CN115657726B - Control switching method of multiple unmanned aerial vehicles - Google Patents

Abstract

The invention relates to an artificial intelligence technology, and discloses a control switching method of a multi-unmanned aerial vehicle, which comprises the following steps: acquiring position information, motion information and authority information of an unmanned aerial vehicle group, determining piloting unmanned aerial vehicles of the unmanned aerial vehicle group, and establishing an initial motion model of the unmanned aerial vehicle group; acquiring communication information of the unmanned aerial vehicle group, and constructing a topology communication network of the unmanned aerial vehicle group; searching a preset area to be monitored, and when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object, planning a path by using a target pilot according to the target detection object to obtain a pilot path; and (3) reorganizing and forming the unmanned aerial vehicle group according to the pilot route, updating the initial motion model according to the reorganization and forming result to obtain a standard motion model, and controlling the unmanned aerial vehicle group to operate according to the standard motion model. The invention can improve the efficiency of executing tasks by multiple unmanned aerial vehicles.

Description

Control switching method of multiple unmanned aerial vehicles

Technical Field

The invention relates to the technical field of artificial intelligence, in particular to a control switching method of a multi-unmanned aerial vehicle.

Background

With the increasing maturity of unmanned aerial vehicle technology, more and more fields begin to utilize unmanned aerial vehicle to carry out production operation, for example use unmanned aerial vehicle to carry out production activities such as military reconnaissance, electric power inspection, cargo transportation and logistics distribution, and in order to realize complicated operation, often need to be by the unmanned aerial vehicle crowd of a plurality of unmanned aerial vehicles to carry out resultant force cooperation, but unmanned aerial vehicle crowd when carrying out the task, need switch the control mode of unmanned aerial vehicle crowd in real time to satisfy the work demand of different task stages.

The existing multi-unmanned aerial vehicle control switching technology is mainly control switching among multiple base stations, for example, in the process that an unmanned aerial vehicle group flies to a second area from a first area to execute tasks, control authority of the unmanned aerial vehicle group needs to be handed over from a ground base station in the first area to a ground base station in the second area, in practical application, the control switching among the multiple base stations is more influenced by the coverage effect of the ground base station, communication delay between the unmanned aerial vehicle group and the ground base station is higher, and efficiency of the multi-unmanned aerial vehicle in executing tasks is possibly lower.

Disclosure of Invention

The invention provides a control switching method of multiple unmanned aerial vehicles, and mainly aims to solve the problem that efficiency is low when the multiple unmanned aerial vehicles execute tasks.

In order to achieve the above object, the present invention provides a control switching method for multiple unmanned aerial vehicles, including:

acquiring position information, motion information and authority information of an unmanned aerial vehicle group, determining piloting unmanned aerial vehicles of the unmanned aerial vehicle group according to the authority information, and establishing an initial motion model of the unmanned aerial vehicle group by utilizing the position information and the motion information;

Acquiring communication information of the unmanned aerial vehicle group, and constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model;

Performing area search on a preset area to be monitored by using the unmanned aerial vehicle group, and judging whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object;

When the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, the unmanned aerial vehicle is used as a target piloting machine, the control authority of the unmanned aerial vehicle group is switched to the target piloting machine, and the control authority of the target piloting machine is utilized to carry out path planning according to the target detection object so as to obtain a piloting path;

The topology communication network is utilized to reorganize and form the unmanned aerial vehicle group according to the pilot route, the initial motion model is updated according to the reorganization and formation result to obtain a standard motion model, and the target navigation machine is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the standard motion model;

when the unmanned aerial vehicle is the piloting unmanned aerial vehicle, the piloting unmanned aerial vehicle is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the initial motion model.

Optionally, the establishing an initial motion model of the unmanned aerial vehicle group by using the position information and the motion information includes:

Extracting the positioning coordinates, the course angle and the pitch angle of the unmanned aerial vehicle group from the position information;

extracting the flying speed, pitch angle speed, yaw angle speed and execution delay of the unmanned aerial vehicle group from the motion information;

Establishing an initial motion model using the positioning coordinates, the heading angle, the pitch angle, the flight speed, the yaw rate, the pitch angle rate, and the execution delay as follows:

Wherein ,[xⁱ-x₀ ⁱ,yⁱ-y₀ ⁱ,zⁱ-z₀ ⁱ,δ,γ,v,w,u]^T is a state vector of an ith unmanned aerial vehicle in the unmanned aerial vehicle group, i is the ith unmanned aerial vehicle in the unmanned aerial vehicle group, x ⁱ is a real-time transverse axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, x ₀ ⁱ is a transverse axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, y ⁱ is the real-time vertical axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, y ₀ ⁱ is the vertical axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, z ⁱ is the real-time vertical axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, z ₀ ⁱ is the vertical axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, delta is the course angle, gamma is the pitch angle, v is the flying speed, w is the yaw rate, u is the pitch rate, T is a transposed symbol, tau _v is the flying speed execution delay in the execution delays, r _v is a control command corresponding to the flying speed, τ _w is a yaw rate execution delay in the execution delays, r _w is a control command corresponding to the yaw rate, τ _u is a pitch rate execution delay in the execution delays, and r _u is the pitch angle speed corresponding to the flying speed.

Optionally, the constructing the topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model includes:

Selecting unmanned aerial vehicles in the unmanned aerial vehicle group as target unmanned aerial vehicles one by one, and extracting target positions of the target unmanned aerial vehicles from the initial motion model;

Determining the communication unmanned aerial vehicle of the target unmanned aerial vehicle according to the communication information, and extracting the communication delay between the target unmanned aerial vehicle and the communication unmanned aerial vehicle from the communication information;

And taking the target position as a graph node, connecting the graph node corresponding to the target unmanned aerial vehicle with the graph node corresponding to the communication unmanned aerial vehicle to obtain a node edge, and taking the communication delay as an edge weight corresponding to the node edge to obtain the topology communication network.

