CN108983818B - Formation transformation method of UAV based on virtual structure - Google Patents
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- G05D1/10—Simultaneous control of position or course in three dimensions
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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- G05D1/60—Intended control result
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- G05D1/60—Intended control result
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Abstract
The invention discloses an unmanned aerial vehicle formation transformation method based on a virtual structure, which is applied to the field of unmanned aerial vehicle formation and control and aims at solving the problem that each unmanned aerial vehicle follows a virtual mass point in the existing virtual structure method, and flexible formation transformation cannot be realized due to the limited virtual structure; according to the invention, the formation of the unmanned aerial vehicle based on the virtual structure is established, then the flight state of the whole formation is controlled by controlling the flight state of the virtual structure, and the unmanned aerial vehicle moves around the virtual particle to which the unmanned aerial vehicle belongs, so that the flexible transformation of the formation of the unmanned aerial vehicle based on the virtual structure is realized.
Description
Technical Field
The invention belongs to the field of unmanned aerial vehicle formation and control, and particularly relates to a formation and formation transformation control technology considering large-scale small unmanned aerial vehicles.
Background
Unmanned aerial vehicles have originated in the military field, and through decades of development, have entered the rapid development phase at present, and the kind is more and more, and the application field is constantly expanded, and the task type is more and more extensive. In the aspect of military affairs, the micro unmanned aerial vehicle can perform reconnaissance and monitoring under the complex terrain condition of field operation, and can also be used for reconnaissance of the internal condition of a building under a special environment, monitoring, hostage rescuing, terrorist action and the like. In the civil field, the system is mainly used for monitoring and surveying disasters such as flood, forest fire, earthquake and the like, civil aviation shooting, entertainment shooting and the like.
With the acceleration of the informatization and intellectualization degree of the modern society and the instantaneous change of the environment in which the unmanned aerial vehicle is applied, a single unmanned aerial vehicle cannot complete a specific task often, or the unmanned aerial vehicle capable of well completing the task is expensive often. In order to make up the defects of a single unmanned aerial vehicle, the unmanned aerial vehicle cluster with large scale, low cost and multiple functions is provided to replace the single unmanned aerial vehicle, and the cooperative combat of the unmanned aerial vehicle cluster is realized through technologies such as air networking, autonomous control, crowd intelligent decision and the like. The formation control of the unmanned aerial vehicles means that when a plurality of unmanned aerial vehicles, even thousands of unmanned aerial vehicles, move jointly, fixed or variable geometric shapes are kept among all bodies, and meanwhile, the task constraints of obstacle avoidance and internal collision avoidance are completed. When the unmanned aerial vehicles execute tasks together in a formation mode, mutual influence exists among the unmanned aerial vehicles, and therefore difficult problems of information communication, exchange, calculation and the like among the unmanned aerial vehicles need to be solved, and generation, maintenance and transformation of formation in the task execution process of the unmanned aerial vehicles are guaranteed. The current method for controlling the formation mainly comprises the following steps: a navigator-follower approach, a behavior-based approach, a virtual structure approach, an artificial potential field function-based approach, and a consistency algorithm-based approach. Each method has respective advantages and disadvantages, for example, the behavior-based method has clear formation feedback, the unmanned aerial vehicle reacts according to the position information of other unmanned aerial vehicles, and the system can realize distributed control, so that the real-time performance and the parallelism of the system are improved. The disadvantage is that the group behavior is not well defined and it is very difficult to mathematically analyze it. The virtual structure method has the advantages that the motion of the whole intelligent agent group can be controlled only by defining the motion behaviors of the rigid bodies, and the method can also carry out formation feedback. However, the disadvantage is that the application range is largely limited by the formation formed by the virtual structure method, i.e. flexible formation transformation cannot be realized. The navigator-follower method has the defect that once the navigator fails, the whole formation is greatly fluctuated and even fails.
Disclosure of Invention
In order to solve the technical problem, the invention provides an unmanned aerial vehicle formation transformation method based on a virtual structure, and flexible transformation of unmanned aerial vehicle formations is realized.
The technical scheme adopted by the invention is as follows: an unmanned aerial vehicle formation transformation method based on a virtual structure comprises the following steps:
s1, establishing an unmanned aerial vehicle formation based on a virtual structure;
s2, based on the unmanned aerial vehicle formation established in the step S1, each unmanned aerial vehicle adopts an automatic following mode to change the formation according to the formation change instruction sent by the ground control base station;
and S3, based on the unmanned aerial vehicle formation established in the step S1, according to the formation reorganization instruction sent by the ground control base station, each unmanned aerial vehicle adopts a forced following mode to reorganize the formation.
