CN106940567B - Unmanned aerial vehicle formation optimal information interaction topology generation method and device - Google Patents
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Abstract
The invention provides a method and a device for generating optimal information interaction topology of unmanned aerial vehicle formation, wherein the method comprises the following steps: acquiring a communication network topology and a corresponding empowerment undirected graph according to a formation form of a two-dimensional persistent formation required by the unmanned aerial vehicle; calculating a two-dimensional optimal rigid graph of the weighted undirected graph according to a two-dimensional optimal rigid graph generation algorithm; and acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generating algorithm, wherein the two-dimensional optimal persistent diagram is the optimal information interaction topology of the formation. The device provided by the embodiment of the invention is realized based on the method. The invention can minimize the formation communication cost of the two-dimensional persistent formation in the process of keeping the formation.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a method and a device for generating optimal information interaction topology of unmanned aerial vehicle formation.
Background
During the takeoff and cruising phases, all Unmanned Aerial Vehicles (UAVs) generally perform information interaction through point-to-point communication links (communications links) to form a certain formation shape (formation shape or formation geometry), and keep the formation shape continuing to fly toward the target area. The communication links used therein are called Information interaction Topology (Information exchange Topology), communication Topology (communication Topology), connection Topology (connection Topology), Information Structure (Information Structure) or Information Topology (Information Topology) of the formation of the UAVs, which are only a part of the set of all available communication links between UAVs. For the sake of uniform expression, the name "information interaction topology" is used hereinafter. Meanwhile, the collection of all available Communication links between UAVs is called the UAV formation Communication Network Topology (Communication Network Topology).
Due to the fact that the communication distance between any two positions of the UAVs in the information interaction topology is different, the communication link between different UAVs in the information interaction topology has different communication costs and consumes corresponding battery power or fuel of the UAVs. In practice, the communication cost of the communication link between two UAVs is affected by many factors, such as mission requirements, communication distance, flight performance, safety, etc. For simplicity of illustration, the communication cost is directly expressed by communication distance.
At the same time, the battery power or fuel available to each UAV is limited. Therefore, how to reduce the battery power or fuel consumption of the UAV by optimizing the unmanned aerial vehicle formation information interaction topology becomes a technical problem which needs to be solved urgently.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an optimal information interaction topology generation method and device for unmanned aerial vehicle formation, which are used for realizing minimum formation communication cost of two-dimensional persistent formation in the process of keeping formation flying.
In a first aspect, an embodiment of the present invention provides an optimal information interaction topology generation method for unmanned aerial vehicle formation, where the method includes:
acquiring a communication network topology and a corresponding empowerment undirected graph according to a formation form of a two-dimensional persistent formation required by the unmanned aerial vehicle;
calculating a two-dimensional optimal rigid graph of the weighted undirected graph according to a two-dimensional optimal rigid graph generation algorithm;
and acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generating algorithm, wherein the two-dimensional optimal persistent diagram is the optimal information interaction topology of the formation.
Optionally, the two-dimensional optimal persistent map generation algorithm includes:
converting the two-dimensional optimal rigid graph into a first directed graph;
adding a virtual pilot node in the first directed graph to obtain a second directed graph; two outgoing arcs are arranged between the virtual pilot node and each node in the first directed graph, and the weight of each outgoing arc of the virtual pilot node is the same and is greater than the sum of the weights of all arcs in the first directed graph;
obtaining a first minimum tree diagram of the second directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the first minimum tree diagram to obtain a third directed graph;
deleting all arcs in the second directed graph corresponding to the first minimum tree graph and reverse arcs corresponding to the arcs in the second directed graph to obtain a fourth directed graph;
acquiring a second minimum tree diagram of the fourth directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the second minimum tree diagram to obtain a fifth directed graph;
merging the third directed graph and the fifth directed graph to obtain a sixth directed graph and the number m of arcs in the sixth directed graph;
and when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m 2n-3, the sixth directed graph is a two-dimensional optimal persistent graph.
Optionally, the two-dimensional optimal persistent map generation algorithm further includes:
when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m < (2n-3), acquiring two arcs corresponding to the ith edge in the two-dimensional optimal rigid graph, wherein the initial value of a symbol l is 1;
if the two arcs are not in the sixth directed graph, the degree of entry of the first edge corresponding to the two nodes is obtained;
when the incomes of two nodes corresponding to the ith edge are not both equal to 2, adding an incoming arc of any one node with the incomes smaller than 2, which is connected with the other node, into the sixth directed graph to obtain a seventh directed graph;
if the number m of arcs in the seventh directed graph is equal to (2n-3), the seventh directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the seventh directed graph.
