Route method and device for formation control unmanned aerial vehicle network

Abstract

The application discloses a kind of method and equipment for the routing of formation control unmanned aerial vehicle network, wherein the method comprises: each node periodically utilizes Hello message to carry out link sensing, to know the adjacent node with its existence communication link;Hello message carries the spatial position and expected position offset of node;Based on the adjacent node, build one-hop neighbor set and two-hop neighbor set;Based on the spatial position and expected position offset, determine link quality parameter;Based on link quality parameter, one-hop neighbor set and two-hop neighbor set, establish multipoint relay (MPR) set;TC message is sent to other nodes in network by network broadcast;TC message carries the link quality parameter between node itself and adjacent node;Based on the received TC message, according to the principle that the quality weight of routing path is minimum, generate routing table;Quality weight is the cumulative value of link quality parameter on all links in path. By using the application, the routing performance of formation control unmanned aerial vehicle network can be improved.

Description

Technical Field

[0001] This invention relates to mobile communication technology, and in particular to a routing method and apparatus for swarm control of unmanned aerial vehicle (UAV) networks. Background Technology

[0002] Dynamic, multi-tasking unmanned aerial vehicle (UAV) swarm systems require communication networking technologies (especially flight ad hoc networking) to form a UAV network, enabling collaborative operation. Among these, formation control is a common collaborative control technology.

[0003] Optimized link state routing (OLSR) is a commonly used proactive routing solution. This solution pre-records and stores routing information related to the network topology in the routing table of each node (usually achieved by the node periodically flooding the entire network with link state information). When sending service data, it can directly query the routing table to find the path from the source node to the destination node, avoiding the latency caused by the route discovery waiting process.

[0004] In the process of developing this invention, the inventors discovered that existing OLSR routing schemes suffer from poor routing performance when applied to UAV networks employing formation control technology. The specific reasons are analyzed as follows:

[0005] Existing OLSR routing schemes utilize mobility information such as node location, speed, and acceleration for routing. For example, link failure time is calculated based on the speed and distance of adjacent nodes, serving as the expected transmission count (ETX), and a routing table is then constructed based on the ETX. In swarm-controlled UAV networks, nodes are in motion. Through swarm control, the relative positions of nodes in the network are coordinated to gradually converge to an expected value. However, before this convergence, the relative positions of nodes may not be consistent with the expected value of swarm control. Thus, under swarm control, the relative positions will change significantly thereafter. For example, two nodes that are close to each other before the relative positions converge to the expected value may become far apart afterward. Therefore, constructing a routing table based solely on the relative distance between adjacent nodes cannot accurately reflect the actual positional relationships between nodes, leading to unreliable routing and reduced routing performance. Therefore, existing OLSR routing schemes are not suitable for UAV networks employing swarm control technology. Summary of the Invention

[0006] In view of this, the main objective of the present invention is to provide a routing method and apparatus for a formation-controlled unmanned aerial vehicle (UAV) network, which can improve the routing performance of the formation-controlled UAV network.

[0007] To achieve the above objectives, the technical solution proposed in this embodiment of the invention is as follows:

[0008] A routing method for a swarm-controlled unmanned aerial vehicle (UAV) network, comprising:

[0009] Each node in the network periodically uses Hello messages for link awareness to identify neighboring nodes with which it has a connected link; the Hello message carries the node's spatial location and expected location offset, and the expected location offset is used to characterize the node's expected spatial location in the formation after the UAV network is formed.

[0010] The node constructs a one-hop neighbor set and a two-hop neighbor set based on the neighboring nodes; determines the link quality parameters between itself and the neighboring nodes based on its own spatial location and expected location offset; and establishes a multi-point relay (MPR) set based on the link quality parameters, the one-hop neighbor set, and the two-hop neighbor set.

[0011] The node broadcasts a TC message for topology control to other nodes in the network and forwards the received TC message based on the MPR set; the TC message carries the link quality parameters between the node and its neighboring nodes.

[0012] Based on the received TC message, the node generates a routing table according to the principle of minimizing the quality weight of the routing path; the quality weight is the sum of the link quality parameters of all links on the path.

