CN113759973A - Target search control method and system for unmanned aerial vehicle cluster - Google Patents

Target search control method and system for unmanned aerial vehicle cluster Download PDF

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CN113759973A
CN113759973A CN202111070633.6A CN202111070633A CN113759973A CN 113759973 A CN113759973 A CN 113759973A CN 202111070633 A CN202111070633 A CN 202111070633A CN 113759973 A CN113759973 A CN 113759973A
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unmanned aerial
aerial vehicle
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leader
speed
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CN113759973B (en
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范衠
王琛
邝文希
谷敏强
李文姬
王诏君
李冲
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Shantou University
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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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The invention relates to the technical field of unmanned aerial vehicles, in particular to a target search control method and a target search control system for an unmanned aerial vehicle cluster, wherein the method comprises the following steps: each unmanned aerial vehicle in the unmanned aerial vehicle cluster shares the priority and the current position of the unmanned aerial vehicle in real time through broadcasting; the method comprises the steps that a cluster leader of an unmanned aerial vehicle cluster at the current moment determines the current position of a virtual leader in real time, and broadcasts the current position of the virtual leader in the unmanned aerial vehicle cluster in real time; determining the control speed of the unmanned aerial vehicle according to the first distance, the second distance and the third distance of the unmanned aerial vehicle by the unmanned aerial vehicle in the unmanned aerial vehicle cluster; the unmanned aerial vehicles in the unmanned aerial vehicle cluster traverse the search area along with the virtual leader according to the control speed so as to perform cluster search on the target on the premise of avoiding collision of the unmanned aerial vehicles in the unmanned aerial vehicle cluster; the invention realizes the autonomous and efficient search of the unmanned aerial vehicle group for the search area.

Description

Target search control method and system for unmanned aerial vehicle cluster
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a target search control method and a target search control system for an unmanned aerial vehicle cluster.
Background
The unmanned aerial vehicle autonomous cluster search means that an unmanned aerial vehicle cluster flies in the air in a cluster state, and a search task is executed by cluster cooperation.
In the prior art, a group unmanned aerial vehicle searching method mainly searches targets under the control of a central node, namely, the behavior of an unmanned aerial vehicle is controlled by a ground workbench, once a ground base station is destroyed, an unmanned aerial vehicle group loses the capability of executing related tasks, the working range of the unmanned aerial vehicle group is strictly limited due to the relationship of ground control nodes, tasks can be executed only in the communication range of ground control points, and the unmanned aerial vehicle does not have the function of autonomous cluster searching.
Secondly, the existing cluster searching means mostly depends on marking environmental information to improve searching efficiency, which directly results in stronger dependence on computing power of a sensor and a main control chip and poor real-time performance of the existing technical scheme.
Disclosure of Invention
The invention aims to provide a target search control method and a target search control system for an unmanned aerial vehicle cluster, which are used for solving one or more technical problems in the prior art and at least providing a beneficial selection or creation condition.
In order to achieve the purpose, the invention provides the following technical scheme:
a method of target search control for a cluster of drones, the method comprising the steps of:
s100, sharing the priority and the current position of each unmanned aerial vehicle in the unmanned aerial vehicle cluster in real time through broadcasting;
step S200, determining the current position of a virtual leader in real time by a cluster leader of the unmanned aerial vehicle cluster at the current moment, and broadcasting the current position of the virtual leader in real time in the unmanned aerial vehicle cluster;
the cluster leader is an unmanned aerial vehicle with the highest priority in the unmanned aerial vehicle cluster; the virtual leader is set by the cluster leader;
step S300, determining the control speed of the unmanned aerial vehicle according to the first distance, the second distance and the third distance of the unmanned aerial vehicle by the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
the first distance is determined according to the current position of the unmanned aerial vehicle and the current positions of other unmanned aerial vehicles in the unmanned aerial vehicle cluster; the second distance is determined according to the current position of the unmanned aerial vehicle and the current position of the virtual leader; the third distance is the shortest distance between the current position of the unmanned aerial vehicle and the field boundary of the search area;
and S400, the unmanned aerial vehicles in the unmanned aerial vehicle cluster traverse the search area along with the virtual leader according to the control speed so as to perform cluster search on the targets on the premise of avoiding collision of the unmanned aerial vehicles in the unmanned aerial vehicle cluster.