Optionally, the two-dimensional optimal persistent map generation algorithm further includes:
when the incomes of two nodes corresponding to the ith edge are both equal to 2, adding an arc corresponding to the ith edge into the sixth directed graph to obtain a seventh directed graph; the arc is an incoming arc of the first node corresponding to the first edge;
searching a second node with the degree of entry less than 2 in the seventh directed graph according to a mode of firstly entering 1 and then entering 0, and acquiring a path with the least hop count between the second node and the first node;
reversing all arcs corresponding to the path with the least hop number to obtain an eighth directed graph;
if the number m of arcs in the eighth directed graph is equal to (2n-3), the eighth directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the eighth directed graph.
Optionally, the two-dimensional optimal persistent map generation algorithm further includes:
and increasing the value of the symbol l by 1, and if the symbol l is less than or equal to (2n-3), continuing to judge whether two arcs corresponding to the l-th edge are not in the sixth directed graph.
In a second aspect, an embodiment of the present invention further provides an apparatus for generating an optimal information interaction topology for formation of unmanned aerial vehicles, where the apparatus includes:
the empowerment undirected graph acquisition module is used for acquiring the communication network topology and the empowerment undirected graph corresponding to the communication network topology according to a formation form of a two-dimensional persistent formation formed by the unmanned aerial vehicles;
the two-dimensional optimal rigid graph acquisition module is used for calculating a two-dimensional optimal rigid graph of the weighted undirected graph according to a two-dimensional optimal rigid graph generation algorithm;
and the optimal information interaction topology acquisition module is used for acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generation algorithm, wherein the two-dimensional optimal persistent diagram is the optimal information interaction topology of the formation.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module, the two-dimensional optimal persistent diagram by using a two-dimensional optimal persistent diagram generation algorithm includes:
converting the two-dimensional optimal rigid graph into a first directed graph;
adding a virtual pilot node in the first directed graph to obtain a second directed graph; two outgoing arcs are arranged between the virtual pilot node and each node in the first directed graph, and the weight of each outgoing arc of the virtual pilot node is the same and is greater than the sum of the weights of all arcs in the first directed graph;
obtaining a first minimum tree diagram of the second directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the first minimum tree diagram to obtain a third directed graph;
deleting all arcs in the second directed graph corresponding to the first minimum tree graph and reverse arcs corresponding to the arcs in the second directed graph to obtain a fourth directed graph;
acquiring a second minimum tree diagram of the fourth directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the second minimum tree diagram to obtain a fifth directed graph;
merging the third directed graph and the fifth directed graph to obtain a sixth directed graph and the number m of arcs in the sixth directed graph;
and when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m 2n-3, the sixth directed graph is a two-dimensional optimal persistent graph.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module, the two-dimensional optimal persistent diagram by using the two-dimensional optimal persistent diagram generation algorithm further includes:
when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m < (2n-3), acquiring two arcs corresponding to the ith edge in the two-dimensional optimal rigid graph, wherein the initial value of a symbol l is 1;
if the two arcs are not in the sixth directed graph, the degree of entry of the first edge corresponding to the two nodes is obtained;
when the incomes of two nodes corresponding to the ith edge are not both equal to 2, adding an incoming arc of any one node with the incomes smaller than 2, which is connected with the other node, into the sixth directed graph to obtain a seventh directed graph;
if the number m of arcs in the seventh directed graph is equal to (2n-3), the seventh directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the seventh directed graph.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module, the two-dimensional optimal persistent diagram by using the two-dimensional optimal persistent diagram generation algorithm further includes:
when the incomes of two nodes corresponding to the ith edge are both equal to 2, adding an arc corresponding to the ith edge into the sixth directed graph to obtain a seventh directed graph; the arc is an incoming arc of the first node corresponding to the first edge;
searching a second node with the degree of entry less than 2 in the seventh directed graph according to a mode of firstly entering 1 and then entering 0, and acquiring a path with the least hop count between the second node and the first node;
reversing all arcs corresponding to the path with the least hop number to obtain an eighth directed graph;
if the number m of arcs in the eighth directed graph is equal to (2n-3), the eighth directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the eighth directed graph.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module, the two-dimensional optimal persistent diagram by using the two-dimensional optimal persistent diagram generation algorithm further includes:
and increasing the value of the symbol l by 1, and if the symbol l is less than or equal to (2n-3), continuing to judge whether two arcs corresponding to the l-th edge are not in the sixth directed graph.