Further, step S1 includes the following substeps:
s11, generating a Voronoi diagram with virtual particles as generating elements by adopting a Delaunay triangulation algorithm; each generator corresponds to a polygonal Voronoi area; the distance from a point in each polygonal Voronoi area to a generator in the polygonal Voronoi area is less than the distance from other generators; the distances from points on the common edge of the adjacent polygon Voronoi areas to the generating elements in the two adjacent polygon Voronoi areas are equal;
s12, after receiving the takeoff instruction, the unmanned aerial vehicle adopts a forced following mode, and when following the designated virtual particles and reaching the Voronoi area of the polygon to which the designated virtual particles belong, the unmanned aerial vehicle is switched to an automatic following mode;
and S13, establishing a force balance model of the unmanned aerial vehicle according to the repulsive force of the unmanned aerial vehicle from the adjacent unmanned aerial vehicle and the attractive force of the unmanned aerial vehicle from the virtual mass point.
Further, the unmanned aerial vehicle force balance model expression is as follows:
wherein, ViFor a set of unmanned aerial vehicles within communication range of unmanned aerial vehicle i, Fr,ijRepulsion of adjacent drone j, F, for drone i receivesa,iFor unmanned aerial vehicle i to receive the attraction of the virtual mass point, FiFor the force of the unmanned plane, when FiAnd when the value is 0, the unmanned aerial vehicle is in a force balance state.
Furthermore, a virtual structure of the unmanned aerial vehicle formation is formed by a series of inertia coordinates in the earth inertia coordinate system, and the virtual structure comprises a plurality of virtual particles, wherein each virtual particle is expressed as a binary group < p, v >, p is a position vector of the virtual particle in the earth coordinate system, and v is a motion speed of the virtual particle.
Further, step S2 specifically includes the following steps:
s21, the ground control base station translates the sent queue form conversion command into a queue form conversion control command expressed by the virtual particle coordinate parameter; sending a formation change control instruction to the unmanned aerial vehicle cluster through a remote communication channel;
and S22, each unmanned aerial vehicle adopts an automatic following mode based on the principle of proximity to follow the virtual particle with the nearest distance to fly, and establishes a force balance model with the adjacent unmanned aerial vehicle and the nearest virtual particle to reach a force balance state.
Further, step S3 specifically includes the following steps:
s31, the ground control base station sends a formation recombination instruction to the unmanned aerial vehicle cluster through a remote communication channel;
s32, the unmanned aerial vehicle establishes a force balance model between the unmanned aerial vehicle and the adjacent unmanned aerial vehicle as well as the virtual particle, a forced following mode is adopted to fly along with the designated virtual particle, and when the unmanned aerial vehicle reaches the designated virtual particle area, the mode is switched to an automatic following mode.
Further, the formation reorganization control instruction format is as follows: each virtual particle is followed by the number of that virtual particle and the drone number that the virtual particle controls.
The invention has the beneficial effects that: according to the invention, the formation of the unmanned aerial vehicle based on the virtual structure is established, then the flight state of the whole formation is controlled by controlling the flight state of the virtual structure, the unmanned aerial vehicle moves around the virtual particle to which the unmanned aerial vehicle belongs, and the flexible transformation of the formation of the unmanned aerial vehicle based on the virtual structure is realized; compared with the existing virtual structure method in which each unmanned aerial vehicle follows one virtual particle, the method of the invention does not need to control a large number of virtual particles, thereby not only ensuring good formation control effect, but also having small communication traffic and low control difficulty.
Drawings
FIG. 1 is a flow chart of a protocol of the present invention;
fig. 2 is a control state transition diagram of the drone;
FIG. 3 is a Voronoi diagram with a set of virtual prime points as generator;
FIG. 4 is a schematic diagram of a takeoff-following process established by the UAV;
fig. 5 is a schematic diagram of unmanned aerial vehicle formation establishment based on a virtual structure;
fig. 6 is a schematic diagram of unmanned aerial vehicle formation transformation based on a virtual structure;
fig. 7 is a schematic diagram of unmanned aerial vehicle formation merging based on a virtual structure.
