple drones may be obtained by manual measurement, and the measurement may specifically be based on a certain position as the origin of the coordinates, and the coordinate values of the positions of the multiple drones can be obtained by measuring the position
  • the coordinate value of i drone can be expressed as p i (x i , y i , z i ).
  • the take-off positions of the multiple drones can also be automatically detected by the positioning system.
  • the operation S210 may specifically be to turn on multiple drones first, and keep the multiple drones in a take-off standby state.
  • the ground station uses the communication link to obtain the UAV's take-off GPS positioning information.
  • the i-th location information may include, for example UAVs UAV latitude, longitude and altitude, for example, can be expressed as the specific p i (lon i, lat i , h i).
  • the positioning information can be converted into a rectangular coordinate representation to facilitate subsequent determination of the target position.
  • the positioning information can be converted into a rectangular coordinate representation to facilitate subsequent determination of the target position.
  • a staging area corresponding to the take-off area is acquired, and the staging area includes a plurality of target positions.
  • each take-off site corresponds to a preset assembly area.
  • the assembly area may specifically be an area at a certain height above the take-off area and a certain horizontal offset from the take-off area. Therefore, when the take-off site is determined, the assembly area can be determined.
  • the foregoing operation S220 specifically is to determine the corresponding assembly area according to the location of the take-off area (for example, longitude, latitude, and altitude, etc., which can uniquely represent the position of the take-off area).
  • the above-mentioned operation S220 may further include an operation of determining a gathering shape according to the formation task, and determining multiple target positions in the gathering area according to the gathering shape.
  • the plurality of target positions in the i-th target position specifically can be represented by R & lt numeral i, the i-th coordinate values of the target position in the specific example, the ground is represented as a point at the origin. More specifically, in order to facilitate subsequent take-off control, the target position may be represented by the same coordinate system as the take-off position of the drone, which is not limited in the present disclosure.
  • the target position of each drone among the multiple drones is determined according to the take-off positions and multiple target positions of the multiple drones.
  • each of the multiple drones should be associated with one of the multiple target positions.
  • the positions are uniquely corresponding, so that multiple drones can be placed in a proper assembly shape in the assembly area. Therefore, by operating S230, the take-off position and the target position can be one-to-one correspondence, that is, the unique target position of each UAV can be determined.
  • multiple drones may collide during takeoff. Therefore, when determining the target position of each UAV in the above operation S230, the take-off positions of the multiple UAVs should not intersect the line of the corresponding target position.
  • the energy that can be used by the drone during flight is constant.
  • the target position of each UAV in operation S230 try to make the total flight path length of multiple UAVs from the take-off position to the target position be the same. And as far as possible, the average length of the flight path of the multiple drones when flying from the take-off position to the target position should be as small as possible.
  • the target position of the drone in operation S230 when determining the target position of the drone in operation S230, different factors may be considered according to actual requirements and different methods may be used to determine the target position, which is not limited in the present disclosure.
  • the foregoing operation S230 may specifically adopt the method described with reference to FIG. 4, which is not described in detail herein.
  • the above operation S240 may specifically determine the flight trajectory of each drone according to the take-off position and target position of each drone.
  • the take-off time may also be determined according to the flight trajectory, so that the two drones that may collide take off at different time points.
  • control multiple drones to take off so that multiple drones are assembled in the assembly area and placed in a preset shape.
  • the specific implementation manner of the foregoing operation S240 may refer to the description of FIG. 5 to FIG. 6B, for example, which will not be described in detail here.
  • the takeoff control method of the drone cluster in the embodiment of the present disclosure does not make the drone take off to a predetermined target position according to a preset script trajectory. Instead, the target position is determined in real time according to the take-off position of the drone, and then the take-off of the drone is controlled according to the determined target position.
  • restrictions on the placement of drones can be reduced, for example, there is no need to place the drones in a predetermined position in advance, and there is no need to assign numbers to the drones in advance. It can effectively reduce the time-consuming work of the staff, and can avoid the collision of two drones caused by the wrong drone placement. Therefore, the smooth execution of formation tasks can be effectively guaranteed.
  • the restrictions on the placement of drones are reduced, the requirements for the space and environment of the take-off site can also be reduced to a certain extent, and the difficulty of performing formation tasks can be reduced.
  • Fig. 3 schematically shows a flow chart of acquiring the take-off position of a drone according to an embodiment of the present disclosure.
  • the process of obtaining the take-off position of the drone in operation S210 may specifically include operations S311 to S313.
  • the positioning information of the drone in the take-off area obtained in operation S311 may specifically be GPS positioning information, and the GPS positioning information may be specifically obtained by a ground station using a communication link.
  • the GPS positioning information includes the longitude, latitude, and altitude of the drone.
  • the operation S211 may be collected in total M different sets of location information, wherein the i-th group location information may be referred to as p i (lon i, lat i , h i), where i LON Represents the longitude value, lat i represents the latitude value, and h i represents the altitude value.
  • multiple drones may be controlled to turn on and maintain the take-off standby state to enable the GPS positioning function of the drone.
  • the origin of coordinates in the take-off area is determined; in operation S313, the positioning information of multiple drones in the take-off area is converted into relative position information relative to the origin of the coordinates according to the conversion rule.
  • the relative position information can be used to characterize the take-off positions of multiple drones in the take-off area.
  • location information p i (lon i, lat i , h i) , for example, can be converted to p i (x i, y i , z i). That is, through operations S312 to S313, the global position coordinates of the drone can be converted into local coordinates relative to the origin of the coordinate, so as to facilitate the determination of the target position of the drone in operation S230.
  • the conversion rule in operation S230 may specifically be a conversion rule for converting global coordinates into rectangular coordinates.
  • the conversion rule can be specifically expressed by the following formula (1) to formula (3), for example:
  • x i K[cos(lat ref )*sin(lat i )-sin(lat ref )*cos(lat i )*cos(lon i -lon ref )]R e ;
  • lat ref , lon ref and h ref are the longitude value, latitude value and height value of the coordinate origin respectively.
  • Fig. 4 schematically shows a flowchart for determining the target position of each drone according to an embodiment of the present disclosure.
  • the process of determining the target position of the drone in operation S230 may specifically include operations S431 to S434.
  • a bipartite graph is established according to the take-off positions of multiple drones and multiple target locations.
  • operation S431 is specifically: taking multiple take-off positions as a point set, and taking multiple target positions as a point set, and constructing a bipartite graph between the two point sets, so that the Of the two endpoints, one endpoint is the take-off position and the other endpoint is the target position.
  • S the set of coordinate values of multiple take-off positions
  • R the set of coordinate values of multiple target positions
  • the constructed bipartite graph, the i-th take-off position and the j-th target position The connected edges can be expressed as Vij .
  • the bipartite graph established in operation S431 may specifically be fully weighted.
  • the weight value is the inverse number of the distance between the take-off position and the target position, specifically the inverse number of the length of the side Vij .
  • the flight distance of each drone relative to the multiple target positions is determined according to the take-off positions and multiple target positions of the multiple drones.
  • the operation S432 may specifically be: calculating the distance between each take-off position and each of the multiple target positions on a take-off position by take-off position to obtain multiple distance values. Assuming that both the take-off position and the target position are M, the number of calculated distance values is M 2 .
  • the coordinate value of the take-off position and the coordinate value of the target position may be expressed based on the same coordinate system, for example.
  • the coordinate values of the take-off position are local coordinates converted with reference to operation S313 in FIG. 3
  • the coordinate values of the multiple target positions acquired in operation S220 are also local coordinates relative to the origin of the coordinates in operation S312.
  • operation S433 may be specifically, for example, using the KM algorithm (Kuhn-Munkres algorithm) to find the maximum weight matching of the bipartite graph under complete matching, so as to maximize the sum of weights of all matched edges.
  • the KM algorithm is used to calculate the maximum weight matching, and the calculated result is the result of the distance and the minimum, that is, the calculation result can make each of the multiple UAVs
  • the sum of the flight distances of the man-machine relative to the determined target position is the smallest.
  • the calculation result obtained by finding the maximum weight matching of the bipartite graph under complete matching can assign a corresponding point in the set R to each point in the set S
  • the calculation result can determine the takeoff position and the target Correspondence of location.
  • the take-off position uniquely represents a UAV
  • the target position of each UAV can be directly determined according to the calculation result.
  • the distance between the take-off positions of multiple drones and the corresponding target positions can be minimized, so that the electric energy stored by the drones can be saved and utilized. Furthermore, because the KM algorithm is used for the maximum weight matching calculation, it can be ensured that the lines of multiple drones from the take-off position to the target position do not cross, thereby avoiding collisions during the take-off process of the drones to a certain extent.
  • Fig. 5 schematically shows a flow chart of controlling the take-off of a drone according to an embodiment of the present disclosure.
  • the process of controlling multiple drones to take off in operation S240 may specifically include operations S541 to S544.
  • operation S541 determine the flight trajectory of each UAV according to the take-off position of each UAV and the target position of each UAV.
  • the flight trajectory of each drone determined in operation S541 may be specifically, for example: each drone The connection between the takeoff position and the target position.
  • the actual take-off of the UAV is generally to first rise to a predetermined height before flying to the target position.
  • the flight trajectory of each UAV determined in operation S541 may specifically be: a line from the take-off position to a predetermined position at a predetermined height above the take-off position, and a trajectory formed by a combination of the line from the predetermined position to the target position.
  • the predetermined position can also be used as the take-off position described in operation S431 with reference to FIG. 4, which will not be repeated here.
  • the first distance of any two drones is determined according to the flight trajectories of any two drones among the multiple drones. Among them, the first distance is specifically the shortest distance between the flight trajectories of any two UAVs.
  • the takeoff time of each UAV is determined according to the first distance of any two UAVs.
  • the operation S543 may specifically be that when the first distance between the two drones is less than the preset distance, set different take-off times for the two drones to avoid this The two drones collided while flying to the target location.
  • the same takeoff time can be set for the two drones to improve the assembly efficiency of multiple drones.
  • the specific implementation of the operation S543 may also adopt the method described later with reference to FIGS. 6A to 6B, which will not be described in detail here.
  • operation S544 according to the take-off time of each drone and the flight trajectory of each drone, control each drone to take off so that each drone of the multiple drones will fly according to the take-off time
  • the trajectory takes off and flies. This allows multiple drones to fly to the corresponding target position and place them in the required shape in the assembly area.
  • FIG. 6A schematically shows a flowchart for determining the take-off time of multiple drones according to an embodiment of the present disclosure
  • FIG. 6B schematically shows the division of multiple drones into N flights according to an embodiment of the present disclosure Set of flowcharts.
  • operation S6431 and operation S6432 may be specifically included.
  • each flight group includes at least one UAV.
  • the first distance of any two drones among the multiple drones belonging to the same flight group should be different. Less than the preset distance.
  • the preset distance may be, for example, the minimum distance to ensure that two drones will not collide.
  • the value of T delay here can be set according to actual requirements. For example, 1s can be used as the initial value of T delay , and theoretical calculations can be used to determine whether there will be a collision if taking off at the set take-off time.
  • the appropriate value of T delay is increased, for example to increase the T delay 1.5s, then theoretical calculations to determine whether there is a collision through. If there is still a collision, increase the value of T delay again.
  • the T delay may specifically be the minimum value to ensure that the drone cluster takes off without collision, thereby effectively ensuring the takeoff efficiency of the drone cluster.
  • the above-mentioned operation S6431 dividing multiple drones into N flight groups may specifically include operations S6431A to S6431E that are executed cyclically.
  • operation S6431A determine the number of drones included in the i-th flight group.
  • operation S6431B it is determined whether the number of drones included in the i-th flight group is greater than one. Among them, in the case that the number of drones included in the i-th flight group is not greater than 1, because the drones included in the i-th flight group are unlikely to collide with each other taking off at the same time, the cycle ends.
  • perform operation S6431E set i to i+1
  • perform operation S6431F determines whether the i-th flight group includes drones. If included, return to perform operation S6431A. If not included, complete the division of multiple drones. If there are two drones with the first distance less than the preset distance in the i-th flight group, perform operation S6431D: set one of the two drones with the first distance less than the preset distance The drones are divided into the i+1th flight group, until the first distance of any two drones in the i-th flight group is not less than the preset distance, then continue to judge the i+1th flight group.
  • the first distance between the mth drone and the nth drone among the plurality of drones is D nm
  • the preset distance is D min .