Optionally, the performing area search on the preset area to be monitored by using the unmanned aerial vehicle group includes:

selecting one unmanned aerial vehicle in the unmanned aerial vehicle group as a target unmanned aerial vehicle, and extracting a three-dimensional position coordinate of the target unmanned aerial vehicle from the initial motion model as a target position coordinate;

calculating the monitoring width and the monitoring length of the target unmanned aerial vehicle according to the target position coordinates, and calculating the investigation width of the unmanned aerial vehicle group according to the monitoring widths and the monitoring lengths corresponding to all the target unmanned aerial vehicles;

And planning a monitoring path of the region to be monitored according to the detection width to obtain a monitoring path, and searching the region to be detected according to the monitoring path.

Optionally, the calculating the monitoring width and the monitoring length of the target unmanned aerial vehicle according to the target position coordinates includes:

extracting the longitudinal axis coordinate of the target unmanned aerial vehicle from the target position coordinate;

acquiring monitor information of the target unmanned aerial vehicle, and extracting a longitudinal monitoring angle and a transverse detecting angle from the monitor information;

Calculating the monitoring width and the monitoring length according to the longitudinal axis coordinate, the longitudinal monitoring angle and the transverse detection angle by using the following monitoring width algorithm:

Wherein, R ₁ refers to the monitoring width, R ₂ refers to the monitoring length, ceiling is an upward rounding symbol, θ is the longitudinal monitoring angle, α refers to the roll angle of the target unmanned aerial vehicle, β refers to the transverse detection angle, and d refers to the longitudinal axis coordinate of the target unmanned aerial vehicle.

Optionally, the performing path planning according to the target probe by using the control authority of the target navigator to obtain a piloting path includes:

acquiring three-dimensional point cloud information of the surrounding environment of the target probe according to the control authority of the target navigation machine, and the real-time horizontal axis coordinate, the real-time vertical axis coordinate and the real-time vertical axis coordinate of the target navigation machine;

Adding coordinate information of the target probe into the three-dimensional point cloud information to obtain primary point cloud information, and adding coordinate information of the target navigation machine into the primary point cloud information to obtain secondary point cloud information;

obtaining obstacle information in the surrounding environment of the target probe by using a monitor of the target navigation machine, and updating the secondary point cloud information according to the obstacle information to obtain standard point cloud information;

And planning a path according to the standard point cloud information by using a preset optimal path algorithm to obtain the pilot path.

Optionally, the reorganizing and forming the unmanned aerial vehicle group according to the pilot path by using the topology communication network includes:

Generating a communication topology matrix of the target navigation machine according to the topology communication network;

performing topology sequencing on the unmanned aerial vehicle group according to the communication topology matrix, and taking the topology sequence number after the topology sequencing as a reorganization number of the unmanned aerial vehicle group;

and carrying out serial formation on the unmanned aerial vehicle group on the pilot route according to the recombination number to complete the recombination formation.

In order to solve the above problems, the present invention further provides a control switching device of a multi-unmanned aerial vehicle, the device comprising:

The motion model module is used for acquiring the position information, the motion information and the authority information of the unmanned aerial vehicle group, determining the piloting unmanned aerial vehicle of the unmanned aerial vehicle group according to the authority information, and establishing an initial motion model of the unmanned aerial vehicle group by utilizing the position information and the motion information;

The communication network module is used for acquiring communication information of the unmanned aerial vehicle group and constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by utilizing a preset topology communication model;

The control switching module is used for searching a preset area to be monitored by utilizing the unmanned aerial vehicle group, and judging whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle or not when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object; when the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, the unmanned aerial vehicle is used as a target piloting machine, the control authority of the unmanned aerial vehicle group is switched to the target piloting machine, and the control authority of the target piloting machine is utilized to carry out path planning according to the target detection object so as to obtain a piloting path;

The detection operation module is used for reorganizing and forming the unmanned aerial vehicle group according to the pilot route by utilizing the topology communication network, updating the initial motion model according to the reorganization and forming result to obtain a standard motion model, and controlling the unmanned aerial vehicle group to operate the target detection object by utilizing the target navigation machine according to the standard motion model;

And the default operation module is used for controlling the unmanned aerial vehicle group to operate the target detection object by utilizing the piloting unmanned aerial vehicle according to the initial motion model when the unmanned aerial vehicle is the piloting unmanned aerial vehicle.

In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:

At least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of controlling switching of the drone described above.

In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having stored therein at least one computer program that is executed by a processor in an electronic device to implement the above-mentioned multi-unmanned aerial vehicle control switching method.