Detailed Description
In order to facilitate the understanding of the technical contents of the present invention by those skilled in the art, the present invention will be further explained with reference to the accompanying drawings.
Aiming at the defects of the existing formation control technology, the invention provides an unmanned aerial vehicle formation transformation method based on a virtual structure, and the flow chart of the scheme of the invention is shown in figure 1 and is realized by the following three steps:
s1, establishing an unmanned aerial vehicle formation based on a virtual structure;
s11: establishing a virtual structure of the unmanned aerial vehicle formation, and generating a Voronoi diagram with a virtual prime point set as a generating element
A virtual structure of unmanned aerial vehicle formation is formed by a series of inertia coordinates in a geodetic inertia coordinate system, wherein each virtual mass point is represented as a binary group < p, v >, a vector p is a position vector of the virtual mass point in the geodetic inertia coordinate system, and a vector v is a motion speed of the virtual mass point. Thus, a plurality of virtual particles form a virtual structure of the formation, and the state of the virtual particles is the expected state of the actual unmanned aerial vehicle formation.
Where the geodetic coordinate system is a coordinate system that is stationary with respect to the earth's surface, the WGS-84 coordinate system or other equivalent coordinate system may be employed. In the WGS-84 coordinate system, each coordinate is represented by longitude, latitude, and altitude.
In the invention, a Delaunay triangulation algorithm is adopted to generate a Voronoi diagram which takes virtual particles as generating elements, as shown in FIG. 3; for the sake of simplicity, only a two-dimensional schematic is shown here. In the figure, black dots are virtual dots, the virtual dots form a virtual structure of a formation of the unmanned aerial vehicle, each polygon is a Voronoi region with the corresponding virtual dot as a generator, and the characteristics are as follows: each polygon Voronoi area is internally provided with a generator; the distance from the point in each polygonal Voronoi area to the generator is shorter than the distance from the point to other generators; points on a common edge of adjacent polygon Voronoi regions are equidistant from the generators in the adjacent two polygon Voronoi regions.
S12: establishing a takeoff process for an unmanned aerial vehicle
The Voronoi diagram generated in step S11 divides the entire sky into regions, each region having a virtual dot numbered i (i e [1, N ]). And sending the number of the virtual particle to be followed to each unmanned aerial vehicle through the control center. Unmanned aerial vehicle and adjacent unmanned aerial vehicle continuously keep repulsion to avoid colliding with each other. The takeoff direction of the unmanned aerial vehicle is determined through the virtual particle coordinates, and after the unmanned aerial vehicle enters the region of the virtual particle, a force balance model is established with the virtual particle and the adjacent unmanned aerial vehicle. The specific method comprises the following steps:
in FIG. 4, the small triangles represent virtual particles. Let the coordinate P1 of the virtual particle at the takeoff time of the unmanned aerial vehicle be < P1V >, where the position vector is p1＝[x1,y1,z1]，v＝[v1,v2,v3]. After time t, the virtual particle arrives at position P2 < P2V >, i.e. p2＝[v1t,v2t,v3t]. At this time, it is desirable that the unmanned aerial vehicle also reaches the position near P2, the magnitude of the flight speed of the unmanned aerial vehicle is u, and the flight direction of the unmanned aerial vehicle is obtained by the following formula (1).
p1+v·t＝u·t (1)
S13: establishing a force balance model of an unmanned aerial vehicle
Equation (2) represents the interaction force (repulsion) between drone i and adjacent drone j, where xijRepresenting the distance between drone i and adjacent drone j,
is a unit vector, representing the slave drone iTo the unit vector of the unmanned plane j, alpha is a repulsion coefficient, alpha is more than or equal to 1, FRIs a preset fixed repulsive force. Repulsion between the unmanned aerial vehicles has guaranteed to be in safe distance between the unmanned aerial vehicle, avoids bumping.
In addition to forces from neighboring drones, the drones are also attracted by forces from the virtual particles, so that the drones can form a formation along with the virtual particles. Equation (3) the interaction (attraction) between drone i and its belonging virtual particle, where xiRepresenting the distance between drone i and the virtual particle,
a unit vector indicates a unit vector pointing from drone i to the virtual particle. Beta is an attraction coefficient, beta is more than or equal to 0, FAIs a preset fixed attractive force.
