CN111949047B - Central unmanned aerial vehicle selection method for centralized task planning of unmanned aerial vehicle - Google Patents
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Abstract
The invention discloses a central unmanned aerial vehicle selection method for unmanned aerial vehicle centralized mission planning, and belongs to the technical field of unmanned aerial vehicles. The invention comprises the following steps: s1: inputting source data to each unmanned aerial vehicle through a data acquisition module of the unmanned aerial vehicle group; s2: each unmanned aerial vehicle in the unmanned aerial vehicle cluster generates a direct communication link; s3: determining a locally optimal winner and its indirect communication links; s4: a globally optimal winner is found using the indirect communication link. When single-point failure occurs, the method can rapidly select a new central unmanned aerial vehicle to continue to execute mission planning so as to avoid the unmanned aerial vehicle cluster from being paralyzed.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a central unmanned aerial vehicle selection method for centralized mission planning of an unmanned aerial vehicle.
Background
Unmanned aerial vehicles are increasingly being used in complex mission scenarios such as battlefield information collection and fighting, urban fire extinguishing, unmanned express delivery, power grid line patrol, plant protection and the like by virtue of the advantages of adaptability, flexible maneuverability, low cost and the like of 3D ("Dall", "Dirty", "Dangerous") environments. In the process of cooperatively executing the task, the multiple unmanned aerial vehicles or the unmanned aerial vehicle cluster are constrained by the task requirements, the flight environment, the unmanned aerial vehicles and the like, and therefore a complex task planning problem needs to be solved. The task planning problem is that given N distributable unmanned aerial vehicles and M tasks, the optimal matching between the unmanned aerial vehicles and the tasks is found, and the total income obtained by the unmanned aerial vehicles executing the tasks is maximized.
Depending on the architecture for performing mission planning, multi-drone mission planning is generally divided into distributed mission planning and centralized mission planning ("multi-drone autonomous cooperative control theory and method, shenghui et al, 2013, national defense industry press).
Centralized mission planning is performed by a central unit, such as a ground station, a central drone. The centralized task planning based on the central unmanned aerial vehicle has the advantages of simple algorithm, high dynamic response speed and the like. However, the mission planning has the fatal defect of single-point failure, namely, when the central unmanned aerial vehicle breaks down or is damaged, the whole unmanned aerial vehicle cluster falls into paralysis.
Disclosure of Invention
The invention provides a central unmanned aerial vehicle selection method for centralized mission planning of unmanned aerial vehicles aiming at the problem of single point failure of the centralized mission planning.
In order to achieve the purpose, the invention adopts the following technical scheme:
a central unmanned aerial vehicle selection method for unmanned aerial vehicle centralized mission planning comprises the following steps:
s1: inputting source data to each unmanned aerial vehicle through a data acquisition module of the unmanned aerial vehicle cluster;
s2: each unmanned aerial vehicle in the unmanned aerial vehicle cluster generates a direct communication link;
s3: determining a locally optimal winner and its indirect communication links;
s4: a globally optimal winner is found using the indirect communication link.
Further, the source data is input to each unmanned aerial vehicle through a data acquisition module of the unmanned aerial vehicle cluster, and the method includes: the source data at least comprises the serial number, the specified time limit and time synchronization signals of each unmanned aerial vehicle in the unmanned aerial vehicle cluster, and the time synchronization signals are used for synchronizing the clocks of all unmanned aerial vehicles in the unmanned aerial vehicle cluster.
Further, the source data is input to each unmanned aerial vehicle through a data acquisition module of the unmanned aerial vehicle cluster, and the method includes: each unmanned aerial vehicle in the unmanned aerial vehicle cluster is required to be provided with a bidirectional communication module, a broadcast communication module and a calculation module.
Further, each drone in the drone swarm generates a direct communication link, including: each unmanned aerial vehicle in the unmanned aerial vehicle cluster confirms a direct communication link through broadcasting state information; the direct communication link refers to a link through which two unmanned aerial vehicles can directly communicate in a broadcasting or bidirectional communication mode; the state information at least comprises information of whether the communication module and the calculation module are normal or not.