According to the embodiment of the invention, the initial motion model is built by utilizing the positioning coordinates, the course angle, the pitch angle, the flying speed, the yaw angle speed, the pitch angle speed and the execution delay, so that the motion relation of the unmanned aerial vehicle group can be accurately represented, the subsequent unmanned aerial vehicle searching and path planning are assisted, and the topology communication network of the unmanned aerial vehicle group is built by utilizing the preset topology communication model according to the communication information and the initial motion model, so that the communication state of each unmanned aerial vehicle in the unmanned aerial vehicle group can be expressed mathematically, and the subsequent control switching is facilitated; the method comprises the steps that a preset area to be monitored is searched by utilizing the unmanned aerial vehicle group, a monitoring total matrix of the unmanned aerial vehicle group can be accurately determined, a target searching path is planned according to the monitoring total matrix, the unmanned aerial vehicle searching efficiency is improved, a pilot path is obtained by utilizing the target unmanned aerial vehicle to carry out path planning according to target probes, the shortest moving path of the unmanned aerial vehicle group can be simulated, therefore, the unmanned aerial vehicle operation efficiency is improved, the unmanned aerial vehicle group is subjected to recombination formation according to the pilot path by utilizing the topology communication network, the initial motion model is updated according to the recombination formation result, a standard motion model is obtained, permission switching of the unmanned aerial vehicle group pilot aerial vehicle can be realized, the unmanned aerial vehicle closest to the target probes is used as a new pilot aerial vehicle, other unmanned aerial vehicles in the unmanned aerial vehicle group can be subjected to grouping according to the communication distance with the new pilot aerial vehicle, the unmanned aerial vehicle group movement safety is guaranteed, time consumption is reduced, and the target unmanned aerial vehicle searching efficiency is improved. Therefore, the control switching method, the device, the electronic equipment and the computer readable storage medium of the multi-unmanned aerial vehicle can solve the problem of low efficiency when the multi-unmanned aerial vehicle executes tasks.

Drawings

Fig. 1 is a schematic flow chart of a control switching method of a multi-unmanned aerial vehicle according to an embodiment of the invention;

FIG. 2 is a flow chart of performing region searching according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a path planning process according to an embodiment of the present invention;

Fig. 4 is a functional block diagram of a control switching device of a multi-unmanned aerial vehicle according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device for implementing the method for controlling and switching the multiple unmanned aerial vehicles according to an embodiment of the present invention.

The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

The embodiment of the application provides a control switching method of a multi-unmanned aerial vehicle. The execution main body of the control switching method of the multi-unmanned aerial vehicle comprises at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the control switching method of the multi-unmanned aerial vehicle may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

Referring to fig. 1, a flow chart of a control switching method of a multi-unmanned aerial vehicle according to an embodiment of the invention is shown. In this embodiment, the method for controlling and switching the multiple unmanned aerial vehicles includes:

S1, acquiring position information, motion information and authority information of an unmanned aerial vehicle group, determining a piloting unmanned aerial vehicle of the unmanned aerial vehicle group according to the authority information, and establishing an initial motion model of the unmanned aerial vehicle group by utilizing the position information and the motion information;

In the embodiment of the invention, the positioning components such as a GPS (global positioning system) positioner or a Beidou positioner can be utilized to acquire the position information of the unmanned aerial vehicle group, wherein the position information comprises longitude, latitude, horizontal height and the like of the unmanned aerial vehicle group.

In detail, the movement information of the unmanned aerial vehicle group including the flying speed, flying acceleration, deflection angle, and the like of the unmanned aerial vehicle group may be acquired using a sensor such as an acceleration sensor and a gyroscope.

Specifically, the permission information includes a pilot permission and a following permission, and only one unmanned aerial vehicle in the unmanned aerial vehicle group has the pilot permission, and the unmanned aerial vehicles are all following permission.

In detail, determining the piloting unmanned aerial vehicle of the unmanned aerial vehicle group according to the authority information refers to taking the unmanned aerial vehicle with piloting authority in the unmanned aerial vehicle group as the piloting unmanned aerial vehicle.

In the embodiment of the present invention, the establishing an initial motion model of the unmanned aerial vehicle group using the position information and the motion information includes:

Extracting the positioning coordinates, the course angle and the pitch angle of the unmanned aerial vehicle group from the position information;

extracting the flying speed, pitch angle speed, yaw angle speed and execution delay of the unmanned aerial vehicle group from the motion information;

Establishing an initial motion model using the positioning coordinates, the heading angle, the pitch angle, the flight speed, the yaw rate, the pitch angle rate, and the execution delay as follows:

Wherein ,[xⁱ-x₀ ⁱ,yⁱ-y₀ ⁱ,zⁱ-z₀ ⁱ,δ,γ,v,w,u]^T is a state vector of an ith unmanned aerial vehicle in the unmanned aerial vehicle group, i is the ith unmanned aerial vehicle in the unmanned aerial vehicle group, x ⁱ is a real-time transverse axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, x ₀ ⁱ is a transverse axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, y ⁱ is the real-time vertical axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, y ₀ ⁱ is the vertical axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, z ⁱ is the real-time vertical axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, z ₀ ⁱ is the vertical axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, delta is the course angle, gamma is the pitch angle, v is the flying speed, w is the yaw rate, u is the pitch rate, T is a transposed symbol, tau _v is the flying speed execution delay in the execution delays, r _v is a control command corresponding to the flying speed, τ _w is a yaw rate execution delay in the execution delays, r _w is a control command corresponding to the yaw rate, τ _u is a pitch rate execution delay in the execution delays, and r _u is the pitch angle speed corresponding to the flying speed.

In detail, the heading angle refers to an angle between a longitudinal axis of an aircraft and a space aircraft and a north pole of the earth.

Specifically, the pitch angle refers to an included angle between an x-axis of the machine body coordinate system and a horizontal plane, when the x-axis of the machine body coordinate system is above an inertial coordinate system XOY plane, the pitch angle is positive, and otherwise, the pitch angle is negative.

In the embodiment of the invention, the initial motion model is established by utilizing the positioning coordinates, the course angle, the pitch angle, the flying speed, the yaw angle speed, the pitch angle speed and the execution delay, so that the motion relationship of the unmanned aerial vehicle group can be accurately represented, and the subsequent unmanned aerial vehicle searching and path planning are assisted.

S2, acquiring communication information of the unmanned aerial vehicle group, and constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model;

In the embodiment of the invention, the communication information refers to a communication structure among unmanned aerial vehicles, and comprises the serial numbers, communication delays, relative structures of the unmanned aerial vehicles in the unmanned aerial vehicles, and the like.