  • the above operation S6431 may specifically include: Step 1. First determine whether D nm is less than D min , if D nm ⁇ D min , it means that the m-th UAV and the n-th UAV collide during the assembly process Risk, record the numbers of the two drones in the two takeoff groups I 1 and I 2 respectively. Step 2. After changing the values of m and n, repeat step 1 until any two drones in the take-off group I 1 are not at risk of collision. Step 3.
  • the aforementioned i should be greater than or equal to 1 and less than or equal to N.
  • the multiple drones in the take-off area should belong to the first flight group. If the total number of multiple drones is M, the above m and n should both be natural numbers greater than or equal to 1 and less than or equal to M, and m ⁇ n.
  • the embodiment of the present disclosure can make two drones that may collide to take off at different times through the method of determining the take-off time of multiple drones described with reference to FIGS. 6A to 6B. Therefore, it is possible to effectively avoid the occurrence of collision events during the take-off and assembly process of the UAV cluster, and therefore ensure the smooth assembly of the UAV cluster and the smooth progress of subsequent formation tasks.
  • FIG. 7 schematically shows a schematic diagram of the effect of the drones gathering in the gathering area after taking off according to an embodiment of the present disclosure.
  • the embodiment of the present disclosure also uses the method described with reference to FIG. 2 to FIG. 6B to simulate the takeoff control of the UAV cluster.
  • the simulation result is shown in FIG. 7, and multiple UAVs 710 can be controlled to fly to the corresponding target position 720.
  • the take-off control method of the drone cluster in the embodiment of the present disclosure is solved by first converting the allocation problem of the drone target position into a bipartite graph matching problem, and then according to the collision avoidance conditions during the actual flight process, Using delayed take-off to optimize take-off strategy can effectively reduce the risk of collision while ensuring take-off efficiency. And therefore help the smooth execution of subsequent formation tasks.
  • Fig. 8 schematically shows a structural block diagram of a take-off control device for a drone cluster according to an embodiment of the present disclosure.
  • the take-off control device 800 of the drone cluster in the embodiment of the present disclosure includes a take-off position acquisition module 810, a staging area acquisition module 820, a target position determination module 830, and a take-off control module 840.
  • the drone cluster includes multiple drones located in the take-off area. Specifically, for example, it may include the drones 101 to 105 located in the take-off area 10 in FIG. 1.
  • the take-off position obtaining module 810 is used to obtain the take-off positions of multiple drones in the take-off area. According to an embodiment of the present disclosure, the take-off position obtaining module 810 may obtain the take-off position through position sensors provided in the drones 101 to 105, for example. The take-off position acquisition module 810 may be used to perform operation S210 described with reference to FIG. 2, and details are not described herein again.
  • the assembly area acquiring module 820 is used to acquire the assembly area corresponding to the take-off area, and the assembly area includes multiple target positions.
  • the staging area acquisition module 820 can obtain the staging area through communication with a server or a cloud system, for example, and the staging area can correspond to a take-off area, for example.
  • the gathering area acquiring module 820 may be used to perform operation S220 described with reference to FIG. 2, and details are not described herein again.
  • the target position determination module 830 is used to determine the target position of each UAV among the plurality of UAVs according to the take-off position and the plurality of target positions of the plurality of UAVs.
  • the target location determining module 830 may be, for example, a pre-stored program instruction, and the program instruction is executed by a processor to determine the target location.
  • the target position determining module 830 may be used to perform operation S230 described with reference to FIG. 2, and details are not described herein again.
  • the take-off control module 840 is used to control the take-off of multiple drones according to the take-off position of each drone among the multiple drones and the target position of each drone. According to an embodiment of the present disclosure, the take-off control module 840 may control multiple drones to take off, for example, through communication with multiple drones. The takeoff control module 840 may be used to perform the operation S240 described with reference to FIG. 2, and details are not described herein again.
  • the take-off position acquisition module 810 may include, for example, a positioning information acquisition sub-module 811, a coordinate origin determination sub-module 812 and a conversion sub-module 813.
  • the positioning information acquisition sub-module 811 is used to acquire the positioning information of multiple drones in the take-off area.
  • the positioning information acquisition sub-module 811 can be implemented, for example, to be set at the position of each drone among the multiple drones. Sensors etc.
  • the coordinate origin determining sub-module 812 is used to determine the coordinate origin in the take-off area.
  • the conversion sub-module 813 is configured to convert the positioning information of multiple drones in the take-off area into relative position information of the origin of the relative coordinates according to the conversion rule. Wherein, the relative position information is used to characterize the take-off positions of multiple drones in the take-off area.
  • the coordinate origin determination sub-module 812 and the conversion sub-module 813 may be implemented as two different program instructions or the same program instruction, for example, and the program instructions are executed by the processor to realize the aforementioned functions.
  • the positioning information acquisition sub-module 811, the coordinate origin determination sub-module 812, and the conversion sub-module 813 may, for example, be respectively used to perform operations S311 to S313 described with reference to FIG. 3, and details are not described herein again.
  • the above-mentioned target position determination module 830 may include, for example, a bipartite graph establishment sub-module 831, a flight distance determination sub-module 832, a calculation sub-module 833 and a target position determination sub-module 834.
  • the bipartite graph creation sub-module 831 is used to create a bipartite graph according to the takeoff positions and multiple target positions of multiple drones.
  • the flight distance determination submodule 832 is used to determine the flight distance of each drone relative to the multiple target positions according to the take-off positions and multiple target positions of the multiple drones.
  • the calculation sub-module 833 is used to perform maximum weight matching calculation on the bipartite graph according to the flight distance of each UAV relative to multiple target positions to obtain the calculation result.
  • the target position determination sub-module 834 is used to determine the target position of each UAV according to the calculation result. Wherein, the calculation result is used to minimize the sum of the flying distance of each drone relative to the determined target position among the multiple drones.
  • the bipartite graph establishment sub-module 831, the flight distance determination sub-module 832, the calculation sub-module 833, and the target position determination sub-module 834 can all be implemented as program instructions, which are called by the processor to achieve the foregoing Function.
  • the bipartite graph establishment sub-module 831, the flying distance determination sub-module 832, the calculation sub-module 833, and the target position determination sub-module 834 can be respectively used to perform operations S431 to S434 described with reference to FIG. 4, and details are not described herein again.
  • the takeoff control module 840 may include, for example, a flight trajectory determination submodule 841, a first distance determination submodule 842, a takeoff time determination submodule 843, and a takeoff control submodule 844.
  • the flight trajectory determination sub-module 841 is used to determine the flight trajectory of each drone according to the take-off position of each drone and the target position of each drone.
  • the first distance determining sub-module 842 is configured to determine the first distance of any two drones according to the flight trajectories of any two drones among the plurality of drones.
  • the take-off time determination submodule 843 is used to determine the take-off time of each UAV according to the first distance of any two UAVs.
  • the take-off control sub-module 844 is used to control the take-off of each UAV according to the take-off time of each UAV and the flight trajectory of each UAV.
  • the first distance of any two drones is the shortest distance between the flight trajectories of any two drones.
  • the flight trajectory determination submodule 841, the first distance determination submodule 842, and the takeoff time determination submodule 843 may be implemented as program instructions, and the takeoff control submodule 844 may be implemented as program instructions and not related to multiple aircraft.
  • the communication module of human-machine communication can control multiple drones to take off through communication with multiple drones.
  • the flight trajectory determination sub-module 841, the first distance determination sub-module 842, the take-off time determination sub-module 843, and the take-off control sub-module 844 may be respectively used to perform operations S541 to S544 described with reference to FIG. 5, and details are not described herein again.
  • the above-mentioned take-off time determining sub-module 843 may include a dividing unit 8431 and a determining unit 8432.
  • the dividing unit 8431 is used to divide multiple drones into N flight groups according to the first distance of any two drones, where N is an integer greater than 1.
  • the determining unit 8432 is used to determine the take-off time of each flight group in the N flight groups.
  • each flight group includes at least one drone, and in the case that any flight group in the N flight groups includes multiple drones, any two of the multiple drones included in any flight group
  • the first distance of the drone is not less than the preset distance; the take-off time of different flight groups is different, and the take-off time of at least one drone included in each flight group is the same.
  • the dividing unit 8431 and the determining unit 8432 may be implemented as program instructions.
  • the dividing unit 8431 and the determining unit 8432 may be respectively configured to perform operations S6431 to S6432 described with reference to FIG. 6A, and details are not described herein again.
  • the above-mentioned dividing unit 8431 may be specifically configured to perform the following operations in a loop: determine the number of drones included in the i-th flight group; the number of drones included in the i-th flight group is greater than 1. In this case, determine whether the first distance of any two drones in the i-th flight group is less than the preset distance; in the case that there are two drones with the first distance less than the preset distance in the i-th flight group , Divide one of the two drones into the i+1th flight group; and the first distance of any two drones in the i-th flight group is not less than the preset distance In the case of, set i to i+1.
  • the dividing unit 8431 may be specifically configured to perform operations S6431A to S6431E described with reference to FIG. 6B, and details are not described herein again.
  • any number of modules, submodules, units, and subunits, or at least part of the functions of any number of them, may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be split into multiple modules for implementation.
  • any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), System-on-chip, system-on-substrate, system-on-package, application-specific integrated circuit (ASIC), or hardware or firmware in any other reasonable way that integrates or encapsulates the circuit, or can be implemented by software, hardware, and firmware. Any one of these implementations or an appropriate combination of any of them can be implemented.
  • FPGA field programmable gate array
  • PLA programmable logic array
  • ASIC application-specific integrated circuit
  • any one of these implementations or an appropriate combination of any of them can be implemented.
  • one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be at least partially implemented as a computer program module, and the computer program module may perform corresponding functions when it is executed.
  • take-off position acquisition module 810 For example, take-off position acquisition module 810, assembly area acquisition module 820, target position determination module 830, take-off control module 840, positioning information acquisition sub-module 811, coordinate origin determination sub-module 812, conversion sub-module 813, bipartite graph establishment sub-module 831 , Flight distance determination submodule 832, calculation submodule 833, target position determination submodule 834, flight trajectory determination submodule 841, first distance determination submodule 842, takeoff time determination submodule 843, takeoff control submodule 844, division unit Any number of the 8431 and the determining unit 8432 can be combined into one module for implementation, or any one of the modules can be split into multiple modules.
  • At least one of the module 844, the dividing unit 8431, and the determining unit 8432 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on
  • take-off position acquisition module 810 assembly area acquisition module 820, target position determination module 830, take-off control module 840, positioning information acquisition sub-module 811, coordinate origin determination sub-module 812, conversion sub-module 813, bipartite graph establishment sub-module 831 , Flight distance determination submodule 832, calculation submodule 833, target position determination submodule 834, flight trajectory determination submodule 841, first distance determination submodule 842, takeoff time determination submodule 843, takeoff control submodule 844, division unit
  • At least one of the 8431 and the determining unit 8432 can be at least partially implemented as a computer program module, and when the computer program module is run, it can perform a corresponding function.
  • Fig. 9 schematically shows a block diagram of a take-off control system suitable for implementing a take-off control method of a drone cluster according to an embodiment of the present disclosure.
  • the takeoff control system shown in FIG. 9 is only an example, and should not bring any limitation to the function and scope of use of the embodiments of the present disclosure.
  • a takeoff control system 900 includes a processor 901, which can be loaded to a random access memory (RAM) 903 according to a program stored in a read only memory (ROM) 902 or from a storage part 908 In the program, various appropriate actions and processing are performed.
  • the processor 901 may include, for example, a general-purpose microprocessor (for example, a CPU), an instruction set processor and/or a related chipset and/or a special purpose microprocessor (for example, an application specific integrated circuit (ASIC)), and so on.
  • the processor 901 may also include on-board memory for caching purposes.
  • the processor 901 may include a single processing unit or multiple processing units for performing different actions of a method flow according to an embodiment of the present disclosure.
  • the RAM 903 stores various programs and data required for the operation of the takeoff control system 900.
  • the processor 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904.
  • the processor 901 executes various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 902 and/or RAM 903. It should be noted that the program may also be stored in one or more memories other than ROM 902 and RAM 903.
  • the processor 901 may also execute various operations of the method flow according to the embodiments of the present disclosure by executing programs stored in the one or more memories.