Further, in step S200, the determining, by the cluster leader of the unmanned aerial vehicle cluster at the current time, the current position of the virtual leader in real time includes:
the cluster leader adopts a Levy flight algorithm to determine the current position of the virtual leader in real time, so that the virtual leader traverses a search area and broadcasts the current position of the virtual leader in real time in an unmanned aerial vehicle cluster; wherein the virtual leader is located at an arbitrary position within the search area at an initial time of the search target.
Further, the method further comprises:
determining in real-time whether the cluster leader is down;
and under the condition that the cluster leader is damaged, taking the unmanned aerial vehicle with the priority next to the cluster leader in the unmanned aerial vehicle cluster as a new cluster leader.
Further, in step S300, determining the control speed of the unmanned aerial vehicle in the unmanned aerial vehicle cluster according to the first distance, the second distance, and the third distance of the unmanned aerial vehicle includes:
unmanned aerial vehicles in the unmanned aerial vehicle cluster acquire a first distance, a second distance and a third distance of the unmanned aerial vehicle;
determining a first speed of an unmanned aerial vehicle in the unmanned aerial vehicle cluster according to a first distance of the unmanned aerial vehicle;
determining a second speed of the unmanned aerial vehicle according to a second distance of the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
determining a third speed of the unmanned aerial vehicle according to a third distance of the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
and determining the control speed of the unmanned aerial vehicle according to the first speed, the second speed and the third speed of the unmanned aerial vehicle.
Further, the control speed of the unmanned aerial vehicle is calculated by adopting the following formula:
Figure BDA0003260110740000021
Figure BDA0003260110740000022
wherein,
Figure BDA0003260110740000023
representing the theoretical speed of the ith drone,
Figure BDA0003260110740000024
indicating the control speed, v, of the ith unmanned plane at the current momentlimitRepresenting the speed cut-off value of the drone,
Figure BDA0003260110740000025
representing a first speed, v, of the ith droneliRepresenting a second speed of the ith drone,
Figure BDA0003260110740000026
is the third speed of the ith drone.
Further, the first speed of the unmanned aerial vehicle is calculated by adopting the following formula:
Figure BDA0003260110740000027
Figure BDA0003260110740000028
wherein,
Figure BDA0003260110740000029
representing a first speed, r, of the ith drone0 repDenotes a first distance threshold, riIndicating the current position of the ith drone, rjIndicates the current position of the jth drone, rijRepresenting a first distance, r, of the ith drone from the jth droneij＝|ri-rj|，CrepIs a first gain factor to be used for the first,
Figure BDA0003260110740000031
indicating that the ith drone is subject to a first repelling velocity created by the jth drone.
Further, the second speed of the unmanned aerial vehicle is calculated by adopting the following formula:
Figure BDA0003260110740000032
Figure BDA0003260110740000033
Figure BDA0003260110740000034
wherein v isliIndicating a second speed, r, of the ith droneileaderRepresenting a second distance, r, of the ith drone from the virtual leaderileader＝|rleader-ri|，riIndicating the current position of the ith drone, rleaderRepresents the current location of the virtual leader,afollow，pfollowa second gain coefficient respectively representing the maximum acceleration and braking curve of the unmanned aerial vehicle in the unmanned aerial vehicle cluster when the unmanned aerial vehicle approaches the virtual leader, CfollowA velocity component adjustment coefficient, v, representing a trend of drones in said drone swarm towards a virtual leaderfRepresenting an initial velocity at which drones in the drone swarm track a virtual leader, D (r, a, p) being a velocity decay function.