[0013] This invention also proposes a routing device for swarm control of unmanned aerial vehicle (UAV) networks, which is installed in each node of the network and includes:

[0014] The link awareness unit is used to periodically use Hello messages to perform link awareness in order to identify neighboring nodes with which it has a connected link; the Hello message carries the spatial location and expected location offset of the node.

[0015] The neighbor detection unit is used to construct a one-hop neighbor set and a two-hop neighbor set based on the known neighbor nodes; determine the link quality parameters between itself and the neighbor nodes based on its own spatial location and expected location offset; and establish a multi-point relay (MPR) set based on the link quality parameters, the one-hop neighbor set, and the two-hop neighbor set.

[0016] The topology control unit is used to send TC messages for topology control to other nodes in the network via network-wide broadcast, and to forward the received TC messages based on the MPR set; the TC messages carry the link quality parameters between the node itself and the neighboring nodes.

[0017] The routing table generation unit is used to generate a routing table based on the received TC message, according to the principle of minimizing the quality weight of the routing path; the quality weight is the sum of the link quality parameters of all links on the path.

[0018] This invention also proposes a routing device for swarm control of unmanned aerial vehicle (UAV) networks, including a processor and a memory;

[0019] The memory stores an application program that can be executed by the processor, which enables the processor to execute the routing method for swarm control of the drone network as described above.

[0020] This invention also proposes a computer-readable storage medium storing computer-readable instructions for executing the routing method for formation-controlled UAV networks as described above.

[0021] This invention also proposes a computer program product, including a computer program / instructions, characterized in that, when the computer program / instructions are executed by a processor, they implement the steps of the routing method for swarm control of UAV networks as described above.

[0022] In summary, the routing scheme for formation-controlled UAV networks proposed in this invention improves upon existing OLSR protocol schemes by leveraging the cooperative movement characteristics of UAV networks under formation control, thereby ensuring the routing performance of formation-controlled UAV networks. In the improved scheme, when performing link awareness, each node needs to carry its own interactive spatial location and desired location offset in the Hello message. This allows each node, upon sensing a neighboring node with a connected link, to determine the link quality parameters between itself and the neighboring node based on its own spatial location and desired location offset. Based on these link quality parameters, an MPR set is established. When broadcasting TC messages for topology control across the network, these TC messages must carry the link quality parameters between the node and its neighboring nodes. Finally, when generating a routing table based on the TC messages, the routing path is selected according to the principle of minimizing the cumulative value of the link quality parameters across all links on the path. The above scheme considers both the actual positional relationship between adjacent nodes and the expected positional relationship (i.e., expected positional offset) under cooperative control when constructing link quality parameters. In this way, the link quality parameters can fully reflect the future movement trend of the nodes. Therefore, the construction of MPR sets and the generation of routing tables based on link quality parameters can avoid the routing unreliability caused by existing OLSR protocol schemes that only consider the actual spatial relationship between nodes and ignore the cooperative movement of network nodes. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention;

[0024] Figure 2 This is an example diagram of the Hello message format according to an embodiment of the present invention;

[0025] Figure 3 This is an example diagram of the TC message format according to an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the device structure according to an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] Figure 1 This is a schematic diagram of the method flow of an embodiment of the present invention, such as... Figure 1 As shown, the routing method for swarm control UAV networks implemented in this embodiment mainly includes the following steps:

[0029] Step 101: Each node in the network periodically uses Hello messages to perform link awareness in order to know the neighboring nodes with which it has a connected link; the Hello message carries the spatial location and expected location offset of the node.

[0030] In this step, unlike the link-aware method in the existing OLSR protocol scheme, two new items related to its own state (i.e., the node's spatial location and expected location offset) need to be added to the Hello message sent by each node (i.e., the UAV) to its neighbors. This is to consider both the actual positional relationship between adjacent nodes and the expected positional relationship under cooperative control when constructing the link quality parameters used to generate the routing table. This allows the link quality parameters to fully reflect the future movement trend of the nodes, so as to take advantage of the cooperative movement characteristics of the UAV network under formation control and ensure the reliability of the route.

[0031] The aforementioned spatial position refers to the current spatial position of the node; the aforementioned expected position offset refers to the expected formation position offset of the node during formation control, which reflects the expected position of the node in the formation after the formation of the UAV network.