  • the takeoff control system 900 may further include an input/output (I/O) interface 905, and the input/output (I/O) interface 905 is also connected to the bus 904.
  • the takeoff control system 900 may also include one or more of the following components connected to the I/O interface 905: an input part 906 including a keyboard, a mouse, etc.; including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. And an output section 907 of speakers and the like; a storage section 908 including a hard disk and the like; and a communication section 909 including a network interface card such as a LAN card, a modem, and the like.
  • the communication section 909 performs communication processing via a network such as the Internet.
  • the drive 910 is also connected to the I/O interface 905 as needed.
  • a removable medium 911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as required, so that the computer program read therefrom is installed into the storage portion 908 as required.
  • the method flow according to the embodiment of the present disclosure may be implemented as a computer software program.
  • the embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains program code for executing the method shown in the flowchart.
  • the computer program may be downloaded and installed from the network through the communication part 909, and/or installed from the removable medium 911.
  • the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed.
  • the above-described systems, devices, devices, modules, units, etc. may be implemented by computer program modules.
  • the present disclosure also provides a computer-readable storage medium.
  • the computer-readable storage medium may be included in the device/device/system described in the above embodiment; or it may exist alone without being assembled into the device/ In the device/system.
  • the aforementioned computer-readable storage medium carries one or more programs, and when the aforementioned one or more programs are executed, the method according to the embodiments of the present disclosure is implemented.
  • the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but not limited to: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM) , Erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.
  • the computer-readable storage medium may include one or more memories other than the ROM 902 and/or RAM 903 and/or ROM 902 and RAM 903 described above.
  • FIG. 10A schematically shows a schematic diagram of an unmanned aerial vehicle cluster system according to the first exemplary embodiment of the present disclosure
  • FIG. 10B schematically shows a schematic diagram of an unmanned aerial vehicle cluster system according to the second exemplary embodiment of the present disclosure.
  • the drone cluster system of the embodiment of the present disclosure may include multiple drones and control devices.
  • the number of the multiple drones can be set according to actual needs.
  • the multiple drones may include, for example, M drones from the first drone to the Mth drone.
  • control device 1040 may be installed in any one of the N drones, for example, in the first drone 1010.
  • the second UAV 1020 to the Mth UAV 1030 all communicate with the first UAV 1010 to receive the flight signal sent by the control device 1040 through the communication connection.
  • the control device 1040 may be independent of the first to Nth drones and be installed at the ground control center.
  • the first drone 1010', the second drone 1020' to the Mth drone 1030' are all communicatively connected with the control device 1040 at the ground control center to receive the control device through the communication connection Flight signal sent by 1040.
  • the control device 1040 may include a memory 1041 and a processor 1042, for example.
  • the memory 1041 stores one or more program instructions.
  • the processor 1042 can perform the following operations by calling the one or more program instructions: determine the take-off positions of multiple drones in the take-off area according to the positioning information of the multiple drones; obtain the assembly area corresponding to the take-off area,
  • the staging area includes multiple target positions (operation S220); according to the take-off positions of the multiple drones and the multiple target positions, determine the target position of each of the multiple drones (operation S230); and
  • the take-off position of each UAV and the target position of each UAV send flight signals to the controller of each UAV.
  • the flight signal is used to control the flight of each UAV.
  • each of the multiple drones includes a sensor 1001 and a controller 1002.
  • the sensor 1001 may be, for example, a position sensor or a global positioning system (GPS), etc., and is used to obtain positioning information of the drone where it is located.
  • the controller 1002 may be, for example, a flight control system, or a microprocessor, etc., for controlling the flight of the drone where it is located according to the flight signal.
  • the sensor 1001 may be connected to the processor 1042 in the control device 1040, for example, to send the acquired positioning information of the drone to the processor 1042.
  • the controller 1002 may be connected to the processor 1042 in the control device 1040, for example, to receive the flight signal sent by the control device 1040, and control the drone to fly according to the flight signal.
  • the processor 1042 may, for example, send a flight signal through the following operations: determine the flight trajectory of each drone according to the take-off position of each drone and the target position of each drone (operation S541 ); Determine the first distance of any two drones according to the flight trajectory of any two drones in the multiple drones (operation S542); Determine each drone according to the first distance of any two drones The take-off time of the drone (operation S543); and send a flight signal to each drone according to the take-off time of each drone and the flight trajectory of each drone.
  • the first distance of any two drones is the shortest distance between the flight trajectories of any two drones.
  • the flight signal includes the take-off time and flight trajectory.