Further, the third speed of the unmanned aerial vehicle is calculated by adopting the following formula:
Figure BDA0003260110740000035
Figure BDA0003260110740000036
Figure BDA0003260110740000037
wherein,
Figure BDA0003260110740000038
third speed, r, for the ith dronesIs a point which is positioned on the boundary of the field and is closest to the unmanned aerial vehicle, and is used as the position of the virtual agent, risIs the shortest distance between the ith unmanned aerial vehicle and the field boundary, ris＝|ri-rs|；rwallIs a safe distance between the unmanned aerial vehicle and the field boundary, vsAs a virtual velocity vector of a virtual agent, virtual velocity vsIs perpendicular to the field boundary where the virtual agent is located and points to the field viVelocity vector, v, for the ith droneisMagnitude is the norm, v, of the vector difference between the velocity vector of the ith drone and the virtual velocity vector of the virtual agentis＝|vi-vs|；CshillTo be an adjustable factor, ashill、pshillIs a tunable ginsengAnd (4) counting.
A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, realizes the steps of the method for target search control of a cluster of drones as defined in any of the previous claims.
A target search control system for a cluster of drones, the system comprising:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor is enabled to implement any one of the above methods for controlling target search of a cluster of drones.
The invention has the beneficial effects that: the invention discloses a target search control method and a target search control system for an unmanned aerial vehicle cluster, which are used for the unmanned aerial vehicle autonomous cluster to execute a search task, ground central control nodes are not needed, the distance between the unmanned aerial vehicle autonomous cluster and the central control nodes is not limited, and the area for executing the task is flexible; the search process does not depend on marking environmental information, does not have strong dependence on the sensor, is simple to deploy, and can avoid collision between unmanned aerial vehicles when the unmanned aerial vehicles search for the target.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a target search control method of an unmanned aerial vehicle cluster in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a simulation of a stage in which an unmanned aerial vehicle starts to search for a target according to an embodiment of the present invention;
fig. 3 is a schematic diagram of determining the control speed of the drone in an embodiment of the present invention.
Detailed Description
The conception, specific structure and technical effects of the present application will be described clearly and completely with reference to the following embodiments and the accompanying drawings, so that the purpose, scheme and effects of the present application can be fully understood. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Referring to fig. 1 and fig. 2, as shown in fig. 1, a method for controlling target search of an unmanned aerial vehicle cluster according to an embodiment of the present application, the method includes the following steps:
s100, sharing the priority and the current position of each unmanned aerial vehicle in the unmanned aerial vehicle cluster in real time through broadcasting;
step S200, determining the current position of a virtual leader in real time by a cluster leader of the unmanned aerial vehicle cluster at the current moment, and broadcasting the current position of the virtual leader in real time in the unmanned aerial vehicle cluster;
the cluster leader is an unmanned aerial vehicle with the highest priority in the unmanned aerial vehicle cluster; the virtual leader is set by the cluster leader;
step S300, determining the control speed of the unmanned aerial vehicle according to the first distance, the second distance and the third distance of the unmanned aerial vehicle by the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
the first distance is determined according to the current position of the unmanned aerial vehicle and the current positions of other unmanned aerial vehicles in the unmanned aerial vehicle cluster; the second distance is determined according to the current position of the unmanned aerial vehicle and the current position of the virtual leader; the third distance is the shortest distance between the current position of the unmanned aerial vehicle and the field boundary of the search area;
and S400, the unmanned aerial vehicles in the unmanned aerial vehicle cluster traverse the search area along with the virtual leader according to the control speed so as to perform cluster search on the targets on the premise of avoiding collision of the unmanned aerial vehicles in the unmanned aerial vehicle cluster.
It should be noted that, in the analysis of the inventor in the background art, the related research of the cluster search of the unmanned aerial vehicle mostly depends on marking the environmental information by using, for example, an pheromone model, so that the high efficiency of the cluster search of the unmanned aerial vehicle is realized as much as possible, and the capability of the unmanned aerial vehicle with a sensor is ignored.
In the embodiment provided by the invention, each unmanned aerial vehicle in the unmanned aerial vehicle cluster has a specific priority (for example, a preset priority), and the unmanned aerial vehicle with the highest priority at a certain time serves as a cluster leader. The virtual leader is arranged in the unmanned aerial vehicle cluster, the initial position of the virtual leader is located at any position in a search area, the position of the virtual leader is calculated by the leader, and the unmanned aerial vehicle cluster shares self priority and self position in real time through broadcasting, so that the unmanned aerial vehicle cluster follows the virtual leader to traverse the search area, and during the period, the unmanned aerial vehicle in the unmanned aerial vehicle cluster determines the control speed of the unmanned aerial vehicle according to the first distance, the second distance and the third distance of the unmanned aerial vehicle, so that collision of the unmanned aerial vehicle in the unmanned aerial vehicle cluster is avoided, and the unmanned aerial vehicle cluster keeps a cluster state to search targets.