In the embodiment of the present invention, the constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model includes:

Selecting unmanned aerial vehicles in the unmanned aerial vehicle group as target unmanned aerial vehicles one by one, and extracting target positions of the target unmanned aerial vehicles from the initial motion model;

Determining the communication unmanned aerial vehicle of the target unmanned aerial vehicle according to the communication information, and extracting the communication delay between the target unmanned aerial vehicle and the communication unmanned aerial vehicle from the communication information;

And taking the target position as a graph node, connecting the graph node corresponding to the target unmanned aerial vehicle with the graph node corresponding to the communication unmanned aerial vehicle to obtain a node edge, and taking the communication delay as an edge weight corresponding to the node edge to obtain the topology communication network.

In detail, the target position refers to a relative position of the target unmanned aerial vehicle in the unmanned aerial vehicle group.

Specifically, the communication unmanned aerial vehicle is an unmanned aerial vehicle that communicates with the target unmanned aerial vehicle, for example, the communication between the unmanned aerial vehicle A and the unmanned aerial vehicle B and the unmanned aerial vehicle C is performed, and then the unmanned aerial vehicle A is the unmanned aerial vehicle B and the unmanned aerial vehicle C.

In the embodiment of the invention, the communication state of each unmanned aerial vehicle in the unmanned aerial vehicle group can be expressed mathematically by constructing the topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by utilizing the preset topology communication model, thereby facilitating the subsequent control switching.

S3, carrying out area search on a preset area to be monitored by using the unmanned aerial vehicle group, and judging whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle or not when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object;

in the embodiment of the present invention, referring to fig. 2, the performing area search on a preset area to be monitored by using the unmanned aerial vehicle group includes:

s21, selecting one unmanned aerial vehicle in the unmanned aerial vehicle group as a target unmanned aerial vehicle, and extracting a three-dimensional position coordinate of the target unmanned aerial vehicle from the initial motion model as a target position coordinate;

S22, calculating the monitoring width and the monitoring length of the target unmanned aerial vehicle according to the target position coordinates, and calculating the investigation width of the unmanned aerial vehicle group according to the monitoring widths and the monitoring lengths corresponding to all the target unmanned aerial vehicles;

S23, planning a monitoring path of the area to be monitored according to the detection width, obtaining a monitoring path, and searching the area to be detected according to the monitoring path.

Specifically, the monitoring width refers to an actual width of the obtained monitoring area portion when the monitor of the target unmanned aerial vehicle monitors the ground.

In detail, the monitoring length refers to the actual length of the obtained monitoring area part when the monitor of the target unmanned aerial vehicle detects the ground.

In detail, the calculating the monitoring width and the monitoring length of the target unmanned aerial vehicle according to the target position coordinates includes:

extracting the longitudinal axis coordinate of the target unmanned aerial vehicle from the target position coordinate;

acquiring monitor information of the target unmanned aerial vehicle, and extracting a longitudinal monitoring angle and a transverse detecting angle from the monitor information;

Calculating the monitoring width and the monitoring length according to the longitudinal axis coordinate, the longitudinal monitoring angle and the transverse detection angle by using the following monitoring width algorithm:

Wherein, R ₁ refers to the monitoring width, R ₂ refers to the monitoring length, ceiling is an upward rounding symbol, θ is the longitudinal monitoring angle, α refers to the roll angle of the target unmanned aerial vehicle, β refers to the transverse detection angle, and d refers to the longitudinal axis coordinate of the target unmanned aerial vehicle.

According to the embodiment of the invention, the monitoring width of the target unmanned aerial vehicle is calculated according to the longitudinal axis coordinate, the longitudinal monitoring angle and the transverse detection angle by using the monitoring width algorithm, so that the monitoring width of the unmanned aerial vehicle can be determined by combining the real-time height and the roll angle of the target unmanned aerial vehicle, the irregular deformation of a monitoring area caused by the movement of the unmanned aerial vehicle is accurately represented, the planning of a subsequent monitoring path is facilitated, and the searching efficiency of the unmanned aerial vehicle area is improved.

In detail, the monitor may be a monitoring device such as a camera or a radar transmitter.

Specifically, the longitudinal monitoring angle refers to an included angle between an upper view and a lower view of the monitor.

In detail, the lateral detection angle refers to an included angle between left and right fields of view of the monitor.

In detail, the investigation width is a unit width when the unmanned aerial vehicle group performs the area search.

Specifically, the calculating the investigation width of the unmanned aerial vehicle group according to the monitoring width and the monitoring length includes:

Constructing a monitoring matrix by utilizing the monitoring width and the monitoring length, and constructing a monitoring total matrix of the unmanned aerial vehicle group according to the initial motion model and the monitoring matrix;

And extracting the total monitoring length and the total monitoring width from the total monitoring matrix, and selecting one with the largest numerical value from the total monitoring length and the total monitoring width as the investigation width.

In detail, the constructing the monitoring matrix using the monitoring width and the monitoring length means generating a matrix area having a width corresponding to the monitoring width and a length corresponding to the monitoring length, and using the matrix area as the monitoring matrix.

In detail, the monitoring path of the area to be monitored can be planned according to the detection width by using a scanning line detection mode, and a monitoring path is obtained.

Specifically, the performing area search on the area to be detected according to the monitoring path includes:

acquiring shot monitoring pictures of the unmanned aerial vehicle group under the monitoring path, and collecting all the monitoring pictures into a monitoring atlas;

Selecting monitoring pictures in the monitoring picture set one by one as target pictures, and extracting picture feature sets of the target pictures by using a preset target object identification model;

Selecting the picture features in the picture feature set one by one as target picture features, and calculating the similarity between the target picture features and the preset picture features of the target detection object by using the following target similarity algorithm:

Wherein D refers to the similarity, ρ is a preset similarity coefficient, arccos is an inverse cosine function, n is a total column number of feature vectors in the target image feature, the total column number of feature vectors in the target image feature is equal to the total column number of feature vectors in the image feature of the target probe, j refers to a j-th column in the feature vectors, C _j refers to a j-th column in the target image feature vectors, x is a vector point multiplication algorithm, and B _j refers to a j-th column of feature vectors in the image feature of the target probe;

And when the similarity is larger than a preset similarity threshold, determining that the region corresponding to the target picture feature contains the target detection object.