According to the technical scheme, the communication network topology and the corresponding empowerment undirected graph are obtained according to the formation form of the two-dimensional persistent formation formed by the unmanned aerial vehicles; then, calculating a two-dimensional optimal rigid graph of the weighted undirected graph according to a two-dimensional optimal rigid graph generation algorithm; and finally, acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generating algorithm, wherein the two-dimensional optimal persistent diagram is the optimal information interaction topology of the formation. Compared with the prior art, the method can calculate the optimal information interaction topology of the two-dimensional persistent formation in a shorter time, so that the formation communication cost of the two-dimensional persistent formation in the formation keeping process is minimum.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for generating an optimal information interaction topology for formation of unmanned aerial vehicles according to an embodiment of the present invention;
fig. 2(a) - (b) are schematic diagrams of the formation and relative position of a two-dimensional persistent formation composed of 5 drones in the embodiment of the present invention; unmanned aerial vehicle UAV1, UAV2, UAV3, UAV4, and UAV5 at positions 1,2,3,4, and 5, respectively, of the formation;
fig. 3(a) - (d) are schematic diagrams of a process for acquiring an optimal information interaction topology of a two-dimensional persistent formation composed of 5 unmanned aerial vehicles in fig. 2 by using the method in fig. 1; finally use UAV1 as a formation pilot;
FIG. 4 is a schematic diagram of an optimal information interaction topology obtained by the related art, using a UAV5 as a formation pilot;
fig. 5(a) - (b) are schematic diagrams of the formation and relative position of a two-dimensional persistent formation composed of 16 drones in the embodiment of the present invention; wherein, unmanned aerial vehicle UAV1, UAV2, UAV3, UAV4, UAV5, UAV6, UAV7, UAV8, UAV9, UAV10, UAV11, UAV12, UAV13, UAV14, UAV15, and UAV16 are at positions No. 1, No. 2, No. 3, No. 4, No. 5, No. 6, No. 7, No. 8, No. 9, No. 10, No. 11, No. 12, No. 13, No. 14, No. 15, and No. 16, respectively, of the formation;
fig. 6(a) - (h) are schematic diagrams of a process for acquiring an optimal information interaction topology of a two-dimensional persistent formation composed of 16 unmanned aerial vehicles in fig. 5 by using the method in fig. 1; finally use UAV1 as a formation pilot;
FIG. 7 is a schematic diagram of an optimal information interaction topology obtained by the related art, using a UAV13 as a formation pilot;
fig. 8 is a block diagram of an optimal information interaction topology generation apparatus for formation of unmanned aerial vehicles according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for generating an optimal information interaction topology for formation of unmanned aerial vehicles according to an embodiment of the present invention. As shown in fig. 1, the method includes:
101. and acquiring the communication network topology and the corresponding empowerment undirected graph according to a formation form of the two-dimensional persistent formation required by the unmanned aerial vehicle.
In practical application, the embodiment of the invention determines the available communication links among the unmanned aerial vehicles in the formation according to the formation of the preset formation and the communication range of the unmanned aerial vehicles, and constructs the communication network topology of the formation by taking the unmanned aerial vehicles as nodes and the available communication links as arcs. The distance between any two unmanned aerial vehicles is within the communication range of the unmanned aerial vehicles, two-way communication links are arranged between the two unmanned aerial vehicles, and the communication cost of each communication link is determined by the corresponding communication distance.
Assume that n UAVs form and maintain a two-dimensional formation S by one-way communication between the UAVs. The n positions in the formation S are respectively numbered as {1,2, …, n }, and the height of each position is identical. The formation communication network topology can be represented by an entitled directed graph D ═ V, a, W, P:
(1)V＝{v i1 ≦ i ≦ n is the set of nodes in the graph, where vi denotes UAVi.
(2)
I is not less than 1, j is not less than n is an arc set in the figure, wherein the arc aij＝(vi,vj) Indicating that there is a communication link available from UAVi to UAVj so that UAVi can send information to UAVj.
(3)W＝{w(aij)},aije.A is the set of weights for all arcs in the graph, where w (a)ij) Representing a communication link a from UAVi to UAVjijThe cost of (a).
(4)P＝{p i1 ≦ i ≦ n is the specific set of positions of each UAV in the formation S, referred to as UAV Position Configuration (UAV Position Configuration). Wherein n positions in the formation S are respectively numbered as {1, 2.,. n }, and then p is more than or equal to 1iN indicates the specific position of UAVi in the formation S.
In order to maintain formation, the UAVs need to use corresponding one-way communication links for information interaction to keep the distance between them constant, but all the one-way communication links are not necessarily used, that is, the information interaction topology T ═ V, a used for formation to maintain formation*,W*P) is just one sub-graph of the communication network topology D ═ V, a, W, P), where
Indicating that the UAVi needs to send self information to the UAVj so that the UAVj can adjust its parameters to keep the distance from the UAVi constant according to the received information, i.e., the UAVj has a distance constraint from the UAVi. In the information interaction topology T, the node viThe degree of entry indicates how many other UAVs the UAVi needs to receive information from, i.e., the number of distance constraints with other UAVs, denoted d-(i) (ii) a Node viOut-degree of (d) indicates how many other UAVs the UAVi needs to send information to, and is denoted as+(i)。
102. And calculating the two-dimensional optimal rigid map of the weighted undirected graph according to a two-dimensional optimal rigid map generation algorithm.
It should be noted that, in the embodiment of the present invention, the two-dimensional optimal stiffness map is defined as follows:
if the sum of the edge weights of a Two-Dimensional minimum rigid graph is the minimum of all Two-Dimensional rigid graphs with the same node, the Two-Dimensional minimum rigid graph is a Two-Dimensional Optimal rigid graph (2 DORG).