As a further improvement of the foregoing embodiment, in step S200, the determining, by the cluster leader of the unmanned cluster at the current time, the current position of the virtual leader in real time includes:
the cluster leader adopts a Levy flight algorithm to determine the current position of the virtual leader in real time, so that the virtual leader traverses a search area and broadcasts the current position of the virtual leader in real time in an unmanned aerial vehicle cluster;
wherein the virtual leader is located at an arbitrary position within the search area at an initial time of the search target.
It should be noted that the leader is not different from other unmanned aerial vehicles in the unmanned aerial vehicle cluster except for calculating and broadcasting the position of the virtual leader.
In some embodiments, the step size of the virtual leader performing the lave flight is calculated by using the following formula:
Figure BDA0003260110740000051
wherein z is the original step length, zsIs the virtual collarThe leader performs the step length of the Laiwei flight, i.e. the u and v obey the normal distribution of the step length after the original step length is adjusted, and the parameter beta is the value range of [0, 2 ]]In one embodiment, β ═ 1.5;
Figure BDA0003260110740000061
wherein,
Figure BDA0003260110740000062
x and t are independent variables.
In some embodiments, the scaling factor γ is always set to γ ═ 1; however, in an actual flight mission, the scale factor γ needs to be adjusted according to the environmental size, and may be set to γ ═ 47, for example.
In the embodiment provided by the invention, the unmanned aerial vehicle cluster does not depend on marking the environmental information and recording the traversed position in the searching process, and can realize the efficient traversal of the area only depending on the random step length.
As a further refinement of the above embodiment, the method further comprises:
determining in real-time whether the cluster leader is down;
determining remaining drones in the drone swarm in case of a crash of the swarm leader;
and automatically updating the unmanned aerial vehicle with the highest priority in the rest unmanned aerial vehicles as the cluster leader.
That is, in the event that the cluster leader fails, a drone in the drone cluster having a priority next to the cluster leader is treated as a new cluster leader.
In the embodiment provided by the invention, when the virtual leader traverses a certain area by a Levis flight algorithm, the position of the virtual leader is updated and broadcasted by the cluster leader in real time, the cluster leader is automatically updated under the condition that the cluster leader is damaged, and the cluster fault tolerance capability is strong; and the unmanned aerial vehicle in the unmanned aerial vehicle cluster carries out Levy flight motion along with the virtual leader according to the control speed, so that the effect of cluster target searching is achieved.
Referring to fig. 3, as a further improvement of the foregoing embodiment, in step S300, determining a control speed of each drone in the drone swarm according to the first distance, the second distance, and the third distance of the drone includes:
unmanned aerial vehicles in the unmanned aerial vehicle cluster acquire a first distance, a second distance and a third distance of the unmanned aerial vehicle;
determining a first speed of an unmanned aerial vehicle in the unmanned aerial vehicle cluster according to a first distance of the unmanned aerial vehicle;
determining a second speed of the unmanned aerial vehicle according to a second distance of the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
determining a third speed of the unmanned aerial vehicle according to a third distance of the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
and determining the control speed of the unmanned aerial vehicle according to the first speed, the second speed and the third speed of the unmanned aerial vehicle.
As a further improvement of the above embodiment, the first speed of the drone is calculated by using the following formula:
Figure BDA0003260110740000063
Figure BDA0003260110740000064
wherein,
Figure BDA0003260110740000071
representing a first speed, r, of the ith drone0 repDenotes a first distance threshold, riIndicating the current position of the ith drone, rjIndicates the current position of the jth drone, rijRepresenting a first distance, r, of the ith drone from the jth droneij＝|ri-rj|，CrepIs a first gain systemNumber, CrepHas a value range of [0.2,10.0 ]]In units of 1/s (fraction of a second),
Figure BDA0003260110740000072
indicating that the ith drone is subject to a first repelling velocity created by the jth drone.