[0032] Figure 2 This is an example diagram of the Hello message format according to an embodiment of the present invention. and This is newly introduced information related to the drone itself. Let i be the spatial location of node i. Let be the desired position offset of node i. Since and They are For a 3D vector, each element is recommended to occupy 2 bytes (16 bits). However, if higher precision is required, each element can occupy 4 bytes (32 bits). and It may take up multiple lines; the specific content formatting can be arranged according to the actual system settings. and To ensure the success rate of forward and reverse packet transmissions on links with a specific neighbor, 2 bytes (i.e., 16 bits) are typically used.

[0033] Step 102: Based on the known neighboring nodes, the node constructs a one-hop neighbor set and a two-hop neighbor set; based on its own spatial location and expected location offset with the neighboring nodes, it determines the link quality parameters between itself and the neighboring nodes; based on the link quality parameters, the one-hop neighbor set and the two-hop neighbor set, it establishes a multi-point relay (MPR) set.

[0034] Here, unlike the existing OLSR protocol scheme, this step requires determining the link quality parameters between itself and the neighboring nodes based on the spatial location and expected location offset of itself and the neighboring nodes, and establishing an MPR set based on the constructed link quality parameters with the neighboring nodes to ensure the reliability of the MPR set.

[0035] In one implementation, each node i can specifically determine the link quality parameters between itself and its neighboring nodes j with which it has a connected link using the following method:

[0036] Step x1, according to Calculate the relative position between node i and its neighboring node j, which have a connected link; where, Let i be the spatial position of node i at time t. Let j be the spatial location of node j at time t; Let be the distance between node i and node j at time t.

[0037] Step x2, when At that time, according to , obtain parameters .

[0038] in, ;

[0039] Let be the desired position offset of node i;

[0040] Let be the desired position offset of node j;

[0041] These are preset weighting coefficients, and they are positive constants.

[0042] r is a preset communication radius threshold, which can be set by those skilled in the art according to the reliability communication needs of adjacent nodes in the actual application scenario.

[0043] when At that time, according to , obtain parameters .

[0044] Step x3: Set the parameters , which serves as the link quality parameter between node i and node j.

[0045] Based on the above steps x1 and x2, it can be seen that the parameter... It contains the location and status information of the drone and its neighbors at various times (i.e. and the position status information after the formation is completed. .

[0046] In one implementation, to be compatible with the ETX metric commonly used in the OLSR protocol, each node i can also determine its link quality parameters with its neighboring node j, with which it has a connected link, using the following method:

[0047] Step y1, according to Calculate the relative position between node i and its neighboring node j, which have a connected link; where, Let i be the spatial position of node i at time t. Let j be the spatial location of node j at time t; Let be the distance between node i and node j at time t.

[0048] Step y2, when At that time, according to , obtain parameters .

[0049] in,

[0050] ;

[0051] Let be the desired position offset of node i;

[0052] Let be the desired position offset of node j;

[0053] These are preset weighting coefficients, and they are positive constants.

[0054] r is a preset communication radius threshold, which can be set by those skilled in the art according to the reliability communication needs of adjacent nodes in the actual application scenario.

[0055] when At that time, according to , obtain parameters .

[0056] Step y3, according to Calculate parameters ;in, Let be the success rate of forward data packet transmission between node i and node j, and Let be the success rate of reverse data packet transmission between node i and node j.

[0057] Step y4: Set the parameters , which serves as the link quality parameter between node i and node j.

[0058] In one implementation, the MPR set can be established using the following method:

[0059] Step z1: Based on the one-hop neighbor set and the two-hop neighbor set constructed by node i, select a one-hop neighbor node that can cover the isolated two-hop neighbor node as MPR from the one-hop neighbor set.

[0060] The specific implementation of this step is the same as the MPR set construction method in the existing OLSR protocol, and will not be repeated here.

[0061] Step z2: In the one-hop neighbor set, among the remaining nodes excluding those already selected as MPRs, select one node as an MPR in sequence according to the preset MPR selection strategy, until the selected MPRs can cover all neighbor nodes in the two-hop neighbor set.