In the embodiment of the invention, the two-dimensional optimal rigid map is obtained by adopting the existing two-dimensional optimal rigid map generation algorithm, and the basic steps of the algorithm are shown in table 1.
TABLE 1
Note that the time complexity of the two-dimensional optimal rigid map generation algorithm shown in table 1 is mainly determined by Step 4. While Step4 needs to compute | E | times at most, and the time complexity of computing the rank of matrix M i-th time is
Wherein m isiThe number of rows of M at the i-th calculation. Since the two-dimensional optimal rigid graph generation algorithm shown in Table 1 operates, it is best to add M each timeCAll can meet the requirements in Step 6. Step4 only needs to calculate n 2 x V3 times, and the i-th calculation is performed by M line number MiTherefore, the time complexity of the two-dimensional optimal rigid map generation algorithm shown in table 1 is at least:
103. and acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generation algorithm.
It should be noted that, in the embodiment of the present invention, the two-dimensional optimal persistent graph is defined as follows:
in the Two-Dimensional space, if the degree of each node of a directed Graph is less than or equal to 2, and the corresponding undirected Graph is a Two-Dimensional optimal rigid Graph, the directed Graph is a Two-Dimensional optimal persistent Graph (2 DOPG).
The specific steps of acquiring the two-dimensional optimal persistent diagram by utilizing the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generation algorithm in the embodiment of the invention comprise:
1031. and converting the two-dimensional optimal rigid graph into a first directed graph.
1032. Adding a virtual pilot node in the first directed graph to obtain a second directed graph; two arcs are arranged between the virtual pilot node and each node in the first directed graph, and the weight of each arc of the virtual pilot node is the same and is larger than the sum of the weights of all arcs in the first directed graph.
1033. And acquiring a first minimum tree diagram of the second directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the first minimum tree diagram to obtain a third directed graph.
1034. And deleting all arcs in the second directed graph corresponding to the first minimum tree graph and reverse arcs corresponding to the arcs in the second directed graph to obtain a fourth directed graph.
1035. And acquiring a second minimum tree diagram of the fourth directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the second minimum tree diagram to obtain a fifth directed graph.
1036. And merging the third directed graph and the fifth directed graph to obtain a sixth directed graph and the number m of arcs in the sixth directed graph.
1037. And when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m 2n-3, the sixth directed graph is a two-dimensional optimal persistent graph.
The specific steps of acquiring the two-dimensional optimal persistent diagram by utilizing the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generation algorithm in the embodiment of the invention comprise:
when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m < (2n-3), acquiring two arcs corresponding to the ith edge in the two-dimensional optimal rigid graph, wherein the initial value of a symbol l is 1;
if the two arcs are not in the sixth directed graph, the degree of entry of the first edge corresponding to the two nodes is obtained;
when the incomes of two nodes corresponding to the ith edge are not both equal to 2, adding an incoming arc of any one node with the incomes smaller than 2, which is connected with the other node, into the sixth directed graph to obtain a seventh directed graph;
if the number m of arcs in the seventh directed graph is equal to (2n-3), the seventh directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the seventh directed graph.
Based on the above description, the embodiment of the present invention provides a Two-Dimensional Optimal persistent Graph generation algorithm based on a Two-Dimensional Optimal Rigid Graph and a Minimum Cost architecture (2 DORG _ MCA), and the steps of the algorithm are shown in table 2.
TABLE 2
It should be noted that the Minimum tree diagram (MCA) in this embodiment refers to a Minimum spanning tree of an entitled directed graph. The first algorithm to solve the MCA problem was the Edmonds algorithm, whose computational complexity was O (| A | × | V |), where | A | and | V | are the number of arcs and the number of nodes in the weighted directed graph, respectively, and later Gabow et al proposed a faster implementation for the Edmonds algorithm, whose computational complexity was O (| A | + | V | × log | V |).
It can be understood that the two-dimensional optimal persistent diagram generation algorithm in table 2 is mainly determined by the time complexity of Step3 and Step 5. For example, Step3 and Step5 in table 2 of the embodiment of the present invention are implemented by Edmonds algorithm proposed by Gabow et al, so that the time complexity of the algorithm is about O (2 × (| a | + | V | × log | V |).
From Step1 in table 2, | a | ═ 2 × | E*And from the characteristics of the two-dimensional optimal stiffness map, the two-dimensional optimal stiffness map R ═ V, E*,W*Number of edges | E) of P)*Equal to 2 x V-3, the time complexity of the algorithm is again about O (2 x (4 x V + V x log V)).
The best two-dimensional optimal persistent graph generation algorithm in the prior art needs to calculate the rank of the matrix, so that the time complexity is at least O (| V |)3) Compared with the two-dimensional optimal persistent graph generation algorithm, the two-dimensional optimal persistent graph generation algorithm in the embodiment of the invention has lower time complexity.
In the embodiment of the invention, all the UAVs in the formation can be used as formation pilots, so that the two-dimensional optimal persistent graph is the optimal information interaction topology of the formation.