It should be noted that the first distance threshold may be understood as a safe distance for the drones to fly, and if the distance between two drones in the group is smaller than the first distance threshold, the drones may generate a repelling speed in the opposite direction, that is, a first repelling speed, so that no collision occurs between the drones. Since the ith drone may receive repulsion from multiple individuals in the drone swarm, the first repulsion velocity of all drones needs to be considered to determine the first velocity of the drone.
As a further improvement of the above embodiment, the second speed of the drone is calculated using the following formula:
Figure BDA0003260110740000073
Figure BDA0003260110740000074
Figure BDA0003260110740000075
wherein v isliIndicating a second speed, r, of the ith droneileaderRepresenting a second distance, r, of the ith drone from the virtual leaderileader＝|rleader-ri|，riIndicating the current position of the ith drone, rleaderRepresenting the current position of the virtual leader, afollow，pfollowA second gain factor representing respectively the maximum acceleration and braking curve of the drone in said cluster when it approaches the virtual leader, afollowIs not only a sheetThe bit is m/s2、pfollowHas the unit of 1/s, CfollowA velocity component adjustment coefficient, v, representing a trend of drones in said drone swarm towards a virtual leaderfRepresenting an initial speed at which drones in the drone swarm track a virtual leader. D (r, a, p) is a smooth speed decay function, here as the braking curve of the drone to its desired stopping point.
It should be noted that, in the following description,
Figure BDA0003260110740000076
a direction vector representing the direction of the ith drone toward the virtual leader position, each drone in the cluster of drones having the same parameter afollow、pfollowAnd vf。
As a further improvement of the above embodiment, a calculation formula of the third speed of the unmanned aerial vehicle is:
Figure BDA0003260110740000077
Figure BDA0003260110740000081
Figure BDA0003260110740000082
wherein,
Figure BDA0003260110740000083
third speed, r, for the ith dronesIs a point which is positioned on the boundary of the field and is closest to the unmanned aerial vehicle, and is used as the position of the virtual agent, risIs the shortest distance between the ith unmanned aerial vehicle and the field boundary, ris＝|ri-rs|；rwallIs a safe distance between the unmanned aerial vehicle and the field boundary, vsAs a virtual velocity vector of a virtual agent, virtual velocity vsIs perpendicular to the virtualThe intelligent agent is positioned at the boundary of the place and points to the place, and the virtual intelligent agent does not generate displacement under the action of the virtual speed, so the virtual speed is called as the virtual speed. v. ofiVelocity vector, v, for the ith droneisMagnitude is the norm, v, of the vector difference between the velocity vector of the ith drone and the virtual velocity vector of the virtual agentis＝|vi-vs|；CshillTo be an adjustable factor, ashill、pshillFor adjustable parameters, ashillHas the unit of m/s2、pshillThe unit of (1/s). The speed of the unmanned aerial vehicle far away from the field boundary is calculated through the formula
Figure BDA0003260110740000084
In the direction of (v)i-vs)/vis。
As a further improvement of the above embodiment, the control speed of the drone is calculated by using the following formula:
Figure BDA0003260110740000085
Figure BDA0003260110740000086
wherein,
Figure BDA0003260110740000087
representing the theoretical speed of the ith drone,
Figure BDA0003260110740000088
indicating the control speed, v, of the ith unmanned plane at the current momentlimitRepresenting the speed cutoff of the drone.
In this embodiment, a speed cutoff value is introduced, and under the condition that the direction of the speed is not changed, if the calculated theoretical speed is greater than the speed cutoff value v of the unmanned aerial vehicle flightlimitSetting the control speed as the speed cut-off value, and keeping the direction to be consistent with the theoretical speedThus, the method can be used for the treatment of the tumor.