Further, the determining of the locally optimal winner and its indirect communication link includes: and finding out the unmanned aerial vehicle with the most direct communication link in all unmanned aerial vehicles on the direct communication link of any unmanned aerial vehicle in the unmanned aerial vehicle cluster through broadcasting, considering that the unmanned aerial vehicle with the most direct communication link is the winner of the unmanned aerial vehicle in the competition center, and using any unmanned aerial vehicle as a relay unmanned aerial vehicle to generate an indirect communication link for the winner.
Further, the central unmanned aerial vehicle is an unmanned aerial vehicle which executes task planning in the unmanned aerial vehicle cluster; the relay unmanned aerial vehicle builds an intermediate unmanned aerial vehicle of a communication link for the other two unmanned aerial vehicles; the winner is the central unmanned aerial vehicle which is determined by each unmanned aerial vehicle, and the winner of each unmanned aerial vehicle can be changed according to the comparison condition of the number of the direct communication links.
Further, the determining of the locally optimal winner and its indirect communication link includes: the indirect communication link is a communication link formed by three unmanned aerial vehicles, the link comprises a relay unmanned aerial vehicle, the relay unmanned aerial vehicle can be in direct communication with the other two unmanned aerial vehicles, and the other two unmanned aerial vehicles can only be in indirect communication through the relay unmanned aerial vehicle.
Further, the finding of the globally optimal winner by using the indirect communication link includes: each unmanned aerial vehicle in the indirect communication link judges whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, S7 is executed, and if not, S5 is executed; and S7: each drone in the indirect communication link flooding its respective winner message through its direct communication link; and S5: s5 determines whether S5 is executed for the first time, if so, executes S6a, otherwise, executes S6b, and the winner message at least includes a winner and a direct communication link of the winner.
And S6a: in the indirect communication link, when the step S3 is executed, the unmanned aerial vehicle whose winner is updated diffuses the winner message thereof in the indirect communication link, the unmanned aerial vehicle which received the message compares the winner itself with all the received winners, and judges whether the number of direct communication links of the winner itself is the most, if not, the winner itself is updated to the winner which has the most number of direct communication links in all the received winner messages; and executing each unmanned aerial vehicle in the indirect communication link to judge whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, executing S7, and otherwise, executing S5.
S6b: s6a or S6b is executed last time and then the unmanned aerial vehicle which updates the winner diffuses the respectively updated winner message in the indirect communication link, the unmanned aerial vehicle which receives the message compares the own winner with all the received winners, and judges whether the number of the direct communication links of the own winner is the most or not, if not, the own winner is updated to the winner which has the most number of the direct communication links in all the received winner messages; and executing each unmanned aerial vehicle in the indirect communication link to judge whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, executing S7, and otherwise, executing S5.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a central unmanned aerial vehicle selection method aiming at the problem of single point failure of centralized mission planning. The method includes the steps that unmanned planes with the most direct communication links in a local area are found out through a broadcast communication mode to serve as candidate winners of a central unmanned plane, then an indirect communication link is constructed through the unmanned planes in the candidate winners direct communication link, information of the candidate winners is diffused to other unmanned planes, and finally the central unmanned planes are unified into the unmanned planes with the most direct communication links in an unmanned plane cluster through multiple rounds of message diffusion and comparison.
The method adopts the mode that unmanned aerial vehicles communicate with each other, ground command control is not needed, the method has the characteristic of autonomous selection and autonomous decision making, and meanwhile, a rapid greedy comparison mechanism is combined, so that the method has the characteristics of simplicity and feasibility, and when the original central unmanned aerial vehicle breaks down or is knocked down, a new central unmanned aerial vehicle can be selected rapidly and efficiently, so that the problem of single-point failure of centralized mission planning is solved, and the unmanned aerial vehicle group is prevented from falling into paralysis.
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Fig. 1 is a multi-drone profile of one embodiment of the present invention;
FIG. 2 is a flow chart of one embodiment of the present invention.