In detail, the object recognition model may be YoLo network or an Anchor Based network trained using an atlas containing the object probes.

In detail, by calculating the similarity between the target picture feature and the preset picture feature of the target probe by using the target similarity algorithm, each feature vector of the target picture can be subjected to hierarchical comparison, so that accuracy of similarity calculation is improved.

In the embodiment of the invention, the monitoring total matrix of the unmanned aerial vehicle group can be accurately determined by utilizing the unmanned aerial vehicle group to perform area search on the preset area to be monitored, and the searching path of the target is planned according to the monitoring total matrix, so that the searching efficiency of the unmanned aerial vehicle is improved.

S4, when the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, taking the unmanned aerial vehicle as a target piloting machine, switching the control authority of the unmanned aerial vehicle group to the target piloting machine, and carrying out path planning according to the target detection object by utilizing the control authority of the target piloting machine to obtain a piloting path;

in the embodiment of the invention, the target navigation machine is an unmanned aerial vehicle for piloting an unmanned aerial vehicle group.

In detail, the switching the control authority of the unmanned aerial vehicle group to the target navigation machine means that the authority information of the unmanned aerial vehicle group is updated so that the control authority of the target navigation machine is changed to the navigation authority.

In detail, the pilot path is used for planning an effective path of the target pilot unmanned aerial vehicle to reach the target detection object.

In the embodiment of the present invention, the path planning is performed according to the target probe by using the control authority of the target navigation machine to obtain a navigation path, including:

acquiring three-dimensional point cloud information of the surrounding environment of the target probe according to the control authority of the target navigation machine, and the real-time horizontal axis coordinate, the real-time vertical axis coordinate and the real-time vertical axis coordinate of the target navigation machine;

Adding coordinate information of the target probe into the three-dimensional point cloud information to obtain primary point cloud information, and adding coordinate information of the target navigation machine into the primary point cloud information to obtain secondary point cloud information;

obtaining obstacle information in the surrounding environment of the target probe by using a monitor of the target navigation machine, and updating the secondary point cloud information according to the obstacle information to obtain standard point cloud information;

And planning a path according to the standard point cloud information by using a preset optimal path algorithm to obtain the pilot path.

Specifically, the method for acquiring the obstacle information in the surrounding environment of the target probe by using the monitor of the target navigation machine is consistent with the step of performing the area search on the area to be detected according to the monitoring path in the step S3, which is not described herein.

In detail, referring to fig. 3, the performing path planning according to the standard point cloud information by using a preset optimal path algorithm to obtain the pilot path includes:

S31, acquiring coordinate information of the target detection object and coordinate information of the target navigation machine from the standard point cloud information, taking the coordinate information of the target detection object as an end point coordinate, taking the coordinate information of the target navigation machine as a starting point coordinate, and adding the starting point coordinate into a preset first coordinate set;

S32, randomly generating effective node coordinates according to the starting point coordinates and the ending point coordinates, and adding all the effective node coordinates into a first coordinate set;

s33, selecting coordinates in the first coordinate set one by one as target coordinates, and judging whether an obstacle exists in a straight line path between the target coordinates and the terminal coordinates;

S34, when an obstacle exists in a linear path between the target coordinate and the end point coordinate, calculating an effective path distance of the target coordinate, calculating a linear end point distance of the target coordinate according to the end point coordinate, and adding the linear end point distance and the effective path distance to obtain a target path distance;

S35, judging whether the target path distance is smaller than a preset initial path distance;

S36, deleting the target coordinates from the first coordinate set when the target path distance is greater than or equal to the initial path distance, and returning to the step of selecting the coordinates in the first coordinate set one by one as target coordinates;

S37, when the target path distance is smaller than the initial path distance, taking the target path distance as the initial path distance, and moving the target coordinates from the first coordinate set to a preset second coordinate set;

s38, taking an obstacle closest to the target coordinate as the target obstacle, acquiring an effective node coordinate corresponding to the target obstacle, adding the effective node coordinate into the first coordinate set, and returning to the step of selecting the coordinates in the first coordinate set one by one as the target coordinates;

and S39, when no obstacle exists in the straight line path between the target coordinate and the end point coordinate, generating the pilot path according to the second coordinate set, the target coordinate and the end point coordinate.

In detail, an effective node coordinate may be randomly generated according to the starting point coordinate and the ending point coordinate by using a random forest algorithm or an ant colony algorithm, wherein the effective node coordinate refers to a node coordinate sequence starting from the starting point coordinate, and no obstacle exists between the nodes and a straight line connecting the nodes.

Specifically, the effective path distance calculated from the target coordinates refers to the distance of an effective path obtained by sequentially connecting the starting point coordinates to the effective nodes between the target coordinates.

In the embodiment of the invention, the target navigation machine is utilized to carry out path planning according to the target detection object to obtain the navigation path, so that the shortest moving path of the unmanned aerial vehicle group can be simulated, and the operation efficiency of the unmanned aerial vehicle is improved.