Compared with the prior art, the embodiment provided by the invention has the following advantages:
the virtual leader is arranged in an unmanned aerial vehicle cluster, the initial position of the virtual leader is located at any position in a search area, the virtual leader moves according to the step length of flight in a Lewy dimension, a group of unmanned aerial vehicles moves along with the virtual leader, the unmanned aerial vehicle with the highest priority in the group serves as the leader, the position of the virtual leader is calculated by the leader, the unmanned aerial vehicle cluster shares the priority and the position of the unmanned aerial vehicle by broadcasting in real time, if the leader is damaged, the unmanned aerial vehicle with the high priority becomes a new group leader again, the position of the virtual leader is updated and broadcasted continuously, the virtual leader is followed to traverse the search area, and during the period, the unmanned aerial vehicles mutually avoid by generating mutual repulsion speed when the distance is too close, the unmanned aerial vehicles keep a cluster state, and cluster target search is performed by the scheme. The unmanned aerial vehicle autonomous cluster high-efficiency target searching is achieved without depending on recording environment information.
Corresponding to the method of fig. 1, an embodiment of the present invention further provides a computer-readable storage medium, where an object search control program of a cluster of drones is stored on the computer-readable storage medium, and when executed by a processor, the method of the present invention as in any one of the above embodiments is implemented.
Corresponding to the method in fig. 1, an embodiment of the present invention further provides a target search control system for an unmanned aerial vehicle cluster, where the system includes:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor is enabled to implement the method for controlling target search of a cluster of drones according to any of the above embodiments.
The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiment, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method embodiment.
The Processor may be a Central-Processing Unit (CPU), other general-purpose Processor, a Digital Signal Processor (DSP), an Application-Specific-Integrated-Circuit (ASIC), a Field-Programmable Gate array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, or the like. The general processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor is a control center of the target search control system of the drone cluster, and various interfaces and lines are used to connect various parts of the target search control system operable device of the whole drone cluster.
The memory may be configured to store the computer program and/or module, and the processor may implement various functions of the target search control system of the drone cluster by executing or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart-Media-Card (SMC), a Secure-digital (SD) Card, a Flash-memory Card (Flash-Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
While the description of the present application has been made in considerable detail and with particular reference to a few illustrated embodiments, it is not intended to be limited to any such details or embodiments or any particular embodiments, but it is to be construed that the present application effectively covers the intended scope of the application by reference to the appended claims, which are interpreted in view of the broad potential of the prior art. Further, the foregoing describes the present application in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial changes from the present application, not presently foreseen, may nonetheless represent equivalents thereto.

Claims (10)

1. A target search control method for an unmanned aerial vehicle cluster is characterized by comprising the following steps:
s100, sharing the priority and the current position of each unmanned aerial vehicle in the unmanned aerial vehicle cluster in real time through broadcasting;
step S200, determining the current position of a virtual leader in real time by a cluster leader of the unmanned aerial vehicle cluster at the current moment, and broadcasting the current position of the virtual leader in real time in the unmanned aerial vehicle cluster;
the cluster leader is an unmanned aerial vehicle with the highest priority in the unmanned aerial vehicle cluster; the virtual leader is set by the cluster leader;
step S300, determining the control speed of the unmanned aerial vehicle according to the first distance, the second distance and the third distance of the unmanned aerial vehicle by the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
the first distance is determined according to the current position of the unmanned aerial vehicle and the current positions of other unmanned aerial vehicles in the unmanned aerial vehicle cluster; the second distance is determined according to the current position of the unmanned aerial vehicle and the current position of the virtual leader; the third distance is the shortest distance between the current position of the unmanned aerial vehicle and the field boundary of the search area;
and S400, the unmanned aerial vehicles in the unmanned aerial vehicle cluster traverse the search area along with the virtual leader according to the control speed so as to perform cluster search on the targets on the premise of avoiding collision of the unmanned aerial vehicles in the unmanned aerial vehicle cluster.
2. The method as claimed in claim 1, wherein in step S200, the determining, by the cluster leader of the unmanned aerial vehicle cluster at the current time, the current location of the virtual leader in real time includes:
the cluster leader adopts a Levy flight algorithm to determine the current position of the virtual leader in real time, so that the virtual leader traverses a search area and broadcasts the current position of the virtual leader in real time in an unmanned aerial vehicle cluster; wherein the virtual leader is located at an arbitrary position within the search area at an initial time of the search target.
3. The method of claim 2, wherein the method further comprises:
determining in real-time whether the cluster leader is down;
and under the condition that the cluster leader is damaged, taking the unmanned aerial vehicle with the priority next to the cluster leader in the unmanned aerial vehicle cluster as a new cluster leader.