[0062] The MPR selection strategy is as follows: if there is a first neighbor node in the two-hop neighbor set, then select a neighbor node from the first neighbor node, and select the path with the smallest quality weight among all paths between node i and the currently selected neighbor node, and take the one-hop neighbor on that path as the MPR; the first neighbor node is a two-hop neighbor node in the two-hop neighbor set that is not covered by all the currently selected MPRs.

[0063] Here, the MPR set construction method differs from that in existing OLSR protocols in its MPR selection strategy. In this strategy, when a two-hop neighbor node is covered by multiple one-hop neighbor nodes, the one-hop neighbor node with the lowest path quality weight is selected as the MPR. The quality weight is the cumulative value of the link quality parameters of all links on the path; in other words, the MPR is selected based on the magnitude of the link quality parameters. This ensures that the MPR selection fully considers the expected position of the nodes after formation. Since this expected position is stable after formation, the reliability of the selected MPR can be guaranteed, avoiding the influence of node movement before formation and preventing the selection of unreliable MPRs based solely on the actual position of the nodes.

[0064] Step z3: Based on all the currently selected MPRs, obtain the MPR set of node i.

[0065] In this step, the MPRs selected in steps z1 and z2 are used as members of the MPR set of node i.

[0066] Step 103: The node sends a TC message for topology control to other nodes in the network via a network-wide broadcast, and forwards the received TC message based on the MPR set; the TC message carries the link quality parameters between the node itself and the neighboring nodes.

[0067] The difference between this step and the existing OLSR protocol is that when a node broadcasts a TC message (i.e., a TopologyControl message) across the network, it needs to include the link quality parameters between itself and its neighboring nodes in the TC message so that each node can generate a reliable routing table based on the received link quality parameters in subsequent steps.

[0068] Figure 3 This is an example diagram of the TC message format according to an embodiment of the present invention. Figure 3 As shown, or For the quality metrics of the link with a specific neighbor (i.e., link quality parameters), it is recommended to use 4 bytes (i.e., 32 bits), but it is not limited to this.

[0069] Step 104: Based on the received TC message, the node generates a routing table according to the principle of minimizing the quality weight of the routing path; the quality weight is the sum of the link quality parameters of all links on the path.

[0070] In this step, unlike the existing OLSR protocol which generates routing tables based on TC messages, it is necessary to select the path with the smallest cumulative value of the link quality parameter to construct the routing table. As mentioned above, this link quality parameter contains both the actual location status information of the UAV and its neighbors and the location status information after the formation is completed, thus ensuring the reliability of the routing table.

[0071] Based on the above method embodiments, this invention also proposes a routing device for a formation-controlled UAV network, which is installed in each node of the network, such as... Figure 4 As shown, it includes:

[0072] The link awareness unit 401 is used to periodically use Hello messages to perform link awareness in order to know the neighboring nodes with which it has a connected link; the Hello message carries the spatial location and expected location offset of the node.

[0073] The neighbor detection unit 402 is used to construct a one-hop neighbor set and a two-hop neighbor set based on the known neighbor nodes; determine the link quality parameters between itself and the neighbor nodes based on its own spatial location and expected location offset; and establish a multi-point relay (MPR) set based on the link quality parameters, the one-hop neighbor set and the two-hop neighbor set.

[0074] The topology control unit 403 is used to send TC messages for topology control to other nodes in the network via network-wide broadcast, and to forward the received TC messages based on the MPR set; the TC messages carry the link quality parameters between the node itself and the neighboring nodes.

[0075] The routing table generation unit 404 is used to generate a routing table based on the received TC message and according to the principle of minimizing the quality weight of the routing path; the quality weight is the sum of the link quality parameters of all links on the path.

[0076] It should be noted that the above methods and apparatus are based on the same inventive concept. Since the methods and apparatus solve problems in similar ways, the implementation of the apparatus and methods can refer to each other, and the repeated parts will not be described again.