The following examples verify the superiority and effectiveness of the unmanned aerial vehicle formation optimal information interaction topology generation method provided by the embodiment of the invention.
1. And the optimal information interaction topology of the small-scale two-dimensional persistent formation formed by the unmanned aerial vehicles.
Assuming a small-scale two-dimensional persistent formation consisting of 5 drones (UAV1, UAV2, UAV3, UAV4, UAV 5), the communication range for each airplane is 1600 m. They need to form and maintain a two-dimensional space formation as shown in fig. 2(a), where the formation positions are numbered {1,2,3,4,5}, respectively, and UAV1, UAV2, UAV3, UAV4, and UAV5 are at positions 1,2,3,4, and 5, respectively, of the formation; the distance between them is shown in fig. 2 (a); if the position No. 4 in the formation is taken as the origin of the plane coordinate system, the coordinates of each position in the formation S of the two-dimensional persistent formation are as shown in fig. 2 (b).
Based on the optimization method, firstly, the planet position is configured as P ═ {1,2,3,4,5}, then the corresponding communication network topology D is constructed as (V, a, W, P), and then the arc in D is converted into an edge, so as to obtain the corresponding weighted undirected graph G ═ V, E, W, P. Obtained according to the two-dimensional optimal rigid graph acquisition method shown in Table 1G, as shown in fig. 3 (a). And obtaining a two-dimensional optimal persistent diagram T corresponding to the R according to the two-dimensional optimal persistent diagram obtaining method shown in the table 2. Wherein, the minimum tree graph T 'is obtained from Step3 in Table 2'1As shown in FIG. 3 (b); minimum Tree graph T 'from Step5 in Table 2'2As shown in FIG. 3 (c); finally, mixing T'1V in (1)0And v0Get T after arc-out deletion1Prepared from T'2V in (1)0And v0Get T after arc-out deletion2Then, will T1And T2The combined directed graph T is shown in fig. 3 (d). Since the total number of arcs in T is the same as the total number of edges in R, the condition of Step7 in Table 2 is satisfied, and T is a two-dimensional optimal persistent graph corresponding to R. And because the degree of entry of the node v1 in T is 0, that is, T is the optimal information interaction topology of the two-dimensional persistent formation, the UAV1 serves as a formation navigator, and the corresponding formation communication cost is 4912.
In contrast, the optimal information interaction topology obtained by the best two-dimensional optimal persistent graph generation algorithm in the prior art is shown in fig. 4, and the UAV5 is used as a formation navigator, and its corresponding formation communication cost is 4912, but its time complexity is higher than that of the two-dimensional optimal persistent graph acquisition method shown in table 2.
2. And the optimal information interaction topology of the large-scale two-dimensional persistent formation formed by the unmanned aerial vehicles.
Assuming a two-dimensional persistent formation consisting of 16 drones (UAV1, UAV2, UAV3, UAV4, UAV5, UAV6, UAV7, UAV8, UAV9, UAV10, UAV11, UAV12, UAV13, UAV14, UAV15, and UAV16), the communication range of each aircraft is 1600m, the formation needs to form and maintain a two-dimensional spatial formation as shown in fig. 5. The formation positions are respectively numbered as {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}, and the positions of UAV1, UAV2, UAV3, UAV4, UAV5, UAV6, UAV7, UAV8, UAV9, UAV10, UAV11, UAV12, UAV13, UAV14, UAV15 and UAV16 at positions 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 and 16 of the formation; the relative position of each aircraft in the two-dimensional space is shown in fig. 5(a), and if the position No. 10 is taken as the origin of the plane coordinate system, the coordinates of each position in the formation are shown in fig. 5 (b).
Based on the optimization method, first, the planet position is configured as P {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16}, then the corresponding communication network topology D ═ V, a, W, P is constructed, then the arc in the communication network topology D is converted into an edge, the corresponding weighted undirected graph G ═ V, E, W, P is obtained, and the two-dimensional optimal rigid graph R of the weighted undirected graph G is obtained according to the two-dimensional optimal rigid graph obtaining method shown in table 1, as shown in fig. 6 (a). Obtaining a two-dimensional optimal persistent diagram T corresponding to the R according to the two-dimensional optimal persistent diagram obtaining method shown in the table 2, wherein the specific process is as follows:
(1) minimum Tree graph T 'from Step 3'1As shown in fig. 6 (b).
(2) Minimum Tree graph T 'from Step 5'2As shown in fig. 6 (c).
(3) From Step6 by T1And T2The combined directed graph T is shown in fig. 6 (d). Wherein, T1Is prepared from T'1V in (1)0And v0Is deleted to obtain a directed graph, T2Is prepared from T'2V in (1)0And v0And (4) deleting the outgoing arc to obtain the directed graph.