  • the processor 1042 may, for example, determine the take-off time of each UAV through the following operations: According to the first distance of any two UAVs, multiple UAVs are divided into N flight groups , N is an integer greater than 1 (operation S6431); and determine the take-off time of each flight group in the N flight groups (operation S6432). Wherein, each flight group includes at least one UAV, and in the case that any flight group in N flight groups includes multiple UAVs, any two of the multiple UAVs included in any flight group The first distance of the drone is not less than the preset distance; the take-off time of different flight groups is different, and the take-off time of at least one drone included in each flight group is the same.
  • the processor 1042 may divide multiple drones into N flight groups by, for example, cyclically executing the following operations: determine the number of drones included in the i-th flight group (operation S6431A); When the number of drones included in the i-th flight group is greater than 1, it is determined whether the first distance of any two drones in the i-th flight group is less than the preset distance (operation S6431C); in the i-th flight If there are two drones in the group whose first distance is less than the preset distance, divide one of the two drones into the i+1th flight group (operation S6431D); and In the case that the first distance of any two drones in the i-th flight group is not less than the preset distance, the i is set to i+1 (operation S6431E). Among them, before the above operations are performed cyclically, multiple drones belong to the first flight group, and 1 ⁇ i ⁇ N.
  • the processor 1042 may, for example, determine the target position of each drone among the multiple drones through the following operations: establish a bipartite graph based on the take-off positions and multiple target positions of the multiple drones (Operation S431); Determine the flight distance of each drone relative to multiple target positions according to the take-off position and multiple target positions of multiple drones (Operation S432); For the flight distance of the target position, perform maximum weight matching calculation on the bipartite graph to obtain the calculation result (operation S433); and according to the calculation result, determine the target position of each UAV (operation S434). Among them, the calculation result is used to minimize the sum of the flying distance of each drone relative to the determined target position among the multiple drones.
  • the processor 1042 may determine the take-off positions of multiple drones in the take-off area by, for example, determining the origin of coordinates in the take-off area (operation S312); and according to the conversion rule, the multiple drones
  • the positioning information of the drone is converted into relative position information of the relative coordinate origin, and the relative position information is used to characterize the take-off positions of multiple drones in the take-off area (operation S313).
  • each block in the flowchart or block diagram may represent a module, program segment, or part of code, and the above-mentioned module, program segment, or part of code contains one or more for realizing the specified logical function Executable instructions.
  • the functions marked in the block may also occur in a different order from the order marked in the drawings. For example, two blocks shown in succession can actually be executed substantially in parallel, or they can sometimes be executed in the reverse order, depending on the functions involved.
  • each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be It is realized by a combination of dedicated hardware and computer instructions.

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Abstract

一种无人机集群系统及起飞控制方法、装置、系统和可读介质。其中，无人机集群包括位于起飞区域的多架无人机，该无人机集群的起飞控制方法包括：获取多架无人机在起飞区域内的起飞位置(S210)；获取与起飞区域对应的集结区域，该集结区域包括多个目标位置(S220)；根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置(S230)；以及根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞(S240)。

Description

无人机集群系统及起飞控制方法、装置、系统和可读介质 技术领域
本公开涉及电子技术领域，更具体地，涉及一种无人机集群系统及起飞控制方法、装置、系统和可读介质。
背景技术
目前，单个无人机的使用(例如用于航拍、巡检、物流等)已较为成熟。考虑到多旋翼无人机定位精确、位置跟踪灵活及能够悬停等优点，采用多架无人机组成编队执行任务，无疑是当前无人机发展的一个重要趋势。
在实现本公开构思的过程中，发明人发现现有技术中至少存在如下问题：采用无人机编队执行任务时，通常需要使无人机从指定位置起飞并集结组成指定的编队队形，再执行后续任务。而由于成本的控制和技术的限制，通常无人机采用预设脚本轨迹的形式实现编队飞行。考虑到起飞环境较为复杂、干扰较多，无人机在起飞时首要解决的问题是尽可能的避免碰撞情况的发生。目前解决碰撞问题，通常从无人机地面初始摆放位置的角度进行考虑。具体通过将无人机以指定的编号顺序，按照集结时相对位置进行地面摆放的方式解决碰撞问题。同时，需要适当地增大相邻两架无人机之间的距离，以使得无人机起飞过程中具有足够的安全空间。
上述解决碰撞问题的方法具有以下缺陷：每架无人机都需要以人工分配的方式指定编号。因此，当编队无人机数量较大时，人工逐机分配编号的工作较为耗时，当有某架无人机出现故障需要替换时，也需要给替换的无人机继续分配编号。再者，无人机的摆放限制较多。一方面，需要将指定编号的无人机放在指定的位置，而若存在摆放错误的情况，就有可能引起无人机之间的碰撞，从而导致编队起飞任务失败。另一方面，无人机摆放受地面场地空间、环境等限制因素的影响较大，因此，无人机的摆放往往很难满足集结队形的要求。
发明内容
有鉴于此，本公开提供了一种能够有效降低人工耗时、降低场地要求的无人机集群及起飞控制方法、装置、系统及可读介质。
本公开的一个方面提供了一种无人机集群的起飞控制方法，其中，无 人机集群包括位于起飞区域的多架无人机。该方法包括：获取多架无人机在起飞区域内的起飞位置；获取与起飞区域对应的集结区域，该集结区域包括多个目标位置；根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置；以及根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞。
根据本公开的实施例，上述根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞包括：根据每架无人机的起飞位置及每架无人机的目标位置，确定每架无人机的飞行轨迹；根据多架无人机中任意两架无人机的飞行轨迹，确定任意两架无人机的第一距离；根据任意两架无人机的第一距离，确定每架无人机的起飞时间；以及根据每架无人机的起飞时间及每架无人机的飞行轨迹，控制每架无人机起飞，其中，任意两架无人机的第一距离为任意两架无人机的飞行轨迹之间的最短距离。
根据本公开的实施例，上述根据任意两架无人机的第一距离，确定每架无人机的起飞时间包括：根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，N为大于1的整数；以及确定N个飞行组中每个飞行组的起飞时间。其中，每个飞行组包括至少一架无人机，且在N个飞行组中的任一飞行组包括多架无人机的情况下，任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的至少一架无人机的起飞时间相同。
根据本公开的实施例，上述根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，包括循环执行的以下操作：确定第i个飞行组包括的无人机个数；在第i个飞行组包括的无人机个数大于1的情况下，确定第i个飞行组中任意两架无人机的第一距离是否小于预设距离；在第i个飞行组中存在第一距离小于预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及在第i个飞行组中任意两架无人机的第一距离均不小于预设距离的情况下，将i置为i+1，其中，在循环执行以上操作之前，多架无人机均属于第1个飞行组，1≤i≤N。
根据本公开的实施例，上述根据多架无人机的起飞位置及多个目标位 置，确定多架无人机中每架无人机的目标位置，包括：根据多架无人机的起飞位置及多个目标位置，建立二分图；根据多架无人机的起飞位置及多个目标位置，确定每架无人机相对于多个目标位置的飞行距离；根据每架无人机相对于多个目标位置的飞行距离，对二分图进行最大权匹配计算，得到计算结果；以及根据计算结果，确定每架无人机的目标位置。其中，计算结果用于使多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
根据本公开的实施例，上述获取所述多架无人机在起飞区域内的起飞位置包括：获取多架无人机在起飞区域内的定位信息；确定起飞区域中的坐标原点；以及根据转换规则，将多架无人机在起飞区域内的定位信息转换为相对坐标原点的相对位置信息，该相对位置信息用于表征多架无人机在起飞区域内的起飞位置。
本公开的另一个方面提供了一种无人机集群的起飞控制装置，其中，无人机集群包括位于起飞区域的多架无人机。该起飞控制装置包括起飞位置获取模块、集结区域获取模块、目标位置确定模块及起飞控制模块。其中，起飞位置获取模块用于获取多架无人机在起飞区域内的起飞位置。集结区域获取模块用于获取与起飞区域对应的集结区域，该集结区域包括多个目标位置。目标位置确定模块用于根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置。起飞控制模块用于根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞。
根据本公开的实施例，上述起飞控制模块包括飞行轨迹确定子模块、第一距离确定子模块、起飞时间确定子模块及起飞控制子模块。其中，飞行轨迹确定子模块用于根据每架无人机的起飞位置及每架无人机的目标位置，确定每架无人机的飞行轨迹。第一距离确定子模块用于根据多架无人机中任意两架无人机的飞行轨迹，确定任意两架无人机的第一距离。起飞时间确定子模块用于根据任意两架无人机的第一距离，确定每架无人机的起飞时间。起飞控制子模块用于根据每架无人机的起飞时间及每架无人机的飞行轨迹，控制每架无人机起飞。其中，任意两架无人机的第一距离为任意两架无人机的飞行轨迹之间的最短距离。
根据本公开的实施例，上述起飞时间确定子模块包括划分单元和确定单元。其中，划分单元用于根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，N为大于1的整数。确定单元用于确定N个飞行组中每个飞行组的起飞时间。其中，每个飞行组包括至少一架无人机，且在N个飞行组中的任一飞行组包括多架无人机的情况下，任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的至少一架无人机的起飞时间相同。