S5, reorganizing and forming the unmanned aerial vehicle group according to the pilot path by using the topology communication network, updating the initial motion model according to the reorganization and forming result to obtain a standard motion model, and controlling the unmanned aerial vehicle group to operate the target detection object by using the target navigation machine according to the standard motion model;

in the embodiment of the present invention, the reorganizing and forming the unmanned aerial vehicle group according to the pilot path by using the topology communication network includes:

Generating a communication topology matrix of the target navigation machine according to the topology communication network;

performing topology sequencing on the unmanned aerial vehicle group according to the communication topology matrix, and taking the topology sequence number after the topology sequencing as a reorganization number of the unmanned aerial vehicle group;

and carrying out serial formation on the unmanned aerial vehicle group on the pilot route according to the recombination number to complete the recombination formation.

In detail, a topology algorithm may be utilized to generate a communication topology matrix of the target navigation machine according to the topology communication network.

Specifically, the serial queuing of the unmanned aerial vehicle group on the pilot path according to the reorganization number refers to serial queuing with the target pilot as a head of a queue, wherein the queue is ordered according to the reorganization number and follows the pilot path.

Specifically, updating the initial motion model according to the result of the reorganization formation to obtain a standard motion model refers to adjusting the arrangement sequence of unmanned aerial vehicles in the unmanned aerial vehicle group in the initial motion model according to the result of the reorganization formation, and adjusting the flight speed execution delay, the yaw angular speed execution delay and the pitch angle speed execution delay according to the result of the reorganization formation, so as to obtain the standard motion model.

In detail, the controlling the unmanned aerial vehicle group to operate the target detection object according to the standard motion model by using the target navigation machine refers to moving along the pilot path according to the standard motion model, and operating the target detection object when the target detection object reaches the end point of the pilot path.

In the embodiment of the invention, the topology communication network is utilized to reorganize and form the unmanned aerial vehicle group according to the pilot route, the initial motion model is updated according to the reorganization and formation result to obtain the standard motion model, and the permission switching of unmanned aerial vehicle group pilot aircraft can be realized, so that unmanned aerial vehicles closest to the target detection object are used as new pilot aircraft, and other unmanned aerial vehicles in the unmanned aerial vehicle group can be formed according to the communication distance with the new pilot aircraft, thereby not only ensuring the safety of unmanned aerial vehicle group motion, but also reducing the time consumption of forming the group, and simultaneously improving the searching efficiency of unmanned aerial vehicle target objects.

And S6, when the unmanned aerial vehicle is the piloting unmanned aerial vehicle, controlling the unmanned aerial vehicle group to operate the target detection object by utilizing the piloting unmanned aerial vehicle according to the initial motion model.

In the embodiment of the present invention, the method for controlling the unmanned aerial vehicle group to operate the target probe by using the pilot unmanned aerial vehicle according to the initial motion model is consistent with the method for controlling the unmanned aerial vehicle group to operate the target probe by using the target navigation machine according to the standard motion model in the step S5, and will not be described herein.

According to the embodiment of the invention, the initial motion model is built by utilizing the positioning coordinates, the course angle, the pitch angle, the flying speed, the yaw angle speed, the pitch angle speed and the execution delay, so that the motion relation of the unmanned aerial vehicle group can be accurately represented, the subsequent unmanned aerial vehicle searching and path planning are assisted, and the topology communication network of the unmanned aerial vehicle group is built by utilizing the preset topology communication model according to the communication information and the initial motion model, so that the communication state of each unmanned aerial vehicle in the unmanned aerial vehicle group can be expressed mathematically, and the subsequent control switching is facilitated; the method comprises the steps that a preset area to be monitored is searched by utilizing the unmanned aerial vehicle group, a monitoring total matrix of the unmanned aerial vehicle group can be accurately determined, a target searching path is planned according to the monitoring total matrix, the unmanned aerial vehicle searching efficiency is improved, a pilot path is obtained by utilizing the target unmanned aerial vehicle to carry out path planning according to target probes, the shortest moving path of the unmanned aerial vehicle group can be simulated, therefore, the unmanned aerial vehicle operation efficiency is improved, the unmanned aerial vehicle group is subjected to recombination formation according to the pilot path by utilizing the topology communication network, the initial motion model is updated according to the recombination formation result, a standard motion model is obtained, permission switching of the unmanned aerial vehicle group pilot aerial vehicle can be realized, the unmanned aerial vehicle closest to the target probes is used as a new pilot aerial vehicle, other unmanned aerial vehicles in the unmanned aerial vehicle group can be subjected to grouping according to the communication distance with the new pilot aerial vehicle, the unmanned aerial vehicle group movement safety is guaranteed, time consumption is reduced, and the target unmanned aerial vehicle searching efficiency is improved. Therefore, the control switching method of the multiple unmanned aerial vehicles can solve the problem of lower efficiency when the multiple unmanned aerial vehicles execute tasks.

Fig. 4 is a functional block diagram of a control switching device of a multi-unmanned aerial vehicle according to an embodiment of the present invention.

The control switching device 100 of the multi-unmanned aerial vehicle can be installed in electronic equipment. According to the implemented functions, the control switching device 100 of the multi-unmanned aerial vehicle may include a motion model module 101, a communication network module 102, a control switching module 103, a detection operation module 104, and a default operation module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.