(4) Due to the edge e in R39Two corresponding arcs a39And a93Are not in T, and v in T3And v9All of the degrees of income are equal to 2, i.e., the condition of Step11 is satisfied, and therefore: firstly, a is39Added to T, the results are shown as the dashed arcs in FIG. 6 (e); then finding out a node v with the degree of income less than 22So that from v2To v9Having a way with a minimum number of hops (v)2,v9) (ii) a All arcs on this line are then reversed, with the result shown as the dotted-dashed arc in fig. 6 (f).
(5) Due to the edge e in R815Two corresponding arcs a815And a158Are not in T, and v in T8And v15All of the degrees of income are equal to 2, i.e., the condition of Step11 is satisfied, and therefore: firstly, a is815Added to T, the result is shown by the dotted arc in FIG. 6(g)Shown in the specification; then finding out a node v with the degree of income less than 25So that from v5To v15Having a way with a minimum number of hops (v)5,v7,v8,v15) (ii) a All arcs on this line are then reversed, with the result shown as the dotted-dashed arc in fig. 6 (h). Since the number of arcs in T is the same as the number of edges in R at this time, the condition of Step12 is satisfied, and T is a two-dimensional optimal persistent diagram of R. And because of node v in T1The degree of engagement is 0, i.e. T is the optimal information interaction topology of the two-dimensional persistent formation, the UAV1 is used as a formation navigator, and the corresponding formation communication cost is 17714.
In contrast, the optimal information interaction topology obtained by the best two-dimensional optimal persistent graph generation algorithm in the prior art is shown in fig. 7, and the UAV13 is used as a formation navigator, and its corresponding formation communication cost is 17714, but its time complexity is higher than that of the two-dimensional optimal persistent graph acquisition method shown in table 2 above.
The embodiment of the present invention further provides an apparatus for generating an optimal information interaction topology for formation of unmanned aerial vehicles, as shown in fig. 8, including:
the empowerment undirected graph obtaining module M1 is used for obtaining the communication network topology and the empowerment undirected graph corresponding to the communication network topology according to a formation form of the two-dimensional persistent formation formed by the unmanned aerial vehicles;
the two-dimensional optimal rigid map acquisition module M2 is used for calculating a two-dimensional optimal rigid map of the weighted undirected map according to a two-dimensional optimal rigid map generation algorithm;
and the optimal information interaction topology obtaining module M3 is used for obtaining a two-dimensional optimal persistent map according to the two-dimensional optimal rigid map and the two-dimensional optimal persistent map generating algorithm, wherein the two-dimensional optimal persistent map is the optimal information interaction topology of the formation.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module M3, a two-dimensional optimal persistent diagram by using a two-dimensional optimal persistent diagram generation algorithm includes:
converting the two-dimensional optimal rigid graph R into a first directed graph DR；
In the first directed graph DRIn adding virtualizationNavigator node V0Get the second directed graph DR'; the virtual navigator node V0And the first directed graph DRWherein two arc outlets are arranged between each node, and the virtual navigator node V0The weight of each outgoing arc is the same and is larger than the sum of the weights of all arcs in the first directed graph;
obtaining the second directed graph DR' first minimum Tree graph T1', and deleting said first minimum treemap T1' the virtual pilot node V0And the corresponding arc discharge to obtain a third directed graph T1；
Deleting the second directed graph DR' corresponding to the first minimum treemap T1' all arcs in and their corresponding inverse arcs give a fourth directed graph DR”；
Obtaining the fourth directed graph DR"second minimum Tree graph T2', and deleting said second minimum treemap T2' the virtual pilot node V0And corresponding arc discharge to obtain a fifth directed graph T2；
Merging the third directed graph T1And the fifth directed graph T2Obtaining a sixth directed graph T and the number m of arcs in the sixth directed graph T;
and when the number of nodes of the two-dimensional optimal rigid graph R is n and m satisfies m 2n-3, the sixth directed graph T is a two-dimensional optimal persistent graph.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module M3, a two-dimensional optimal persistent diagram by using a two-dimensional optimal persistent diagram generation algorithm further includes:
when the number of nodes of the two-dimensional optimal rigid graph R is n and m satisfies m < (2n-3), acquiring two arcs corresponding to the ith edge in the two-dimensional optimal rigid graph R, wherein the initial value of a symbol l is 1;
if the two arcs are not in the sixth directed graph, the degree of entry of the first edge corresponding to the two nodes is obtained;
when the incomes of two nodes corresponding to the ith edge are not both equal to 2, adding an incoming arc of any one node with the incomes smaller than 2, which is connected with the other node, into the sixth directed graph to obtain a seventh directed graph;
if the number m of arcs in the seventh directed graph is equal to (2n-3), the seventh directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the seventh directed graph.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module M3, a two-dimensional optimal persistent diagram by using a two-dimensional optimal persistent diagram generation algorithm further includes:
when the incomes of two nodes corresponding to the ith edge are both equal to 2, adding an arc corresponding to the ith edge into the sixth directed graph to obtain a seventh directed graph; the arc is an incoming arc of the first node corresponding to the first edge;
searching a second node with the degree of entry less than 2 in the seventh directed graph according to a mode of firstly entering 1 and then entering 0, and acquiring a path with the least hop count between the second node and the first node;
reversing all arcs corresponding to the path with the least hop number to obtain an eighth directed graph;
if the number m of arcs in the eighth directed graph is equal to (2n-3), the eighth directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the eighth directed graph.