Detailed Description
The present invention will be further described with reference to the following examples, which are intended to illustrate only some, but not all, of the embodiments of the present invention. Other embodiments used by those skilled in the art can be obtained without any creative effort based on the embodiments in the present invention, and all of them belong to the protection scope of the present invention.
Example 1:
as shown in fig. 1 and 2, a central drone selection method for centralized mission planning of drones includes the following steps:
s1: initialization: inputting source data to each unmanned aerial vehicle through a data acquisition module of the unmanned aerial vehicle group;
all unmanned aerial vehicles need to have a bidirectional communication function and a broadcast communication function, have certain calculation power and can independently execute a task planning algorithm; all unmanned aerial vehicles are numbered in sequence, and the unmanned aerial vehicle with the number i represents the ith unmanned aerial vehicle; all unmanned aerial vehicles carry synchronous clocks; drone i considers the winner of the central drone as variable W i And is initialized to i, itself;
s2: each unmanned aerial vehicle in the unmanned aerial vehicle cluster generates a direct communication link;
each drone in the drone swarm generates a direct communication link, comprising: each unmanned aerial vehicle in the unmanned aerial vehicle cluster confirms a direct communication link through broadcasting state information; the direct communication link refers to a link through which two unmanned aerial vehicles can directly communicate in a broadcasting or bidirectional communication mode; the state information at least comprises information of whether the communication module and the calculation module are normal or not. The method comprises the following specific steps:
s21: at the moment t0, all the unmanned aerial vehicles broadcast state information to the surroundings within appointed time;
s22: at time t1, the unmanned aerial vehicle i (taking all numbers) records the number of pieces of state information received in the S21 process, and arranges out a number set (including the unmanned aerial vehicle i itself, for convenience of subsequent comparison) of the unmanned aerial vehicle capable of direct communication, which is called neighborhood N for short i (ii) a Neighborhood N i Is used as the number of elements of (1) | N i I denotes, | N i A larger | indicates that the drone i can directly communicate with a larger number of objects or have more direct communication links.
Corresponding to the spatial distribution of fig. 1, the neighborhoods of all drones are shown in table 1 below;
TABLE 1
S3: determining a locally optimal winner and its indirect communication links;
each unmanned aerial vehicle in the unmanned aerial vehicle cluster confirms a direct communication link through broadcasting state information; the direct communication link refers to a link through which two unmanned aerial vehicles can directly communicate in a broadcasting or bidirectional communication mode; the state information at least comprises information of whether the communication module and the calculation module are normal or not.
Any unmanned aerial vehicle in the unmanned aerial vehicle cluster finds out the unmanned aerial vehicle with the most direct communication links in all unmanned aerial vehicles on the direct communication links through broadcasting, the unmanned aerial vehicle with the most direct communication links is considered as a winner of the unmanned aerial vehicle in the competition center, and the unmanned aerial vehicle serves as a relay unmanned aerial vehicle to generate an indirect communication link for the winner.
The central unmanned aerial vehicle is an unmanned aerial vehicle for executing task planning in the unmanned aerial vehicle cluster; the relay unmanned aerial vehicle builds an intermediate unmanned aerial vehicle of a communication link for the other two unmanned aerial vehicles; the winner is the central unmanned aerial vehicle which is determined by each unmanned aerial vehicle, and the winner of each unmanned aerial vehicle can be changed according to the comparison condition of the number of the direct communication links.
The indirect communication link is a communication link formed by three unmanned aerial vehicles, the link comprises a relay unmanned aerial vehicle, the relay unmanned aerial vehicle can be in direct communication with the other two unmanned aerial vehicles, and the other two unmanned aerial vehicles can only be in indirect communication through the relay unmanned aerial vehicle. The method comprises the following specific steps:
s31: at the moment t2, all unmanned aerial vehicles broadcast respective neighborhood information within appointed time;
s32: at time t3, drone i (taking all numbers) obtains its neighborhood N i Neighborhood owned by each unmanned aerial vehicle; recording the neighborhood with the maximum number of elements as N imax I.e. drone imax is the locally optimal winner;
s33: judge winner W of drone i i And N imax Whether the corresponding unmanned aerial vehicle numbers imax are the same or not, if not, updating W i ；
S34: is calculated to belong to N i But not to N imax Is composed of elements of (2) i -N imax (relative complement);
s35: relative complement judgment N i -N imax Whether it is empty, if not unmanned aerial vehicle imax can indirectly communicate with the unmanned aerial vehicle contained in the relative complement through unmanned aerial vehicle i, an indirect communication link can be found out.