In the present embodiment, the functions concerning the respective modules/units are as follows:

The motion model module 101 is configured to obtain position information, motion information, and authority information of an unmanned aerial vehicle group, determine a piloting unmanned aerial vehicle of the unmanned aerial vehicle group according to the authority information, and establish an initial motion model of the unmanned aerial vehicle group by using the position information and the motion information;

The communication network module 102 is configured to obtain communication information of the unmanned aerial vehicle group, and construct a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model;

The control switching module 103 is configured to perform area search on a preset area to be monitored by using the unmanned aerial vehicle group, and determine whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object; when the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, the unmanned aerial vehicle is used as a target piloting machine, the control authority of the unmanned aerial vehicle group is switched to the target piloting machine, and the control authority of the target piloting machine is utilized to carry out path planning according to the target detection object so as to obtain a piloting path;

The detection operation module 104 is configured to reorganize and form the unmanned aerial vehicle group according to the pilot path by using the topology communication network, update the initial motion model according to a reorganization and formation result to obtain a standard motion model, and control the unmanned aerial vehicle group to operate the target detection object according to the standard motion model by using the target navigation machine;

The default operation module 105 is configured to control, when the unmanned aerial vehicle is the piloting unmanned aerial vehicle, the unmanned aerial vehicle to operate the target probe by using the piloting unmanned aerial vehicle according to the initial motion model.

In detail, each module in the multi-unmanned aerial vehicle control switching device 100 in the embodiment of the present invention adopts the same technical means as the multi-unmanned aerial vehicle control switching method described in fig. 1 to 3, and can produce the same technical effects, which are not described herein.

Fig. 5 is a schematic structural diagram of an electronic device for implementing a method for controlling and switching a multi-unmanned aerial vehicle according to an embodiment of the present invention.

The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a control switching program of a drone.

The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (for example, executes a Control switching program of a multi-unmanned aerial vehicle, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device and process data.

The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only for storing application software installed in an electronic device and various data, such as codes of a control switching program of a multi-unmanned aerial vehicle, but also for temporarily storing data that has been output or is to be output.

The communication bus 12 may be a peripheral component interconnect standard (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.

The communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.

Only an electronic device having components is shown, and it will be understood by those skilled in the art that the structures shown in the figures do not limit the electronic device, and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.

For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.

It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.

The control switching program of the multi-unmanned aerial vehicle stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, which when executed in the processor 10, can implement:

acquiring position information, motion information and authority information of an unmanned aerial vehicle group, determining piloting unmanned aerial vehicles of the unmanned aerial vehicle group according to the authority information, and establishing an initial motion model of the unmanned aerial vehicle group by utilizing the position information and the motion information;

Acquiring communication information of the unmanned aerial vehicle group, and constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model;

Performing area search on a preset area to be monitored by using the unmanned aerial vehicle group, and judging whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object;

When the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, the unmanned aerial vehicle is used as a target piloting machine, the control authority of the unmanned aerial vehicle group is switched to the target piloting machine, and the control authority of the target piloting machine is utilized to carry out path planning according to the target detection object so as to obtain a piloting path;

The topology communication network is utilized to reorganize and form the unmanned aerial vehicle group according to the pilot route, the initial motion model is updated according to the reorganization and formation result to obtain a standard motion model, and the target navigation machine is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the standard motion model;

when the unmanned aerial vehicle is the piloting unmanned aerial vehicle, the piloting unmanned aerial vehicle is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the initial motion model.

In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.

Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).

The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:

acquiring position information, motion information and authority information of an unmanned aerial vehicle group, determining piloting unmanned aerial vehicles of the unmanned aerial vehicle group according to the authority information, and establishing an initial motion model of the unmanned aerial vehicle group by utilizing the position information and the motion information;

Acquiring communication information of the unmanned aerial vehicle group, and constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model;

Performing area search on a preset area to be monitored by using the unmanned aerial vehicle group, and judging whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object;

When the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, the unmanned aerial vehicle is used as a target piloting machine, the control authority of the unmanned aerial vehicle group is switched to the target piloting machine, and the control authority of the target piloting machine is utilized to carry out path planning according to the target detection object so as to obtain a piloting path;

The topology communication network is utilized to reorganize and form the unmanned aerial vehicle group according to the pilot route, the initial motion model is updated according to the reorganization and formation result to obtain a standard motion model, and the target navigation machine is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the standard motion model;

when the unmanned aerial vehicle is the piloting unmanned aerial vehicle, the piloting unmanned aerial vehicle is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the initial motion model.

In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.

The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.

The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.

The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Wherein artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) is the theory, method, technique, and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend, and expand human intelligence, sense the environment, acquire knowledge, and use knowledge to obtain optimal results.

Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms first, second, etc. are used to denote a name, but not any particular order.

Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (7)

1. A method for controlling and switching a plurality of unmanned aerial vehicles, the method comprising:

acquiring position information, motion information and authority information of an unmanned aerial vehicle group, determining piloting unmanned aerial vehicles of the unmanned aerial vehicle group according to the authority information, and establishing an initial motion model of the unmanned aerial vehicle group by utilizing the position information and the motion information;

Acquiring communication information of the unmanned aerial vehicle group, and constructing a topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model;

Performing area search on a preset area to be monitored by using the unmanned aerial vehicle group, and judging whether the unmanned aerial vehicle is the piloting unmanned aerial vehicle when one unmanned aerial vehicle in the unmanned aerial vehicle group monitors a preset target detection object;

When the unmanned aerial vehicle is not the piloting unmanned aerial vehicle, the unmanned aerial vehicle is used as a target piloting machine, the control authority of the unmanned aerial vehicle group is switched to the target piloting machine, and the control authority of the target piloting machine is utilized to carry out path planning according to the target detection object so as to obtain a piloting path;

The topology communication network is utilized to reorganize and form the unmanned aerial vehicle group according to the pilot route, the initial motion model is updated according to the reorganization and formation result to obtain a standard motion model, and the target navigation machine is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the standard motion model;

when the unmanned aerial vehicle is the piloting unmanned aerial vehicle, the piloting unmanned aerial vehicle is utilized to control the unmanned aerial vehicle group to operate the target detection object according to the initial motion model.