Equation (4) represents the stress condition of UAV i, when FiA force equilibrium state is reached at 0, where ViFor a set of unmanned aerial vehicles within communication range of unmanned aerial vehicle i, Fr,ijRepulsion of adjacent drone j, F, for drone i receivesa,iAnd the unmanned plane i is attracted by the virtual particle. When the drones of the whole cluster reach a force balance state, the whole drone formation also reaches a balance state, and a drone formation as shown in fig. 5 is established, wherein the small triangles represent virtual particles.
S2, based on the unmanned aerial vehicle formation established in the step S1, each unmanned aerial vehicle adopts an automatic following mode to change the formation according to a formation control instruction sent by the ground control base station;
s21: ground control base station sends formation change instruction to unmanned aerial vehicle cluster
The ground control base station translates control instructions of the formation, such as (cusp shape, straight line shape, circular shape, triangular shape, herringbone shape and the like) into the formation represented by the virtual particle coordinate parameters, and sends a formation transformation instruction to the unmanned aerial vehicle cluster through a remote communication channel.
S22: unmanned aerial vehicle adopts automatic following mode to establish formation based on principle of being nearby
After the formation of the drone at step S1, the drone assumes the automatic following mode. After the unmanned aerial vehicle receives the formation transformation instruction and the formation represented by the virtual particle coordinate parameters, the unmanned aerial vehicle adopts the principle of close following to follow the nearest virtual particle to fly, a force balance model between each unmanned aerial vehicle and the adjacent unmanned aerial vehicle and between the unmanned aerial vehicle and the nearest virtual particle, namely a formula (4), gradually reaches a force balance state to form the unmanned aerial vehicle formation as shown in fig. 6, and controls the flying state of the whole unmanned aerial vehicle formation by controlling the speed and the motion state of the virtual particle.
And S3, based on the unmanned aerial vehicle formation established in the step S1, according to the formation reorganization instruction sent by the ground control base station, each unmanned aerial vehicle adopts a forced following mode to reorganize the formation.
S31: ground control base station sends new virtual structure information to unmanned aerial vehicle cluster
And the ground control base station translates the formation recombination instruction into a formation represented by the virtual particle coordinate parameters, and sends the formation recombination instruction to the unmanned aerial vehicle cluster through a remote communication channel. The control information format is: each virtual particle is followed by the number of that virtual particle and the drone number that the virtual particle controls. And switching the unmanned aerial vehicle mode into a forced following mode to execute the recombination instruction.
S32: the unmanned aerial vehicles adopt a forced following mode to establish formation according to the virtual structure in the step S31
After the unmanned aerial vehicle receives the control information, the virtual particles followed by the unmanned aerial vehicle are found through searching and matching. And then, establishing a force balance model, namely the state represented by the formula (4), with the adjacent unmanned aerial vehicles and the virtual particles, flying along with the virtual particles, and switching to an automatic following mode after the unmanned aerial vehicles arrive at a specified virtual particle area, so that the splitting or merging operation of the unmanned aerial vehicle formation is realized. Fig. 7 shows that before reassembly, the drone formation is controlled by multiple virtual particles, and after consolidation, there is only one virtual particle.
In summary, the control state of the drone switches between the free following mode and the forced following mode, as shown in fig. 2. The method specifically comprises the following steps: the unmanned aerial vehicle takes off and establishes an unmanned aerial vehicle formation as a forced following mode, and the unmanned aerial vehicle is automatically converted into a free following mode after the formation is established. Later, the unmanned aerial vehicle formation flies in the air, only has formation transform and formation reorganization two kinds of condition, and the formation transform adopts the free following mode, and the formation reorganization then adopts the compulsory following mode, avoids unmanned aerial vehicle to bump at formation reorganization in-process. After the unmanned aerial vehicle cluster finishes formation flight or mission, the unmanned aerial vehicle cluster adopts a forced following mode to land.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
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| US11274936B2 (en) * | 2019-11-14 | 2022-03-15 | Nissan North America, Inc. | Safety-assured remote driving for autonomous vehicles |
| CN113110593B (en) * | 2021-05-06 | 2022-08-09 | 西北工业大学 | Flight formation cooperative self-adaptive control method based on virtual structure and estimation information transmission |
| CN118113065B (en) * | 2024-01-19 | 2025-11-11 | 成都飞机工业（集团）有限责任公司 | Unmanned aerial vehicle formation control method |
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