根据本公开的实施例，上述划分单元具体用于循环执行以下操作：确定第i个飞行组包括的无人机个数；在第i个飞行组包括的无人机个数大于1的情况下，确定第i个飞行组中任意两架无人机的第一距离是否小于预设距离；在第i个飞行组中存在第一距离小于预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及在第i个飞行组中任意两架无人机的第一距离均不小于预设距离的情况下，将i置为i+1。其中，在循环执行以上操作之前，多架无人机均属于第1个飞行组，1≤i≤N。
根据本公开的实施例，上述目标位置确定模块包括二分图建立子模块、飞行距离确定子模块、计算子模块和目标位置确定子模块。其中，二分图建立子模块用于根据多架无人机的起飞位置及多个目标位置，建立二分图。飞行距离确定子模块用于根据多架无人机的起飞位置及多个目标位置，确定每架无人机相对于多个目标位置的飞行距离。计算子模块，用于根据每架无人机相对于多个目标位置的飞行距离，对二分图进行最大权匹配计算，得到计算结果。目标位置确定子模块用于根据计算结果，确定每架无人机的目标位置。其中，计算结果用于使多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
根据本公开的实施例，上述起飞位置获取模块包括定位信息获取子模块、坐标原点确定子模块及转换子模块。其中，定位信息获取子模块用于获取多架无人机在起飞区域内的定位信息。坐标原点确定子模块用于确定起飞区域中的坐标原点。转换子模块用于根据转换规则，将多架无人机在起飞区域内的定位信息转换为相对坐标原点的相对位置信息，该相对位置信息用于表征多架无人机在起飞区域内的起飞位置。
本公开的另一方面提供了一种无人机集群系统，该系统包括：多架无人机和控制装置。其中，每架无人机包括传感器和控制器。传感器用于获取其所在的无人机的定位信息，控制器用于根据飞行信号控制其所在的无人机飞行。控制装置包括存储器和处理器。存储器存储有一条或多条程序指令。处理器用于根据一条或多条程序指令执行以下操作：根据多架无人机的定位信息，确定多架无人机在起飞区域内的起飞位置；获取与起飞区域对应的集结区域，该集结区域包括多个目标位置；根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置；以及根据每架无人机的起飞位置及每架无人机的目标位置，向每架无人机的控制器发送飞行信号。
根据本公开的实施例，上述处理器用于通过执行以下操作发送飞行信号：根据每架无人机的起飞位置及每架无人机的目标位置，确定每架无人机的飞行轨迹；根据多架无人机中任意两架无人机的飞行轨迹，确定任意两架无人机的第一距离；根据任意两架无人机的第一距离，确定每架无人机的起飞时间；以及根据每架无人机的起飞时间及每架无人机的飞行轨迹，向每架无人机发送飞行信号。其中，任意两架无人机的第一距离为任意两架无人机的飞行轨迹之间的最短距离。
根据本公开的实施例，上述根据任意两架无人机的第一距离，确定每架无人机的起飞时间包括：根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，N为大于1的整数；以及确定N个飞行组中每个飞行组的起飞时间。其中，每个飞行组包括至少一架无人机，且在N个飞行组中任一飞行组包括多架无人机的情况下，任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的至少一架无人机的起飞时间相同。
根据本公开的实施例，上述根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，包括循环执行的以下操作：确定第i个飞行组包括的无人机个数；在第i个飞行组包括的无人机个数大于1的情况下，确定第i个飞行组中任意两架无人机的第一距离是否小于预设距离；在第i个飞行组中存在第一距离小于预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及在第i个飞行 组中任意两架无人机的第一距离均不小于预设距离的情况下，将i置为i+1。其中，在循环执行以上操作之前，多架无人机均属于第1个飞行组，1≤i≤N。
根据本公开的实施例，上述根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置，包括：根据多架无人机的起飞位置及多个目标位置，建立二分图；根据多架无人机的起飞位置及多个目标位置，确定每架无人机相对于多个目标位置的飞行距离；根据每架无人机相对于多个目标位置的飞行距离，对二分图进行最大权匹配计算，得到计算结果；以及根据计算结果，确定每架无人机的目标位置。其中，计算结果用于使多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
根据本公开的实施例，上述根据多架无人机的定位信息，确定多架无人机在起飞区域内的起飞位置包括：确定起飞区域中的坐标原点；以及根据转换规则，将多架无人机的定位信息转换为相对坐标原点的相对位置信息。该相对位置信息用于表征多架无人机在起飞区域内的起飞位置。
根据本公开的实施例，上述控制装置设置于多架无人机中的任意一架无人机中。
本公开的另一个方面提供了一种无人机集群的起飞控制系统，包括：一个或多个处理器；存储装置，用于存储一个或多个程序，其中，当所一个或多个程序分别被一个或多个处理器执行时，使得一个或多个处理器执行上述的无人机集群的起飞控制方法。
本公开的另一个方面提供了一种计算机可读存储介质，其上存储有可执行指令，该指令被处理器执行时使处理器执行上述的无人机集群的起飞控制方法。
本公开的另一个方面提供了一种计算机程序，该计算机程序包括计算机可执行指令，该指令在被执行时用于实现如上所述的无人机集群的起飞控制方法。
根据本公开的实施例，可以至少部分地解决现有技术中无人机集群的起飞需要人工逐机分配编号导致的耗时较长的缺陷，并因此通过根据多架无人机的起飞位置确定无人机的目标位置，根据起飞位置和目标位置控制 无人机起飞的控制方法，减少人工逐机分配编号的过程，降低人工耗时，并降低对起飞场地的要求。
附图说明
附图是用来提供对本发明的进一步理解，并且构成说明书的一部分，与下面的具体实施方式一起用于解释本发明，但并不构成对本发明的限制。在附图中：
图1示意性示出了根据本公开实施例的无人机集群及起飞控制方法、装置、系统和可读介质的应用场景；
图2示意性示出了根据本公开实施例的无人机集群的起飞控制方法的流程图；
图3示意性示出了根据本公开实施例的获取无人机的起飞位置的流程图；
图4示意性示出了根据本公开实施例的确定每架无人机的目标位置的流程图；
图5示意性示出了根据本公开实施例的控制无人机起飞的流程图；
图6A示意性示出了根据本公开实施例的确定多架无人机的起飞时间的流程图；
图6B示意性示出了根据本公开实施例的将多架无人机划分为N个飞行组的流程图；
图7示意性示出了根据本公开实施例的无人机起飞后在集结区域集结的效果示意图；
图8示意性示出了根据本公开实施例的无人机集群的起飞控制装置的结构框图；
图9示意性示出了根据本公开实施例的适于实现无人机集群的起飞控制方法的起飞控制系统的方框图；
图10A示意性示出了根据本公开示例性实施例一的无人机集群系统的示意图；以及
图10B示意性示出了根据本公开示例性实施例二的无人机集群系统的示意图。
具体实施方式
以下，将参照附图来描述本公开的实施例。但是应该理解，这些描述只是示例性的，而并非要限制本公开的范围。在下面的详细描述中，为便于解释，阐述了许多具体的细节以提供对本公开实施例的全面理解。然而，明显地，一个或多个实施例在没有这些具体细节的情况下也可以被实施。此外，在以下说明中，省略了对公知结构和技术的描述，以避免不必要地混淆本公开的概念。
在此使用的术语仅仅是为了描述具体实施例，而并非意在限制本公开。在此使用的术语“包括”、“包含”等表明了所述特征、步骤、操作和/或部件的存在，但是并不排除存在或添加一个或多个其他特征、步骤、操作或部件。
在此使用的所有术语(包括技术和科学术语)具有本领域技术人员通常所理解的含义，除非另外定义。应注意，这里使用的术语应解释为具有与本说明书的上下文相一致的含义，而不应以理想化或过于刻板的方式来解释。
在使用类似于“A、B和C等中至少一个”这样的表述的情况下，一般来说应该按照本领域技术人员通常理解该表述的含义来予以解释(例如，“具有A、B和C中至少一个的系统”应包括但不限于单独具有A、单独具有B、单独具有C、具有A和B、具有A和C、具有B和C、和/或具有A、B、C的系统等)。在使用类似于“A、B或C等中至少一个”这样的表述的情况下，一般来说应该按照本领域技术人员通常理解该表述的含义来予以解释(例如，“具有A、B或C中至少一个的系统”应包括但不限于单独具有A、单独具有B、单独具有C、具有A和B、具有A和C、具有B和C、和/或具有A、B、C的系统等)。
本公开的实施例提供了一种无人机集群的起飞控制方法、装置、系统和可读介质。其中无人机集群包括位于起飞区域的多架无人机，无人机集群的起飞控制方法包括：获取多架无人机在起飞区域内的起飞位置；获取与起飞区域对应的集结区域，该集结区域包括多个目标位置；根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置；以及根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞。
图1示意性示出了根据本公开实施例的无人机集群及起飞控制方法、装置、系统和可读介质的应用场景。需要说明的是，图1所示仅为可以应用本公开实施例的应用场景的示例，以帮助本领域技术人员理解本公开的技术内容，但并不意味着本公开实施例不可以用于其他设备、系统、环境或场景。
如图1所示，该应用场景中设置有起飞区域10，该起飞区域10中摆放有由无人机101～105构成的无人机集群。
其中，起飞区域10具体例如可以是地面上的某一平坦区域，以作为无人机的起飞场地。该起飞区域10根据其所在的地理位置(例如经度、维度及高度等)，对应有一集结区域20，用于限定无人机集群起飞后集结的空间范围。
其中，根据无人机集群组成编队执行任务的需求，该集结区域20中可以具有预定的目标位置，具体例如可以是目标位置201～205。该目标位置的数量与无人机集群中无人机的个数相同，以使得无人机集群在飞至集结区域中的目标位置后，能够摆成与执行任务相对应的队形，例如可以是参考图1中的“T”字形队形。其中，目标位置的设置位置取决于无人机集群在集结区域中摆成的队形。可以理解的是，参考图1中目标位置的设置位置及无人机集群在集结区域中摆成的队形仅作为示例以利于理解本公开，该位置及队形具体可以根据具体任务进行设定。例如，无人机集群还可以在集结区域中摆成“D”字形队形、“飞鸟状”队形、椭圆形队形及菱形队形等，本公开对此不作限定。
其中，无人机101～105具体可以采用多旋翼无人机、无人直升机或者固定翼无人机。其中，考虑到多旋翼无人机具有定位精确、位置跟踪灵活及能够悬停等优势，则本公开实施例中的无人机101～105优选为多旋翼无人机。
本公开提供的无人机集群的起飞控制方法，具体是先根据起飞区域10确定集结区域20，根据任务需求确定集结区域包括的目标位置的个数及分布；然后根据无人机集群在起飞区域内的起飞位置，为每个无人机分配适当的目标位置，并控制每个无人机起飞，以使每个无人机飞至为其分配的目标位置时，使得无人机集群在集结区域内摆出与任务需求对应的形状。
其中，考虑到对无人机集群的起飞控制，并非采用预设脚本轨迹的形式，而是实时的根据无人机的起飞位置确定飞行轨迹，因此在执行本公开实施例的无人机集群的起飞控制方法之前，在对无人机进行摆放时，无需对无人机集群在起飞区域内的摆放位置做严格限制，只要保证无人机的摆放满足基本的起飞条件(例如，任意两架无人机之间的间隔为0.5～1m左右)即可。并因此可以降低无人机集群起飞对起飞场地的空间环境要求，以利于编队任务的执行。
可以理解的是，图1中的起飞区域、集结区域、无人机集群包括的无人机个数、无人机在起飞区域内的摆放位置、目标位置的个数及目标位置在集结区域内的分布位置仅仅是示意性的。根据实现需要，可以具有任意位置的起飞区域、集结区域，任意个数的无人机及目标位置。
图2示意性示出了根据本公开实施例的无人机集群的起飞控制方法的流程图。
如图2所示，本公开实施例的无人机集群的起飞控制方法包括操作S210～操作S240。
其中，无人机集群可以包括位于起飞区域的多架无人机，例如包括位于参考图1的起飞区域10中的无人机101～105。相应地，在执行操作S210之前，例如还可以由工作人员将无人机摆放至起飞区域内。其中，在对无人机进行摆放时，具体可以根据起飞场地的情况，选定起飞区域，并将多架无人机尽可能均匀的摆放至该选定的起飞区域内。其中，摆放后相邻两架无人机的距离只要能够满足无人机起飞的最低要求即可，例如任意相邻的两架无人机之间的间隔为0.5m～1m。
在操作S210，获取多架无人机在起飞区域内的起飞位置。
根据本公开的实施例，多架无人机的起飞位置具体可以是由人工测量得到，该测量具体可以是以某一位置作为坐标原点，测量得到多架无人机位置的坐标值，其中第i架无人机的坐标值可以表示为p i(x i，y i，z i)。
根据本公开的实施例，为了进一步减少人工工作耗时，该多架无人机的起飞位置具体还可以由定位系统自动检测得到。则该操作S210具体可以是先将多架无人机开机，使该多架无人机保持起飞待机状态。然后通过无人机的GPS定位功能，地面站利用通信链路获取得到无人机的起飞GPS 定位信息。其中，第i架无人机的定位信息例如可以包括无人机的经度、维度及高度，具体例如可以表示为p i(lon i，lat i，h i)。
根据本公开的实施例，为了便于后续处理，在得到无人机的起飞GPS定位信息后，例如还可以将该定位信息转换为直角坐标表示，以便于后续目标位置的确定，具体详见参考图3的描述。
在操作S220，获取与起飞区域对应的集结区域，该集结区域包括多个目标位置。
根据本公开的实施例，通常情况下，为了便于统一管理及为了保证集结的顺利执行，每个起飞场地都对应有预先设定的集结区域。该集结区域具体可以是在起飞区域上方一定高度处，与起飞区域具有一定水平偏移的区域。因此，当确定起飞场地后，即可确定集结区域。上述操作S220具体即为根据起飞区域所在的位置(例如经度、维度及高度等能唯一表示该起飞区域的位置信息)，确定对应的集结区域。
根据本公开的实施例，上述集结区域中包括有多个目标位置。考虑到在对无人机集群的起飞进行控制之前，已经预先确定了编队任务。且对于确定的编队任务，预先设定有适当的集结形状。因此，上述操作S220还可以包括根据编队任务确定集结形状，并根据集结形状确定集结区域中的多个目标位置的操作。
根据本公开的实施例，该多个目标位置中第i个目标位置具体可以通过标号R i来表示，该第i个目标位置的坐标值具体例如可以以地面中的某一点作为原点来表示。更具体地，为了便于后续的起飞控制，该目标位置例如可以与无人机的起飞位置采用同一坐标系来表示，本公开对此不作限定。
在操作S230，根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置。
根据本公开的实施例，为了为编队任务的执行提供条件，在多架无人机飞至集结区域时，多架无人机中的每架无人机应该与多个目标位置中的一个目标位置唯一对应，以使得多架无人机在集结区域内摆成适当的集结形状。因此，通过操作S230可以将起飞位置与目标位置一一对应起来，即确定每架无人机唯一的目标位置。
根据本公开的实施例，考虑到多架无人机在起飞过程中可能会存在碰撞的情况。因此，在上述操作S230确定每架无人机的目标位置时，应使得多架无人机的起飞位置与对应的目标位置的连线不相交。