4. The method of claim 1, wherein in step S300, the determining the control speed of the drone according to the first distance, the second distance, and the third distance of the drone includes:
unmanned aerial vehicles in the unmanned aerial vehicle cluster acquire a first distance, a second distance and a third distance of the unmanned aerial vehicle;
determining a first speed of an unmanned aerial vehicle in the unmanned aerial vehicle cluster according to a first distance of the unmanned aerial vehicle;
determining a second speed of the unmanned aerial vehicle according to a second distance of the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
determining a third speed of the unmanned aerial vehicle according to a third distance of the unmanned aerial vehicle in the unmanned aerial vehicle cluster;
and determining the control speed of the unmanned aerial vehicle according to the first speed, the second speed and the third speed of the unmanned aerial vehicle.
5. The method of claim 4, wherein the control speed of the UAV is calculated by using the following formula:
Figure FDA0003260110730000021
Figure FDA0003260110730000022
wherein,
Figure FDA0003260110730000023
representing the theoretical speed of the ith drone,
Figure FDA0003260110730000024
indicating the control speed, v, of the ith unmanned plane at the current momentlimitRepresenting the speed cut-off value of the drone,
Figure FDA0003260110730000025
representing a first speed, v, of the ith droneliRepresenting a second speed of the ith drone,
Figure FDA0003260110730000026
is the third speed of the ith drone.
6. The method of claim 5, wherein the first speed of the UAV is calculated by using the following formula:
Figure FDA0003260110730000027
Figure FDA0003260110730000028
wherein,
Figure FDA0003260110730000029
representing a first speed, r, of the ith drone0 repDenotes a first distance threshold, riIndicating the current position of the ith drone, rjIndicates the current position of the jth drone, rijRepresenting a first distance, r, of the ith drone from the jth droneij＝|ri-rj|，CrepIs a first gain factor to be used for the first,
Figure FDA00032601107300000210
indicating that the ith drone is subject to a first repelling velocity created by the jth drone.
7. The method of claim 5, wherein the second speed of the UAV is calculated by the following formula:
Figure FDA00032601107300000211
Figure FDA00032601107300000212
Figure FDA00032601107300000213
wherein v isliIndicating a second speed, r, of the ith droneileaderRepresenting a second distance, r, of the ith drone from the virtual leaderileader＝|rleader-ri|，riRepresents the ithCurrent position of unmanned aerial vehicle, rleaderRepresenting the current position of the virtual leader, afollow，pfollowA second gain coefficient respectively representing the maximum acceleration and braking curve of the unmanned aerial vehicle in the unmanned aerial vehicle cluster when the unmanned aerial vehicle approaches the virtual leader, CfollowA velocity component adjustment coefficient, v, representing a trend of drones in said drone swarm towards a virtual leaderfRepresenting an initial velocity at which drones in the drone swarm track a virtual leader, D (r, a, p) being a velocity decay function.
8. The method of claim 5, wherein the third speed of the UAV is calculated by using the following formula:
Figure FDA0003260110730000031
Figure FDA0003260110730000032
Figure FDA0003260110730000033
wherein,
Figure FDA0003260110730000034
third speed, r, for the ith dronesIs a point which is positioned on the boundary of the field and is closest to the unmanned aerial vehicle, and is used as the position of the virtual agent, risIs the shortest distance between the ith unmanned aerial vehicle and the field boundary, ris＝|ri-rs|；rwallIs a safe distance between the unmanned aerial vehicle and the field boundary, vsAs a virtual velocity vector of a virtual agent, virtual velocity vsIs perpendicular to the field boundary where the virtual agent is located and points to the field viVelocity vector, v, for the ith droneisMagnitude is the norm, v, of the vector difference between the velocity vector of the ith drone and the virtual velocity vector of the virtual agentis＝|vi-vs|；CshillTo be an adjustable factor, ashill、pshillIs an adjustable parameter.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for target search control of a cluster of drones according to any of the claims 1 to 8.
10. An unmanned aerial vehicle cluster's target search control system, its characterized in that includes:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method of target search control for a cluster of drones as claimed in any one of claims 1 to 8.
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