Optionally, the step of acquiring, by the optimal information interaction topology acquisition module M3, a two-dimensional optimal persistent diagram by using a two-dimensional optimal persistent diagram generation algorithm further includes:
and increasing the value of the symbol l by 1, and if the symbol l is less than or equal to (2n-3), continuing to judge whether two arcs corresponding to the l-th edge are not in the sixth directed graph T.
It should be noted that the device for generating the optimal information interaction topology for formation of unmanned aerial vehicles provided by the embodiment of the present invention corresponds to the above method one to one, and the implementation details of the above method are also applicable to the above device, and the system is not described in detail in the embodiment of the present invention.
In the description of the present invention, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the devices in an embodiment may be adaptively changed and placed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in a device of a browser terminal according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (8)
1. An optimal information interaction topology generation method for unmanned aerial vehicle formation is characterized by comprising the following steps:
acquiring a communication network topology and a corresponding empowerment undirected graph according to a formation form of a two-dimensional persistent formation required by the unmanned aerial vehicle;
calculating a two-dimensional optimal rigid graph of the weighted undirected graph according to a two-dimensional optimal rigid graph generation algorithm;
acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generating algorithm, wherein the two-dimensional optimal persistent diagram is the optimal information interaction topology of the formation;
wherein the two-dimensional optimal persistent graph generation algorithm comprises:
converting the two-dimensional optimal rigid graph into a first directed graph;
adding a virtual pilot node in the first directed graph to obtain a second directed graph; two outgoing arcs are arranged between the virtual pilot node and each node in the first directed graph, and the weight of each outgoing arc of the virtual pilot node is the same and is greater than the sum of the weights of all arcs in the first directed graph;
obtaining a first minimum tree diagram of the second directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the first minimum tree diagram to obtain a third directed graph;
deleting all arcs in the second directed graph corresponding to the first minimum tree graph and reverse arcs corresponding to the arcs in the second directed graph to obtain a fourth directed graph;
acquiring a second minimum tree diagram of the fourth directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the second minimum tree diagram to obtain a fifth directed graph;
merging the third directed graph and the fifth directed graph to obtain a sixth directed graph and the number m of arcs in the sixth directed graph;
and when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m 2n-3, the sixth directed graph is a two-dimensional optimal persistent graph.
2. The method for generating the optimal information interaction topology for unmanned aerial vehicle formation according to claim 1, wherein the two-dimensional optimal persistent diagram generation algorithm further comprises:
when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m < (2n-3), acquiring two arcs corresponding to the ith edge in the two-dimensional optimal rigid graph, wherein the initial value of a symbol l is 1;
if the two arcs are not in the sixth directed graph, the degree of entry of the first edge corresponding to the two nodes is obtained;
when the incomes of the two nodes corresponding to the ith edge are not both equal to 2, adding an incoming arc of any one of the two nodes corresponding to the ith edge, the incomes of which are less than 2, connected with the other node into the sixth directed graph to obtain a seventh directed graph;
if the number m of arcs in the seventh directed graph is equal to (2n-3), the seventh directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the seventh directed graph.
3. The method for generating the optimal information interaction topology for unmanned aerial vehicle formation according to claim 2, wherein the two-dimensional optimal persistent diagram generation algorithm further comprises:
when the incomes of two nodes corresponding to the ith edge are both equal to 2, adding an arc corresponding to the ith edge into the sixth directed graph to obtain a seventh directed graph; an arc corresponding to the ith edge is an incoming arc of a first node corresponding to the ith edge;
searching a second node with the degree of entry less than 2 in the seventh directed graph according to a mode of firstly entering 1 and then entering 0, and acquiring a path with the least hop count between the second node and the first node;
reversing all arcs corresponding to the path with the least hop number to obtain an eighth directed graph;
if the number m of arcs in the eighth directed graph is equal to (2n-3), the eighth directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the eighth directed graph.
4. The method for generating the optimal information interaction topology for unmanned aerial vehicle formation according to claim 2 or 3, wherein the two-dimensional optimal persistent graph generation algorithm further comprises:
and increasing the value of the symbol l by 1, and if the symbol l is less than or equal to (2n-3), continuing to judge whether two arcs corresponding to the l-th edge are not in the sixth directed graph.