根据本公开的实施例，考虑到无人机在飞行过程中可使用的能量是恒定的。为了编队任务的顺利进行，在上述操作S230确定每架无人机的目标位置时，应尽量使得多架无人机在自起飞位置飞至目标位置时的飞行路径总长相差不大。且应尽可能使得该多架无人机在自起飞位置飞至目标位置时的飞行路径的平均长度较小。
根据本公开的实施例，上述操作S230在确定无人机的目标位置时，具体可以根据实际需求考虑不同的因素，并采用不同的方法确定目标位置，本公开对此不作限定。例如上述操作S230具体可以采用参考图4描述的方法，在此不再详述。
在操作S240，根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞。
在确定了无人机的起飞位置及目标位置后，即可设定每架无人机的飞行轨迹及起飞时间，并控制无人机在设定的起飞时间根据飞行轨迹飞行。因此，上述操作S240具体可以先根据每架无人机的起飞位置及目标位置，确定每架无人机的飞行轨迹。
根据本公开的实施例，考虑到即使飞行轨迹没有交叉，在两架无人机起飞过程中，也有可能由于距离过近而在相互作用力下偏离轨迹并碰撞。因此，操作S240在确定了飞行轨迹后，还可以根据飞行轨迹确定起飞时间，以使得可能碰撞的两架无人机在不同时间点起飞。最后根据确定的起飞时间及飞行轨迹，控制多架无人机起飞，使得多架无人机在集结区域集结，并摆成预设的形状。根据本公开的实施例，上述操作S240的具体实现方式例如可以参考图5～图6B的描述，在此不再详述。
综上可知，本公开实施例的无人机集群的起飞控制方法，并非使无人机根据预设脚本轨迹向预定的目标位置起飞。而是实时根据无人机的起飞位置确定目标位置，再根据确定的目标位置控制无人机的起飞。从而可以减少无人机摆放的限制条件，例如无需预先将无人机摆放至预定位置，也无需为无人机预先分配编号。可以有效降低工作人员的工作耗时，且可以 避免因无人机摆放错误导致的两架无人机碰撞的情况发生。因此可以有效保证编队任务的顺利执行。再者，由于减少了无人机摆放的限制条件，因此也可以在一定程度上降低对起飞场地的空间、环境等条件的要求，降低编队任务执行难度。
图3示意性示出了根据本公开实施例的获取无人机的起飞位置的流程图。
如图3所示，操作S210中获取无人机的起飞位置的流程具体可以包括操作S311～操作S313。
在操作S311，获取多架无人机在起飞区域内的定位信息。
根据本公开的实施例，该操作S311获取的无人机在起飞区域内的定位信息具体可以是GPS定位信息，该GPS定位信息具体可以是由地面站利用通信链路获取的。该GPS定位信息包括无人机的经度、维度及高度。假设多架无人机的个数为M，则操作S211可以总共收集M组不同的定位信息，其中第i组定位信息可以记为p i(lon i，lat i，h i)，其中lon i表示经度值，lat i表示纬度值，h i表示高度值。
根据本公开的实施例，为了便于获取定位信息，在执行操作S311之前，例如还可以先控制多架无人机开机并保持起飞待机状态，以开启无人机的GPS定位功能。
在操作S312，确定起飞区域中的坐标原点；在操作S313，根据转换规则，将多架无人机在起飞区域内的定位信息转换为相对坐标原点的相对位置信息。该相对位置信息可以用于表征多架无人机在起飞区域内的起飞位置。
根据本公开的实施例，通过操作S312～操作S313，定位信息p i(lon i，lat i，h i)例如可以转换为p i(x i，y i，z i)。即通过操作S312～操作S313，可以将无人机的全局位置坐标转换为相对坐标原点的局部坐标，以利于操作S230中无人机目标位置的确定。
根据本公开的实施例，操作S230中的转换规则具体可以是将全局坐标转换为直角坐标的转换规则。该转换规则具体例如可以由以下的公式(1)～公式(3)表示：
x i＝K[cos(lat ref)*sin(lat i)-sin(lat ref)*cos(lat i)*cos(lon i-lon ref)]R e；  (1)
y i＝Kcos(lat i)sin(lon i-lon ref)*R e；     (2)
z i＝-(h i-h ref)；         (3)
其中，
Figure PCTCN2020071995-appb-000001
c＝sin(lat ref)sin(lat i)+cos(lat ref)cos(lat i)cos(lon i-lon ref)；   (5)
其中，lat ref、lon ref及h ref分别为坐标原点的经度值、纬度值及高度值。
图4示意性示出了根据本公开实施例的确定每架无人机的目标位置的流程图。
如图4所示，操作S230中确定无人机的目标位置的流程具体可以包括操作S431～操作S434。
在操作S431，根据多架无人机的起飞位置及多个目标位置，建立二分图。
根据本公开的实施例，操作S431具体即为：将多个起飞位置作为一个点集，将多个目标位置作为一个点集，在该两个点集之间构建二分图，使得每条边的两个端点中，一个端点为起飞位置，另一个端点为目标位置。具体地，若记多个起飞位置的坐标值组成的集合为S，记多个目标位置的坐标值组成的集合为R，则构建的二分图中，第i个起飞位置与第j个目标位置连成的边即可表示为V ij。
根据本公开的实施例，为了保证多架无人机的飞行距离的总和的值最小，且每架无人机唯一的对应有一个目标位置，操作S431中建立的二分图具体可以是带权完全二分图，其中权值取起飞位置与目标位置之间距离的相反数，具体即为边V ij的长度的相反数。
在操作S432，根据多架无人机的起飞位置及多个目标位置，确定每架无人机相对于多个目标位置的飞行距离。
根据本公开的实施例，该操作S432具体可以是：逐起飞位置的计算每个起飞位置与多个目标位置中每个目标位置之间的距离，得到多个距离值。假设起飞位置与目标位置均为M个，则计算得到的距离值的个数为M 2个。
根据本公开的实施例，为了便于计算飞行距离，此处的起飞位置的坐标值与目标位置的坐标值例如可以是基于同一坐标系表示的。例如，在起飞位置的坐标值是参考图3中操作S313转换得到的局部坐标的情况下， 操作S220中获取的多个目标位置的坐标值也是相对于操作S312中的坐标原点的局部坐标。
在操作S433中，根据每架无人机相对于多个目标位置的飞行距离，对二分图进行最大权匹配计算，得到计算结果；在操作S434中，根据计算结果，确定每架无人机的目标位置。
根据本公开的实施例，操作S433具体例如可以是采用KM算法(Kuhn-Munkres算法)，以求二分图在完备匹配下的最大权匹配，以使所有匹配的边的权值和最大。考虑到权值为边V ij的长度的相反数，则采用KM算法进行最大权匹配计算，得到的计算结果为距离和最小的结果，即该计算结果能够使得多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
根据本公开的实施例，由于求二分图在完备匹配下的最大权匹配得到的计算结果能够给集合S中的每一个点在集合R中分配一个对应点，因此计算结果可以确定起飞位置与目标位置的对应关系。再者，由于起飞位置唯一代表一架无人机，因此根据该计算结果，可直接地确定得到每架无人机的目标位置。
综上可知，通过上述操作S431～操作S434，可以使得多架无人机的起飞位置至对应的目标位置之间的距离和最小，从而可以节约利用无人机存储的电能。再者，由于采用KM算法进行最大权匹配计算，因此可以保证多架无人机自起飞位置至目标位置的连线没有交叉，从而可以在一定程度上避免无人机起飞过程中的碰撞。
图5示意性示出了根据本公开实施例的控制无人机起飞的流程图。
如图5所示，操作S240中控制多架无人机起飞的流程具体可以包括操作S541～操作S544。
在操作S541，根据每架无人机的起飞位置及每架无人机的目标位置，确定每架无人机的飞行轨迹。
根据本公开的实施例，为了保证每架无人机自起飞位置飞行至目标位置的总耗能最小，操作S541中确定的每架无人机的飞行轨迹具体例如可以是：每架无人机的起飞位置与目标位置的连线。
根据本公开的实施例，考虑到无人机的实际起飞一般为先升高至预定 高度后，再向目标位置飞行。则操作S541中确定的每架无人机的飞行轨迹具体可以是：起飞位置至该起飞位置上方预定高度处的预定位置的连线，以及预定位置至目标位置的连线组合形成的轨迹。此种情况下，为了保证为无人机确定的目标位置的准确性，还可以将该预定位置作为参考图4中操作S431中描述的起飞位置，在此不再赘述。
在操作S542，根据多架无人机中任意两架无人机的飞行轨迹，确定任意两架无人机的第一距离。其中，第一距离具体是任意两架无人机的飞行轨迹之间的最短距离。
在操作S543，根据任意两架无人机的第一距离，确定每架无人机的起飞时间。
根据本公开的实施例，该操作S543具体可以是，在两架无人机的第一距离小于预设距离的情况下，则为该两架无人机设定不同的起飞时间，以避免该两架无人机在飞往目标位置的过程中发生碰撞。而在两架无人机的第一距离不小于预设距离的情况下，则可以为该两架无人机设定相通的起飞时间，以提高多架无人机的集结效率。
根据本公开的实施例，该操作S543的具体实施例如还可以采用后续参考图6A～图6B描述的方法，在此不再详述。
在操作S544，根据每架无人机的起飞时间及每架无人机的飞行轨迹，控制每架无人机起飞，以使得多架无人机中的每架无人机在起飞时间按照飞行轨迹起飞并飞行。从而使得多架无人机能够飞至对应的目标位置，并在集结区域内摆成需求的形状。
图6A示意性示出了根据本公开实施例的确定多架无人机的起飞时间的流程图；图6B示意性示出了根据本公开实施例的将多架无人机划分为N个飞行组的流程图。
如图6A所示，参考图5中的操作S543具体可以包括操作S6431和操作S6432。
在操作S6431，根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，N为大于1的整数。在操作S6432，确定N个飞行组中每个飞行组的起飞时间。
根据本公开的实施例，在两架无人机的第一距离小于预设距离的情况 下，考虑到该两架无人机在飞往目标位置的过程中可能发生碰撞，则可以将该两架无人机划分至不同的飞行组，最终划分得到N个飞行组。通过向该N个飞行组分配不同的起飞时间，来有效避免无人机在飞行过程中碰撞情况的发生。其中，每个飞行组包括有至少一架无人机。
根据本公开的实施例，为了保证具有相同起飞时间的无人机不会发生碰撞，则还应使得属于同一飞行组的多架无人机中，任意两架无人机的第一距离均不小于预设距离。根据本公开的实施例，该预设距离具体例如可以是保障两架无人机不会碰撞的最小距离。
根据本公开的实施例，具体例如可以向N个飞行组中的第一个飞行组设定起飞时间t 1，后续第二个飞行组的起飞时间t 2＝t 1+T delay，其中T delay为第二个飞行组的起飞间相对第一个飞行组的起飞时间的延迟时间，依次类推，第i个飞行组的起飞时间可以表示为t i＝t 1+(i-1)T delay。具体地，此处T delay的取值可以根据实际需求进行设定。例如，可以以1s作为T delay的初始值，通过理论推算来确定若按照设定的起飞时间起飞，是否会存在碰撞的情况。若存在碰撞的情况，则适当的增大T delay的值，例如将T delay增大至1.5s，再通过理论推算来确定是否还存在碰撞情况。若仍旧存在碰撞情况，则再次增大T delay的值。依次类推，直至T delay的值能够保证不再存在碰撞情况为止。因此，该T delay具体可以是保证无人机集群起飞不存在碰撞情况的最小值，从而有效保证无人机集群的起飞效率。
根据本公开的实施例，如图6B所述，上述操作S6431将多架无人机划分为N个飞行组具体可以包括循环执行的操作S6431A～操作S6431E。
在操作S6431A，确定第i个飞行组包括的无人机个数。在操作S6431B，判断第i个飞行组包括的无人机个数是否大于1。其中，在第i个飞行组包括的无人机个数不大于1的情况下，由于该第i个飞行组包括的无人机按相同时间起飞不可能发生碰撞，则结束该循环。在第i个飞行组包括的无人机个数大于1的情况下，则需要确定该第i个飞行组包括的多架无人机按相同时间起飞是否存在碰撞的可能，因此执行操作S6431C：判断第i个飞行组中任意两架无人机的第一距离是否小于所述预设距离。在该第i个飞行组中不存在第一距离小于预设距离的两架无人机的情况下，说明该第i个飞行组中的多架无人机在相同时间起飞不可能发生碰撞，则继续对 第i+1个飞行组进行判断，即执行操作S6431E，将i置为i+1，并执行操作S6431F，判断第i个飞行组中是否包括无人机。若包括，则返回执行操作S6431A。若不包括，则完成多架无人机的划分。在该第i个飞行组中存在第一距离小于预设距离的两架无人机的情况下，则执行操作S6431D：将第一距离小于预设距离的两架无人机中的其中一架无人机划分至第i+1个飞行组，直至第i个飞行组中任意两架无人机的第一距离均不小于预设距离，则继续对第i+1个飞行组进行判断。即执行操作S6431E，将i置为i+1，并执行操作S6431F：判断该第i个飞行组是否包括无人机。若不包括，则完成多架无人机的划分，若包括，则返回执行操作S6431A。
根据本公开的实施例，记多架无人机中第m架无人机与第n架无人机之间的第一距离为D nm，预设距离为D min。则上述操作S6431具体还可以包括：步骤1、先判断D nm是否小于D min，若D nm＜D min，则说明该第m架无人机与第n架无人机在集结过程中存在碰撞风险，将该两架无人机的编号分别记录到两个起飞组I 1和I 2中。步骤2、更改m和n值后，重复步骤1，直至起飞组I 1中的任意两架无人机都不存在碰撞风险。步骤3、对起飞组I 2中的无人机再次进行判断和分配，形成起飞组I 2和I 3，并重复步骤1～步骤2，直至起飞组I 2中的任意两架无人机之间都不存在碰撞风险。依次类推，通过重复上述步骤1～3，形成起飞组I 1～I N，且该N个起飞组中的任意两架无人机都不存在碰撞风险。
需要说明的是，上述的i应该大于等于1且小于等于N。在执行操作S6431之前，即执行参考图6B中的循环操作之前，起飞区域内的多架无人机均应属于第1飞行组。若多架无人机的总数为M，则上述m和n应该均为大于等于1且小于等于M的自然数，且m≠n。
综上可知，本公开实施例通过参考图6A～图6B描述的确定多架无人机的起飞时间的方法，可以使得有碰撞可能的两架无人机在不同时间起飞。因此，可以有效避免在无人机集群起飞集结过程中碰撞事件的发生，并因此可以保证无人机集群的顺利集结及后续编队任务的顺利进行。
图7示意性示出了根据本公开实施例的无人机起飞后在集结区域集结的效果示意图。
本公开实施例还采用参考图2～图6B描述的方法对无人机集群的起飞 控制进行了模拟，模拟结果如图7所示，可以控制多架无人机710飞行至对应的目标位置720，并在包括多个目标位置720的集结区域形成如参考图7所示的“JD”字样。
经过模拟可知，本公开实施例的无人机集群的起飞控制方法，通过先将无人机目标位置的分配问题转换为一个二分图匹配问题进行求解，再根据实际飞行过程时的碰撞规避条件，利用延迟起飞的方式对起飞策略进行优化，可以在保证起飞效率的前提下有效地降低碰撞发生的风险。并因此有助于后续编队任务的顺利执行。
图8示意性示出了根据本公开实施例的无人机集群的起飞控制装置的结构框图。
如图8所示，本公开实施例的无人机集群的起飞控制装置800包括起飞位置获取模块810、集结区域获取模块820、目标位置确定模块830和起飞控制模块840。其中，无人机集群包括位于起飞区域的多架无人机，具体例如可以包括位于参考图1中的起飞区域10中的无人机101～105。
其中，起飞位置获取模块810用于获取多架无人机在起飞区域内的起飞位置。根据本公开的实施例，该起飞位置获取模块810例如可以通过设置于无人机101～105中的位置传感器来获取起飞位置。该起飞位置获取模块810例如可以用于执行参考图2描述的操作S210，在此不再赘述。