As shown in table 1, neighborhood N of drone 5 1 = {4,5,6,7}, meaning that the drone 5 can communicate directly with the drones 4, 6,7 in addition to itself; by broadcasting, the drones 4, 6,7 respectively associate their neighborhoods N 4 、N 6 、N 7 Sending to the unmanned aerial vehicle 5; unmanned aerial vehicle 5 discovery N 4 Has the largest number of elements, i.e., imax =4, and therefore its winner W needs to be set 5 Update from 5 to 4; calculating relative complement set N 5 -N 4 = 7, i.e. a 4-5-7 three-node indirect communication link may be formed, the drone 5 may further win the locally optimal winner W 5 =4 and its neighborhood N 4 And sending to the drone 7. The indirect communication links are also 4-6-7 and 7-9-10 as shown in table 1.
S4: a globally optimal winner is found using the indirect communication link.
Each unmanned aerial vehicle in the indirect communication link judges whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, S7 is executed, and if not, S5 is executed; and S7: each drone in the indirect communication link flooding its respective winner message through its direct communication link; and S5: s5, judging whether S5 is executed for the first time, if so, executing S6a, otherwise, executing S6b.
And S6a: in the indirect communication link, when the step S3 is executed, the unmanned aerial vehicle whose winner is updated diffuses the winner message thereof in the indirect communication link, the unmanned aerial vehicle which received the message compares the winner itself with all the received winners, and judges whether the number of direct communication links of the winner itself is the most, if not, the winner itself is updated to the winner which has the most number of direct communication links in all the received winner messages; and executing each unmanned aerial vehicle in the indirect communication link to judge whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, executing S7, and otherwise, executing S5. The winner message includes at least the winner and the direct communication link of the winner (in embodiments replaced by the neighborhood of the winner).
S6b: s6a or S6b is executed last time, and the drone that updated the winner diffuses the respective updated winner messages in the indirect communication link, the drone that received the message compares its own winner with all the received winners, and determines whether the number of direct communication links of its own winner is the largest, if not, updates its own winner to the winner that has the largest number of direct communication links in all the received winner messages; and executing each unmanned aerial vehicle in the indirect communication link to judge whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, executing S7, and otherwise, executing S5. Table 2 messaging and winner update procedure
As shown in table 2, after performing S6a and S6b 1 time, the winners of the drones in all indirect communication links are unified to the drone 4. Any unmanned aerial vehicle in the indirect communication link can be successively and reversely traced back through the unmanned aerial vehicle which has caused the winner to be updated the last time, and then is linked to the unmanned aerial vehicle 4; unmanned aerial vehicles outside the indirect communication link can directly communicate with the unmanned aerial vehicle in the indirect communication link, and are further linked to the unmanned aerial vehicle 4; finally, centralized mission planning centered on the drone 4 can be achieved.