5. An optimal information interaction topology generation device for unmanned aerial vehicle formation, which is characterized by comprising:
the empowerment undirected graph acquisition module is used for acquiring the communication network topology and the empowerment undirected graph corresponding to the communication network topology according to a formation form of a two-dimensional persistent formation formed by the unmanned aerial vehicles;
the two-dimensional optimal rigid graph acquisition module is used for calculating a two-dimensional optimal rigid graph of the weighted undirected graph according to a two-dimensional optimal rigid graph generation algorithm;
the optimal information interaction topology acquisition module is used for acquiring a two-dimensional optimal persistent diagram according to the two-dimensional optimal rigid diagram and the two-dimensional optimal persistent diagram generation algorithm, and the two-dimensional optimal persistent diagram is the optimal information interaction topology of the formation;
wherein: the step that the optimal information interaction topology obtaining module obtains the two-dimensional optimal persistent diagram by using the two-dimensional optimal persistent diagram generating algorithm comprises the following steps:
converting the two-dimensional optimal rigid graph into a first directed graph;
adding a virtual pilot node in the first directed graph to obtain a second directed graph; two outgoing arcs are arranged between the virtual pilot node and each node in the first directed graph, and the weight of each outgoing arc of the virtual pilot node is the same and is greater than the sum of the weights of all arcs in the first directed graph;
obtaining a first minimum tree diagram of the second directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the first minimum tree diagram to obtain a third directed graph;
deleting all arcs in the second directed graph corresponding to the first minimum tree graph and reverse arcs corresponding to the arcs in the second directed graph to obtain a fourth directed graph;
acquiring a second minimum tree diagram of the fourth directed graph, and deleting the virtual pilot node and the corresponding outgoing arc in the second minimum tree diagram to obtain a fifth directed graph;
merging the third directed graph and the fifth directed graph to obtain a sixth directed graph and the number m of arcs in the sixth directed graph;
and when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m 2n-3, the sixth directed graph is a two-dimensional optimal persistent graph.
6. The device for generating the optimal information interaction topology for formation of unmanned aerial vehicles according to claim 5, wherein the step of acquiring the two-dimensional optimal persistent map by the optimal information interaction topology acquisition module using the two-dimensional optimal persistent map generation algorithm further comprises:
when the number of nodes of the two-dimensional optimal rigid graph is n and m satisfies m < (2n-3), acquiring two arcs corresponding to the ith edge in the two-dimensional optimal rigid graph, wherein the initial value of a symbol l is 1;
if the two arcs are not in the sixth directed graph, the degree of entry of the first edge corresponding to the two nodes is obtained;
when the incomes of the two nodes corresponding to the ith edge are not both equal to 2, adding an incoming arc of any one of the two nodes corresponding to the ith edge, the incomes of which are less than 2, connected with the other node into the sixth directed graph to obtain a seventh directed graph;
if the number m of arcs in the seventh directed graph is equal to (2n-3), the seventh directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the seventh directed graph.
7. The device for generating the optimal information interaction topology for formation of unmanned aerial vehicles according to claim 6, wherein the step of acquiring the two-dimensional optimal persistent map by the optimal information interaction topology acquisition module using the two-dimensional optimal persistent map generation algorithm further comprises:
when the incomes of two nodes corresponding to the ith edge are both equal to 2, adding an arc corresponding to the ith edge into the sixth directed graph to obtain a seventh directed graph; an arc corresponding to the ith edge is an incoming arc of a first node corresponding to the ith edge;
searching a second node with the degree of entry less than 2 in the seventh directed graph according to a mode of firstly entering 1 and then entering 0, and acquiring a path with the least hop count between the second node and the first node;
reversing all arcs corresponding to the path with the least hop number to obtain an eighth directed graph;
if the number m of arcs in the eighth directed graph is equal to (2n-3), the eighth directed graph is a two-dimensional optimal persistent graph; otherwise, updating the data in the sixth directed graph to the data in the eighth directed graph.
8. The device for generating the optimal information interaction topology for formation of unmanned aerial vehicles according to claim 6 or 7, wherein the step of acquiring the two-dimensional optimal persistent map by the optimal information interaction topology acquisition module using the two-dimensional optimal persistent map generation algorithm further comprises:
and increasing the value of the symbol l by 1, and if the symbol l is less than or equal to (2n-3), continuing to judge whether two arcs corresponding to the l-th edge are not in the sixth directed graph.
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| CN110598272B (en) * | 2019-08-22 | 2022-11-22 | 合肥工业大学 | Heuristic generation method and device for multi-unmanned platform information interaction topology |
| CN111107604B (en) * | 2019-11-05 | 2022-05-24 | 合肥工业大学 | Rapid optimization method and device for unmanned platform information-aware network |
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| CN110989653B (en) * | 2019-11-05 | 2022-07-12 | 合肥工业大学 | Rapid information interaction topology generation method and device for cooperative situation awareness of unmanned aerial vehicle |
| CN111638726B (en) * | 2020-05-27 | 2021-07-27 | 北京理工大学 | Event trigger communication-based multi-unmanned aerial vehicle formation consistency control method |
| CN112904847B (en) * | 2021-01-18 | 2022-12-13 | 中国人民解放军海军航空大学 | Two-dimensional formation communication topology generation and expression method based on minimum weak rigidity |
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