其中，集结区域获取模块820用于获取与起飞区域对应的集结区域，该集结区域包括多个目标位置。根据本公开的实施例，该集结区域获取模块820例如可以通过与服务器或云端系统的通信来获取得到集结区域，该集结区域例如可以与起飞区域一一对应。该集结区域获取模块820例如可以用于执行参考图2描述的操作S220，在此不再赘述。
其中，目标位置确定模块830用于根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置。根据本公开的实施例，该目标位置确定模块830例如可以为预先存储的程序指令，该程序指令通过被处理器运行来确定得到目标位置。该目标位置确定模块830例如可以用于执行参考图2描述的操作S230，在此不再赘述。
其中，起飞控制模块840用于根据多架无人机中每架无人机的起飞位置及每架无人机的目标位置，控制多架无人机起飞。根据本公开的实施例， 该起飞控制模块840例如可以通过与多架无人机的通信来控制多架无人机起飞。该起飞控制模块840例如可以用于执行参考图2描述的操作S240，在此不再赘述。
根据本公开的实施例，如图8所示，上述起飞位置获取模块810例如可以包括定位信息获取子模块811、坐标原点确定子模块812和转换子模块813。其中，定位信息获取子模块811用于获取多架无人机在起飞区域内的定位信息，该定位信息获取子模块811例如可以实现为设置于多架无人机中每架无人机的位置传感器等。坐标原点确定子模块812用于确定起飞区域中的坐标原点。转换子模块813用于根据转换规则，将多架无人机在起飞区域内的定位信息转换为相对坐标原点的相对位置信息。其中，该相对位置信息用于表征多架无人机在起飞区域内的起飞位置。根据本公开的实施例，坐标原点确定子模块812和转换子模块813例如可以实现为两条不同的程序指令或同一条程序指令，该程序指令通过被处理器运行实现前述的功能。定位信息获取子模块811、坐标原点确定子模块812和转换子模块813例如可以分别用于执行参考图3描述的操作S311～操作S313，在此不再赘述。
根据本公开的实施例，如图8所示，上述目标位置确定模块830例如可以包括二分图建立子模块831、飞行距离确定子模块832、计算子模块833和目标位置确定子模块834。其中，二分图建立子模块831用于根据多架无人机的起飞位置及多个目标位置，建立二分图。飞行距离确定子模块832用于根据多架无人机的起飞位置及多个目标位置，确定每架无人机相对于多个目标位置的飞行距离。计算子模块833用于根据每架无人机相对于多个目标位置的飞行距离，对二分图进行最大权匹配计算，得到计算结果。目标位置确定子模块834用于根据计算结果，确定每架无人机的目标位置。其中，所述计算结果用于使多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。根据本公开的实施例，二分图建立子模块831、飞行距离确定子模块832、计算子模块833和目标位置确定子模块834例如均可以实现为程序指令，该程序指令通过被处理器调用实现前述的功能。二分图建立子模块831、飞行距离确定子模块832、计算子模块833和目标位置确定子模块834例如可以分别用于执行参考图4描述的 操作S431～操作S434，在此不再赘述。
根据本公开的实施例，如图8所示，上述起飞控制模块840例如可以包括飞行轨迹确定子模块841、第一距离确定子模块842、起飞时间确定子模块843和起飞控制子模块844。其中，飞行轨迹确定子模块841用于根据每架无人机的起飞位置及每架无人机的目标位置，确定每架无人机的飞行轨迹。第一距离确定子模块842用于根据多架无人机中任意两架无人机的飞行轨迹，确定任意两架无人机的第一距离。起飞时间确定子模块843用于根据任意两架无人机的第一距离，确定每架无人机的起飞时间。起飞控制子模块844用于根据每架无人机的起飞时间及每架无人机的飞行轨迹，控制每架无人机起飞。其中，任意两架无人机的第一距离为任意两架无人机的飞行轨迹之间的最短距离。根据本公开的实施例，飞行轨迹确定子模块841、第一距离确定子模块842、起飞时间确定子模块843可以实现为程序指令，起飞控制子模块844例如可以实现为程序指令及与多架无人机通信的通信模块，以通过与多架无人机的通信，控制多架无人机起飞。飞行轨迹确定子模块841、第一距离确定子模块842、起飞时间确定子模块843和起飞控制子模块844例如可以分别用于执行参考图5描述的操作S541～操作S544，在此不再赘述。
根据本公开的实施例，如图8所示，上述起飞时间确定子模块843可以包括划分单元8431和确定单元8432。其中，划分单元8431用于根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，N为大于1的整数。确定单元8432用于确定N个飞行组中每个飞行组的起飞时间。其中，每个飞行组包括至少一架无人机，且在N个飞行组中的任一飞行组包括多架无人机的情况下，任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的至少一架无人机的起飞时间相同。根据本公开的实施例，划分单元8431和确定单元8432可以实现为程序指令。划分单元8431和确定单元8432例如可以分别用于执行参考图6A描述的操作S6431～操作S6432，在此不再赘述。
根据本公开的实施例，上述划分单元8431具体可以用于循环执行以下操作：确定第i个飞行组包括的无人机个数；在第i个飞行组包括的无 人机个数大于1的情况下，确定第i个飞行组中任意两架无人机的第一距离是否小于预设距离；在第i个飞行组中存在第一距离小于预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及在第i个飞行组中任意两架无人机的第一距离均不小于预设距离的情况下，将i置为i+1。其中，在循环执行以上操作之前，多架无人机均属于第1个飞行组，1≤i≤N。根据本公开的实施例，该划分单元8431具体例如可以用于执行参考图6B描述的操作S6431A～操作S6431E，在此不再赘述。
根据本公开的实施例的模块、子模块、单元、子单元中的任意多个、或其中任意多个的至少部分功能可以在一个模块中实现。根据本公开实施例的模块、子模块、单元、子单元中的任意一个或多个可以被拆分成多个模块来实现。根据本公开实施例的模块、子模块、单元、子单元中的任意一个或多个可以至少被部分地实现为硬件电路，例如现场可编程门阵列(FPGA)、可编程逻辑阵列(PLA)、片上系统、基板上的系统、封装上的系统、专用集成电路(ASIC)，或可以通过对电路进行集成或封装的任何其他的合理方式的硬件或固件来实现，或以软件、硬件以及固件三种实现方式中任意一种或以其中任意几种的适当组合来实现。或者，根据本公开实施例的模块、子模块、单元、子单元中的一个或多个可以至少被部分地实现为计算机程序模块，当该计算机程序模块被运行时，可以执行相应的功能。
例如，起飞位置获取模块810、集结区域获取模块820、目标位置确定模块830、起飞控制模块840、定位信息获取子模块811、坐标原点确定子模块812、转换子模块813、二分图建立子模块831、飞行距离确定子模块832、计算子模块833、目标位置确定子模块834、飞行轨迹确定子模块841、第一距离确定子模块842、起飞时间确定子模块843、起飞控制子模块844、划分单元8431以及确定单元8432中的任意多个可以合并在一个模块中实现，或者其中的任意一个模块可以被拆分成多个模块。或者，这些模块中的一个或多个模块的至少部分功能可以与其他模块的至少部分功能相结合，并在一个模块中实现。根据本公开的实施例，起飞位置获取模块810、集结区域获取模块820、目标位置确定模块830、起飞控制模块 840、定位信息获取子模块811、坐标原点确定子模块812、转换子模块813、二分图建立子模块831、飞行距离确定子模块832、计算子模块833、目标位置确定子模块834、飞行轨迹确定子模块841、第一距离确定子模块842、起飞时间确定子模块843、起飞控制子模块844、划分单元8431以及确定单元8432中的至少一个可以至少被部分地实现为硬件电路，例如现场可编程门阵列(FPGA)、可编程逻辑阵列(PLA)、片上系统、基板上的系统、封装上的系统、专用集成电路(ASIC)，或可以通过对电路进行集成或封装的任何其他的合理方式等硬件或固件来实现，或以软件、硬件以及固件三种实现方式中任意一种或以其中任意几种的适当组合来实现。或者，起飞位置获取模块810、集结区域获取模块820、目标位置确定模块830、起飞控制模块840、定位信息获取子模块811、坐标原点确定子模块812、转换子模块813、二分图建立子模块831、飞行距离确定子模块832、计算子模块833、目标位置确定子模块834、飞行轨迹确定子模块841、第一距离确定子模块842、起飞时间确定子模块843、起飞控制子模块844、划分单元8431以及确定单元8432中的至少一个可以至少被部分地实现为计算机程序模块，当该计算机程序模块被运行时，可以执行相应的功能。
图9示意性示出了根据本公开实施例的适于实现无人机集群的起飞控制方法的起飞控制系统的方框图。图9示出的起飞控制系统仅仅是一个示例，不应对本公开实施例的功能和使用范围带来任何限制。
如图9所示，根据本公开实施例的起飞控制系统900包括处理器901，其可以根据存储在只读存储器(ROM)902中的程序或者从存储部分908加载到随机访问存储器(RAM)903中的程序而执行各种适当的动作和处理。处理器901例如可以包括通用微处理器(例如CPU)、指令集处理器和/或相关芯片组和/或专用微处理器(例如，专用集成电路(ASIC))，等等。处理器901还可以包括用于缓存用途的板载存储器。处理器901可以包括用于执行根据本公开实施例的方法流程的不同动作的单一处理单元或者是多个处理单元。
在RAM 903中，存储有起飞控制系统900操作所需的各种程序和数据。处理器901、ROM 902以及RAM 903通过总线904彼此相连。处理器901通过执行ROM 902和/或RAM 903中的程序来执行根据本公开实施 例的方法流程的各种操作。需要注意，所述程序也可以存储在除ROM 902和RAM 903以外的一个或多个存储器中。处理器901也可以通过执行存储在所述一个或多个存储器中的程序来执行根据本公开实施例的方法流程的各种操作。
根据本公开的实施例，起飞控制系统900还可以包括输入/输出(I/O)接口905，输入/输出(I/O)接口905也连接至总线904。起飞控制系统900还可以包括连接至I/O接口905的以下部件中的一项或多项：包括键盘、鼠标等的输入部分906；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分907；包括硬盘等的存储部分908；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分909。通信部分909经由诸如因特网的网络执行通信处理。驱动器910也根据需要连接至I/O接口905。可拆卸介质911，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器910上，以便于从其上读出的计算机程序根据需要被安装入存储部分908。
根据本公开的实施例，根据本公开实施例的方法流程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读存储介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分909从网络上被下载和安装，和/或从可拆卸介质911被安装。在该计算机程序被处理器901执行时，执行本公开实施例的系统中限定的上述功能。根据本公开的实施例，上文描述的系统、设备、装置、模块、单元等可以通过计算机程序模块来实现。
本公开还提供了一种计算机可读存储介质，该计算机可读存储介质可以是上述实施例中描述的设备/装置/系统中所包含的；也可以是单独存在，而未装配入该设备/装置/系统中。上述计算机可读存储介质承载有一个或者多个程序，当上述一个或者多个程序被执行时，实现根据本公开实施例的方法。
根据本公开的实施例，计算机可读存储介质可以是非易失性的计算机可读存储介质，例如可以包括但不限于：便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器 (EPROM或闪存)、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本公开中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。例如，根据本公开的实施例，计算机可读存储介质可以包括上文描述的ROM 902和/或RAM 903和/或ROM 902和RAM 903以外的一个或多个存储器。
图10A示意性示出了根据本公开示例性实施例一的无人机集群系统的示意图，图10B示意性示出了根据本公开示例性实施例二的无人机集群系统的示意图。
如图10A～图10B所示，本公开实施例的无人机集群系统可以包括多架无人机及控制装置。该多架无人机的个数可以根据实际需求进行设定。在一实施例中，该多架无人机例如可以包括第一无人机～第M无人机共M架无人机。
在一实施例中，如图10A所示，控制装置1040可以设置于N架无人机中的任意一架无人机中，例如设置于第一无人机1010中。此种情况下，第二无人机1020～第M无人机1030均与第一无人机1010进行通信连接，以通过该通信连接接收控制装置1040发送的飞行信号。
在一实施例中，如图10B所示，该控制装置1040可以独立于第一无人机～第N无人机，设置于地面控制中心处。此种情况下，第一无人机1010’、第二无人机1020’～第M无人机1030’均与该地面控制中心处的控制装置1040通信连接，以通过该通信连接接收控制装置1040发送的飞行信号。
根据本公开的实施例，控制装置1040例如可以包括存储器1041和处理器1042。其中，存储器1041存储有一条或多条程序指令。处理器1042可以通过调用该一条或多条程序指令执行以下操作：根据多架无人机的定位信息，确定多架无人机在起飞区域内的起飞位置；获取与起飞区域对应的集结区域，该集结区域包括多个目标位置(操作S220)；根据多架无人机的起飞位置及多个目标位置，确定多架无人机中每架无人机的目标位置(操作S230)；以及根据每架无人机的起飞位置及每架无人机的目标位置，向每架无人机的控制器发送飞行信号。该飞行信号用于控制每架无人机飞行。
根据本公开的实施例，如图10A～图10B所示，多架无人机中的每架无人机包括传感器1001和控制器1002。其中，传感器1001例如可以为位置传感器或者全球定位系统(GPS)等，用于获取其所在的无人机的定位信息。控制器1002例如可以为飞控系统、或微处理器等，用于根据飞行信号控制其所在的无人机飞行。该传感器1001例如可以与控制装置1040中的处理器1042连接，以将获取的无人机的定位信息发送给处理器1042。控制器1002例如可以与控制装置1040中的处理器1042连接，以用于接收控制装置1040发送的飞行信号，并根据该飞行信号控制所在的无人机飞行。
根据本公开的实施例，处理器1042例如可以通过以下操作发送飞行信号：根据每架无人机的起飞位置及每架无人机的目标位置，确定每架无人机的飞行轨迹(操作S541)；根据多架无人机中任意两架无人机的飞行轨迹，确定任意两架无人机的第一距离(操作S542)；根据任意两架无人机的第一距离，确定每架无人机的起飞时间(操作S543)；以及根据每架无人机的起飞时间及每架无人机的飞行轨迹，向每架无人机发送飞行信号。中，任意两架无人机的第一距离为任意两架无人机的飞行轨迹之间的最短距离。飞行信号中包括该起飞时间和飞行轨迹。