Since it is difficult for the central drone to find other drones that have failed or have been knocked down by an enemy in an actual environment, the termination condition for message transmission and winner update is set so that the central drone can link to all the other drones, and it is highly likely that the termination condition cannot be met, so the present invention sets the termination condition to exceed a prescribed time limit (as shown in step S41) that can obtain an empirical value from multiple simulations or practices.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (4)
1. A central unmanned aerial vehicle selection method for unmanned aerial vehicle centralized mission planning is characterized by comprising the following steps:
s1: inputting source data to each unmanned aerial vehicle through a data acquisition module of the unmanned aerial vehicle cluster;
s2: each unmanned aerial vehicle in the unmanned aerial vehicle cluster generates a direct communication link;
s3: determining a locally optimal winner and its indirect communication links;
s4: finding a globally optimal winner using the indirect communication link;
the determination of the locally optimal winner and its indirect communication links includes: any unmanned aerial vehicle in the unmanned aerial vehicle cluster finds out the unmanned aerial vehicle with the most direct communication links in all unmanned aerial vehicles on the direct communication links through broadcasting, the unmanned aerial vehicle with the most direct communication links is considered as a winner of the unmanned aerial vehicle in the competition center, and the unmanned aerial vehicle serves as a relay unmanned aerial vehicle to generate an indirect communication link for the winner;
the central unmanned aerial vehicle is an unmanned aerial vehicle which executes task planning in the unmanned aerial vehicle cluster; the relay unmanned aerial vehicle builds an intermediate unmanned aerial vehicle of a communication link for the other two unmanned aerial vehicles; the winner is a central unmanned aerial vehicle which is determined by each unmanned aerial vehicle, and the winner of each unmanned aerial vehicle can be changed according to the comparison condition of the number of the direct communication links;
the determining of the locally optimal winner and its indirect communication links includes: the indirect communication link is a communication link formed by three unmanned aerial vehicles, the link comprises a relay unmanned aerial vehicle, the relay unmanned aerial vehicle can directly communicate with the other two unmanned aerial vehicles, and the other two unmanned aerial vehicles can only indirectly communicate through the relay unmanned aerial vehicle;
the finding of the globally optimal winner by using the indirect communication link includes: each unmanned aerial vehicle in the indirect communication link judges whether the clock of the unmanned aerial vehicle exceeds a specified time limit, if so, S7 is executed, and if not, S5 is executed; and S7: each drone in the indirect communication link disseminates a respective winner message through its direct communication link; and S5: s5, judging whether the S5 is executed for the first time, if so, executing S6a, otherwise, executing S6b; the winner message includes at least a winner and a direct communication link of the winner;
and S6a: in the indirect communication link, when the step S3 is executed, the unmanned aerial vehicle whose winner is updated diffuses the winner message thereof in the indirect communication link, the unmanned aerial vehicle which received the message compares the winner itself with all the received winners, and judges whether the number of direct communication links of the winner itself is the most, if not, the winner itself is updated to the winner which has the most number of direct communication links in all the received winner messages; executing each unmanned aerial vehicle in the indirect communication link to judge whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, executing S7, and otherwise, executing S5;
s6b: s6a or S6b is executed last time and then the unmanned aerial vehicle which updates the winner diffuses the respectively updated winner message in the indirect communication link, the unmanned aerial vehicle which receives the message compares the own winner with all the received winners, and judges whether the number of the direct communication links of the own winner is the most or not, if not, the own winner is updated to the winner which has the most number of the direct communication links in all the received winner messages; and executing each unmanned aerial vehicle in the indirect communication link to judge whether the clock of the unmanned aerial vehicle exceeds the specified time limit, if so, executing S7, and otherwise, executing S5.
2. The method of claim 1, wherein said inputting source data to each drone through a data acquisition module of the drone swarm comprises: the source data at least comprises the serial number, the specified time limit and time synchronization signals of each unmanned aerial vehicle in the unmanned aerial vehicle cluster, and the time synchronization signals are used for synchronizing the clocks of all unmanned aerial vehicles in the unmanned aerial vehicle cluster.
3. The method of claim 1, wherein said inputting source data to each drone through a data acquisition module of the drone swarm comprises: each unmanned aerial vehicle in the unmanned aerial vehicle cluster is required to be provided with a bidirectional communication module, a broadcast communication module and a calculation module.
4. The method of claim 1, wherein each drone in the fleet of drones generates a direct communication link, comprising: each unmanned aerial vehicle in the unmanned aerial vehicle cluster confirms a direct communication link through broadcasting state information; the direct communication link refers to a link through which two unmanned aerial vehicles can directly communicate in a broadcasting or bidirectional communication mode; the state information at least comprises information of whether the communication module and the calculation module are normal or not.
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