2. The method for controlling and switching multiple unmanned aerial vehicles according to claim 1, wherein the establishing an initial motion model of the unmanned aerial vehicle group using the position information and the motion information comprises:

Extracting the positioning coordinates, the course angle and the pitch angle of the unmanned aerial vehicle group from the position information;

extracting the flying speed, pitch angle speed, yaw angle speed and execution delay of the unmanned aerial vehicle group from the motion information;

Establishing an initial motion model using the positioning coordinates, the heading angle, the pitch angle, the flight speed, the yaw rate, the pitch angle rate, and the execution delay as follows:

Wherein ,[xⁱ-x₀ ⁱ,yⁱ-y₀ ⁱ,zⁱ-z₀ ⁱ,δ,γ,v,w,u]^T is a state vector of an ith unmanned aerial vehicle in the unmanned aerial vehicle group, i is the ith unmanned aerial vehicle in the unmanned aerial vehicle group, x ⁱ is a real-time transverse axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, x ₀ ⁱ is a transverse axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, y ⁱ is the real-time vertical axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, y ₀ ⁱ is the vertical axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, z ⁱ is the real-time vertical axis coordinate of the ith unmanned aerial vehicle in the unmanned aerial vehicle group, z ₀ ⁱ is the vertical axis coordinate of the ith unmanned aerial vehicle in the positioning coordinates, delta is the course angle, gamma is the pitch angle, v is the flying speed, w is the yaw rate, u is the pitch rate, T is a transposed symbol, tau _v is the flying speed execution delay in the execution delays, r _v is a control command corresponding to the flying speed, τ _w is a yaw rate execution delay in the execution delays, r _w is a control command corresponding to the yaw rate, τ _u is a pitch rate execution delay in the execution delays, and r _u is the pitch angle speed corresponding to the flying speed.

3. The method for controlling and switching multiple unmanned aerial vehicles according to claim 1, wherein the constructing the topology communication network of the unmanned aerial vehicle group according to the communication information and the initial motion model by using a preset topology communication model comprises:

Selecting unmanned aerial vehicles in the unmanned aerial vehicle group as target unmanned aerial vehicles one by one, and extracting target positions of the target unmanned aerial vehicles from the initial motion model;

Determining the communication unmanned aerial vehicle of the target unmanned aerial vehicle according to the communication information, and extracting the communication delay between the target unmanned aerial vehicle and the communication unmanned aerial vehicle from the communication information;

And taking the target position as a graph node, connecting the graph node corresponding to the target unmanned aerial vehicle with the graph node corresponding to the communication unmanned aerial vehicle to obtain a node edge, and taking the communication delay as an edge weight corresponding to the node edge to obtain the topology communication network.

4. The method for controlling and switching multiple unmanned aerial vehicles according to claim 1, wherein the performing area search on the preset area to be monitored by using the unmanned aerial vehicle group comprises:

selecting one unmanned aerial vehicle in the unmanned aerial vehicle group as a target unmanned aerial vehicle, and extracting a three-dimensional position coordinate of the target unmanned aerial vehicle from the initial motion model as a target position coordinate;

calculating the monitoring width and the monitoring length of the target unmanned aerial vehicle according to the target position coordinates, and calculating the investigation width of the unmanned aerial vehicle group according to the monitoring widths and the monitoring lengths corresponding to all the target unmanned aerial vehicles;

and planning a monitoring path of the area to be monitored according to the detection width to obtain a monitoring path, and searching the area to be monitored according to the monitoring path.

5. The method for controlling and switching multiple unmanned aerial vehicles according to claim 4, wherein the calculating the monitoring width and the monitoring length of the target unmanned aerial vehicle according to the target position coordinates comprises:

extracting the longitudinal axis coordinate of the target unmanned aerial vehicle from the target position coordinate;

acquiring monitor information of the target unmanned aerial vehicle, and extracting a longitudinal monitoring angle and a transverse detecting angle from the monitor information;

Calculating the monitoring width and the monitoring length according to the longitudinal axis coordinate, the longitudinal monitoring angle and the transverse detection angle by using the following monitoring width algorithm:

Wherein, R ₁ refers to the monitoring width, R ₂ refers to the monitoring length, ceiling is an upward rounding symbol, θ is the longitudinal monitoring angle, α refers to the roll angle of the target unmanned aerial vehicle, β refers to the transverse detection angle, and d refers to the longitudinal axis coordinate of the target unmanned aerial vehicle.

6. The method for controlling and switching multiple unmanned aerial vehicles according to claim 2, wherein the performing path planning according to the target probe by using the control authority of the target navigator to obtain a pilot path comprises:

acquiring three-dimensional point cloud information of the surrounding environment of the target probe according to the control authority of the target navigation machine, and the real-time horizontal axis coordinate, the real-time vertical axis coordinate and the real-time vertical axis coordinate of the target navigation machine;

Adding coordinate information of the target probe into the three-dimensional point cloud information to obtain primary point cloud information, and adding coordinate information of the target navigation machine into the primary point cloud information to obtain secondary point cloud information;

obtaining obstacle information in the surrounding environment of the target probe by using a monitor of the target navigation machine, and updating the secondary point cloud information according to the obstacle information to obtain standard point cloud information;

And planning a path according to the standard point cloud information by using a preset optimal path algorithm to obtain the pilot path.

7. The method for controlling and switching multiple unmanned aerial vehicles according to claim 6, wherein the reorganizing and queuing the unmanned aerial vehicle group according to the pilot path by using the topology communication network comprises:

Generating a communication topology matrix of the target navigation machine according to the topology communication network;

performing topology sequencing on the unmanned aerial vehicle group according to the communication topology matrix, and taking the topology sequence number after the topology sequencing as a reorganization number of the unmanned aerial vehicle group;

and carrying out serial formation on the unmanned aerial vehicle group on the pilot route according to the recombination number to complete the recombination formation.