根据本公开的实施例，处理器1042例如可以通过以下操作来确定每架无人机的起飞时间：根据任意两架无人机的第一距离，将多架无人机划分为N个飞行组，N为大于1的整数(操作S6431)；以及确定N个飞行组中每个飞行组的起飞时间(操作S6432)。其中，每个飞行组包括至少一架无人机，且在N个飞行组中任一飞行组包括多架无人机的情况下，任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的至少一架无人机的起飞时间相同。
根据本公开的实施例，处理器1042例如可以通过循环执行以下操作来将多架无人机划分为N个飞行组：确定第i个飞行组包括的无人机个数(操作S6431A)；在第i个飞行组包括的无人机个数大于1的情况下，确定第i个飞行组中任意两架无人机的第一距离是否小于预设距离(操作S6431C)；在第i个飞行组中存在第一距离小于预设距离的两架无人机的 情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组(操作S6431D)；以及在第i个飞行组中任意两架无人机的第一距离均不小于预设距离的情况下，将所述i置为i+1(操作S6431E)。其中，在循环执行以上操作之前，多架无人机均属于第1个飞行组，1≤i≤N。
根据本公开的实施例，处理器1042例如可以通过以下操作来确定多架无人机中每架无人机的目标位置：根据多架无人机的起飞位置及多个目标位置，建立二分图(操作S431)；根据多架无人机的起飞位置及多个目标位置，确定每架无人机相对于多个目标位置的飞行距离(操作S432)；根据每架无人机相对于多个目标位置的飞行距离，对二分图进行最大权匹配计算，得到计算结果(操作S433)；以及根据计算结果，确定每架无人机的目标位置(操作S434)。其中，计算结果用于使多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
根据本公开的实施例，处理器1042例如可以通过以下操作来确定多架无人机在起飞区域内的起飞位置：确定起飞区域中的坐标原点(操作S312)；以及根据转换规则，将多架无人机的定位信息转换为相对坐标原点的相对位置信息，该相对位置信息用于表征多架无人机在起飞区域内的起飞位置(操作S313)。
附图中的流程图和框图，图示了按照本公开各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图或流程图中的每个方框、以及框图或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
本领域技术人员可以理解，本公开的各个实施例和/或权利要求中记载的特征可以进行多种组合或/或结合，即使这样的组合或结合没有明确记载于本公开中。特别地，在不脱离本公开精神和教导的情况下，本公开的各 个实施例和/或权利要求中记载的特征可以进行多种组合和/或结合。所有这些组合和/或结合均落入本公开的范围。
以上对本公开的实施例进行了描述。但是，这些实施例仅仅是为了说明的目的，而并非为了限制本公开的范围。尽管在以上分别描述了各实施例，但是这并不意味着各个实施例中的措施不能有利地结合使用。本公开的范围由所附权利要求及其等同物限定。不脱离本公开的范围，本领域技术人员可以做出多种替代和修改，这些替代和修改都应落在本公开的范围之内。

Claims (21)

  1. 一种无人机集群的起飞控制方法，其中，所述无人机集群包括位于起飞区域的多架无人机，所述方法包括：
    获取所述多架无人机在所述起飞区域内的起飞位置；
    获取与所述起飞区域对应的集结区域，所述集结区域包括多个目标位置；
    根据所述多架无人机的起飞位置及所述多个目标位置，确定所述多架无人机中每架无人机的目标位置；以及
    根据所述多架无人机中每架无人机的起飞位置及所述每架无人机的目标位置，控制所述多架无人机起飞。
  2. 根据权利要求1所述的方法，其中，根据所述多架无人机中每架无人机的起飞位置及所述每架无人机的目标位置，控制所述多架无人机起飞包括：
    根据所述每架无人机的起飞位置及所述每架无人机的目标位置，确定所述每架无人机的飞行轨迹；
    根据所述多架无人机中任意两架无人机的飞行轨迹，确定所述任意两架无人机的第一距离；
    根据所述任意两架无人机的第一距离，确定所述每架无人机的起飞时间；以及
    根据所述每架无人机的起飞时间及所述每架无人机的飞行轨迹，控制所述每架无人机起飞，
    其中，所述任意两架无人机的第一距离为所述任意两架无人机的飞行轨迹之间的最短距离。
  3. 根据权利要求2所述的方法，其中，根据所述任意两架无人机的第一距离，确定所述每架无人机的起飞时间包括：
    根据所述任意两架无人机的第一距离，将所述多架无人机划分为N个飞行组，N为大于1的整数；以及
    确定所述N个飞行组中每个飞行组的起飞时间，
    其中，每个飞行组包括至少一架无人机，且在所述N个飞行组中的任 一飞行组包括多架无人机的情况下，所述任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的所述至少一架无人机的起飞时间相同。
  4. 根据权利要求3所述的方法，其中，根据所述任意两架无人机的第一距离，将所述多架无人机划分为N个飞行组，包括循环执行的以下操作：
    确定第i个飞行组包括的无人机个数；
    在所述第i个飞行组包括的无人机个数大于1的情况下，确定所述第i个飞行组中任意两架无人机的第一距离是否小于所述预设距离；
    在所述第i个飞行组中存在第一距离小于所述预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及
    在所述第i个飞行组中任意两架无人机的第一距离均不小于所述预设距离的情况下，将所述i置为i+1，
    其中，在循环执行以上操作之前，所述多架无人机均属于第1个飞行组，1≤i≤N。
  5. 根据权利要求1所述的方法，其中，根据所述多架无人机的起飞位置及所述多个目标位置，确定所述多架无人机中每架无人机的目标位置，包括：
    根据所述多架无人机的起飞位置及所述多个目标位置，建立二分图；
    根据所述多架无人机的起飞位置及所述多个目标位置，确定所述每架无人机相对于所述多个目标位置的飞行距离；
    根据所述每架无人机相对于所述多个目标位置的飞行距离，对所述二分图进行最大权匹配计算，得到计算结果；以及
    根据所述计算结果，确定所述每架无人机的目标位置，
    其中，所述计算结果用于使所述多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
  6. 根据权利要求1所述的方法，其中，获取所述多架无人机在所述起飞区域内的起飞位置包括：
    获取所述多架无人机在所述起飞区域内的定位信息；
    确定所述起飞区域中的坐标原点；以及
    根据转换规则，将所述多架无人机在所述起飞区域内的定位信息转换为相对所述坐标原点的相对位置信息，所述相对位置信息用于表征所述多架无人机在所述起飞区域内的起飞位置。
  7. 一种无人机集群的起飞控制装置，其中，所述无人机集群包括位于起飞区域的多架无人机，所述装置包括：
    起飞位置获取模块，用于获取所述多架无人机在所述起飞区域内的起飞位置；
    集结区域获取模块，用于获取与所述起飞区域对应的集结区域，所述集结区域包括多个目标位置；
    目标位置确定模块，用于根据所述多架无人机的起飞位置及所述多个目标位置，确定所述多架无人机中每架无人机的目标位置；以及
    起飞控制模块，用于根据所述多架无人机中每架无人机的起飞位置及所述每架无人机的目标位置，控制所述多架无人机起飞。
  8. 根据权利要求7所述的装置，其中，所述起飞控制模块包括：
    飞行轨迹确定子模块，用于根据所述每架无人机的起飞位置及所述每架无人机的目标位置，确定所述每架无人机的飞行轨迹；
    第一距离确定子模块，用于根据所述多架无人机中任意两架无人机的飞行轨迹，确定所述任意两架无人机的第一距离；
    起飞时间确定子模块，用于根据所述任意两架无人机的第一距离，确定所述每架无人机的起飞时间；以及
    起飞控制子模块，用于根据所述每架无人机的起飞时间及所述每架无人机的飞行轨迹，控制所述每架无人机起飞，
    其中，所述任意两架无人机的第一距离为所述任意两架无人机的飞行轨迹之间的最短距离。
  9. 根据权利要求8所述的装置，其中，所述起飞时间确定子模块包括：
    划分单元，用于根据所述任意两架无人机的第一距离，将所述多架无人机划分为N个飞行组，N为大于1的整数；以及
    确定单元，用于确定所述N个飞行组中每个飞行组的起飞时间，
    其中，每个飞行组包括至少一架无人机，且在所述N个飞行组中的任一飞行组包括多架无人机的情况下，所述任一飞行组包括的多架无人机中 任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的所述至少一架无人机的起飞时间相同。
  10. 根据权利要求9所述的装置，其中，所述划分单元具体用于循环执行以下操作：
    确定第i个飞行组包括的无人机个数；
    在所述第i个飞行组包括的无人机个数大于1的情况下，确定所述第i个飞行组中任意两架无人机的第一距离是否小于所述预设距离；
    在所述第i个飞行组中存在第一距离小于所述预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及
    在所述第i个飞行组中任意两架无人机的第一距离均不小于所述预设距离的情况下，将所述i置为i+1，
    其中，在循环执行以上操作之前，所述多架无人机均属于第1个飞行组，1≤i≤N。
  11. 根据权利要求7所述的装置，其中，所述目标位置确定模块包括：
    二分图建立子模块，用于根据所述多架无人机的起飞位置及所述多个目标位置，建立二分图；
    飞行距离确定子模块，用于根据所述多架无人机的起飞位置及所述多个目标位置，确定所述每架无人机相对于所述多个目标位置的飞行距离；
    计算子模块，用于根据所述每架无人机相对于所述多个目标位置的飞行距离，对所述二分图进行最大权匹配计算，得到计算结果；以及
    目标位置确定子模块，用于根据所述计算结果，确定所述每架无人机的目标位置，
    其中，所述计算结果用于使所述多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
  12. 根据权利要求7所述的装置，其中，所述起飞位置获取模块包括：
    定位信息获取子模块，用于获取所述多架无人机在所述起飞区域内的定位信息；
    坐标原点确定子模块，用于确定所述起飞区域中的坐标原点；以及
    转换子模块，用于根据转换规则，将所述多架无人机在所述起飞区域 内的定位信息转换为相对所述坐标原点的相对位置信息，所述相对位置信息用于表征所述多架无人机在所述起飞区域内的起飞位置。
  13. 一种无人机集群的起飞控制系统，包括：
    一个或多个处理器；
    存储装置，用于存储一个或多个程序，
    其中，当所述一个或多个程序分别被所述一个或多个处理器执行时，使得所述一个或多个处理器执行根据权利要求1～6中任意一项所述的方法。
  14. 一种计算机可读介质，其上存储有可执行指令，该指令被处理器执行时使处理器执行权利要求1～6中任意一项所述的方法。
  15. 一种无人机集群系统，包括：
    多架无人机，每架无人机包括：
    传感器，用于获取其所在的无人机的定位信息；
    控制器，用于根据飞行信号控制其所在的无人机飞行；
    控制装置，包括：
    存储器，存储有一条或多条程序指令；以及
    处理器，用于根据所述一条或多条程序指令执行以下操作：
    根据所述多架无人机的定位信息，确定所述多架无人机在起飞区域内的起飞位置；
    获取与所述起飞区域对应的集结区域，所述集结区域包括多个目标位置；
    根据所述多架无人机的起飞位置及所述多个目标位置，确定所述多架无人机中每架无人机的目标位置；以及
    根据所述每架无人机的起飞位置及所述每架无人机的目标位置，向所述每架无人机的控制器发送飞行信号。
  16. 根据权利要求15所述的系统，其中，所述处理器用于通过执行以下操作发送所述飞行信号：
    根据所述每架无人机的起飞位置及所述每架无人机的目标位置，确定所述每架无人机的飞行轨迹；
    根据所述多架无人机中任意两架无人机的飞行轨迹，确定所述任意两架无人机的第一距离；
    根据所述任意两架无人机的第一距离，确定所述每架无人机的起飞时间；以及
    根据所述每架无人机的起飞时间及所述每架无人机的飞行轨迹，向所述每架无人机发送飞行信号，
    其中，所述任意两架无人机的第一距离为所述任意两架无人机的飞行轨迹之间的最短距离。
  17. 根据权利要求16所述的系统，其中，所述根据所述任意两架无人机的第一距离，确定所述每架无人机的起飞时间包括：
    根据所述任意两架无人机的第一距离，将所述多架无人机划分为N个飞行组，N为大于1的整数；以及
    确定所述N个飞行组中每个飞行组的起飞时间，
    其中，每个飞行组包括至少一架无人机，且在所述N个飞行组中任一飞行组包括多架无人机的情况下，所述任一飞行组包括的多架无人机中任意两架无人机的第一距离不小于预设距离；不同飞行组的起飞时间不同，且每个飞行组包括的所述至少一架无人机的起飞时间相同。
  18. 根据权利要求17所述的系统，其中，所述根据所述任意两架无人机的第一距离，将所述多架无人机划分为N个飞行组，包括循环执行的以下操作：
    确定第i个飞行组包括的无人机个数；
    在所述第i个飞行组包括的无人机个数大于1的情况下，确定所述第i个飞行组中任意两架无人机的第一距离是否小于所述预设距离；
    在所述第i个飞行组中存在第一距离小于所述预设距离的两架无人机的情况下，将该两架无人机中的其中一架无人机划分至第i+1个飞行组；以及
    在所述第i个飞行组中任意两架无人机的第一距离均不小于所述预设距离的情况下，将所述i置为i+1，
    其中，在循环执行以上操作之前，所述多架无人机均属于第1个飞行组，1≤i≤N。
  19. 根据权利要求15所述的系统，其中，所述根据所述多架无人机的起飞位置及所述多个目标位置，确定所述多架无人机中每架无人机的目标 位置，包括：
    根据所述多架无人机的起飞位置及所述多个目标位置，建立二分图；
    根据所述多架无人机的起飞位置及所述多个目标位置，确定所述每架无人机相对于所述多个目标位置的飞行距离；
    根据所述每架无人机相对于所述多个目标位置的飞行距离，对所述二分图进行最大权匹配计算，得到计算结果；以及
    根据所述计算结果，确定所述每架无人机的目标位置，
    其中，所述计算结果用于使所述多架无人机中每架无人机相对于确定的目标位置的飞行距离的和最小。
  20. 根据权利要求15所述的系统，其中，所述根据所述多架无人机的定位信息，确定所述多架无人机在起飞区域内的起飞位置包括：
    确定所述起飞区域中的坐标原点；以及
    根据转换规则，将所述多架无人机的定位信息转换为相对所述坐标原点的相对位置信息，所述相对位置信息用于表征所述多架无人机在所述起飞区域内的起飞位置。
  21. 根据权利要求15所述的系统，其中：所述控制装置设置于所述多架无人机中的任意一架无人机中。
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