[0077] Based on the above method embodiments, this invention also proposes a routing device for a formation-controlled UAV network, including a processor and a memory; the memory stores an application program executable by the processor, which causes the processor to execute the routing method for the formation-controlled UAV network as described above. Specifically, a system or device equipped with a storage medium can be provided, on which software program code implementing the functions of any of the above embodiments is stored, and the computer (or CPU or MPU) of the system or device can read and execute the program code stored in the storage medium. Furthermore, the operating system or other system operating on the computer can perform some or all of the actual operations through instructions based on the program code. The program code read from the storage medium can also be written to a memory located in an expansion board inserted into the computer or to a memory located in an expansion unit connected to the computer, and then the CPU or other system installed on the expansion board or expansion unit can execute some or all of the actual operations based on the instructions of the program code, thereby realizing the functions of any of the above embodiments of the routing method for the formation-controlled UAV network.

[0078] Specifically, the memory can be implemented as various storage media such as electrically erasable programmable read-only memory (EEPROM), flash memory, and programmable programmable read-only memory (PROM). The processor can be implemented as one or more central processing units (CPUs) or one or more field-programmable gate arrays (FPGAs), wherein the FPGA integrates one or more CPU cores. Specifically, the CPU or CPU core can be implemented as a CPU or an MCU.

[0079] This application embodiment implements a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the routing method for swarm control of a drone network as described above.

[0080] It should be noted that not all steps and modules in the above processes and structural diagrams are mandatory; some steps or modules can be omitted as needed. The execution order of the steps is not fixed and can be adjusted as required. The division of modules is merely for the convenience of description and functional division. In actual implementation, a module can be implemented by multiple modules, and the functions of multiple modules can also be implemented by the same module. These modules can be located in the same device or in different devices.

[0081] The hardware modules in each embodiment can be implemented mechanically or electronically. For example, a hardware module may include specially designed permanent circuitry or logic devices (such as dedicated processors, such as FPGAs or ASICs) to perform specific operations. A hardware module may also include programmable logic devices or circuitry (such as general-purpose processors or other programmable processors) temporarily configured by software to perform specific operations. The choice between mechanical implementation, dedicated permanent circuitry, or temporarily configured circuitry (such as software-configured circuitry) for the hardware module can be made based on cost and time considerations.

[0082] In this document, "illustrative" means "serving as an example, illustration, or description," and any illustration or embodiment described herein as "illustrative" should not be construed as a preferred or more advantageous technical solution. For the sake of brevity, the figures only schematically represent the parts relevant to the invention and do not represent their actual structure as a product. Furthermore, for the sake of clarity and ease of understanding, in some figures, components with the same structure or function are only schematically depicted, or only one is labeled. In this document, "a" does not mean that the number of relevant parts of the invention is limited to "only one," and "a" does not exclude the possibility that the number of relevant parts of the invention is "more than one." In this document, terms such as "upper," "lower," "front," "rear," "left," "right," "inner," and "outer" are used only to indicate the relative positional relationship between relevant parts, and not to limit the absolute position of these relevant parts.

[0083] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A routing method for a formation-controlled unmanned aerial vehicle (UAV) network, characterized in that, include: Each node in the network periodically uses Hello messages to perform link awareness in order to identify neighboring nodes with which it has a connected link. The Hello message carries the node's spatial location and expected location offset. The expected location offset is used to characterize the node's expected spatial location in the formation after the UAV network is formed. The node constructs a one-hop neighbor set and a two-hop neighbor set based on the neighboring nodes; Based on its own spatial location and the desired location offset of the neighboring nodes, the link quality parameters between itself and the neighboring nodes are determined; based on the link quality parameters, the one-hop neighbor set and the two-hop neighbor set, a multi-point relay (MPR) set is established. The node sends TC messages for topology control to other nodes in the network via network-wide broadcast, and forwards the received TC messages based on the MPR set; The TC message carries the link quality parameters between the node itself and the neighboring nodes; Based on the received TC message, the node generates a routing table according to the principle of minimizing the quality weight of the routing path; the quality weight is the sum of the link quality parameters of all links on the path.

2. The method according to claim 1, characterized in that, The process of determining the link quality parameters between itself and its neighboring nodes includes: according to Calculate the relative positions between node i and its neighboring node j, which have a connected link. ;in, Let i be the spatial position of node i at time t. Let j be the spatial position of node j at time t; Let be the distance between node i and node j at time t; when At that time, according to , obtain parameters ;in, , Let be the desired position offset of node i. Let be the desired position offset of node j. is the preset weighting coefficient; r is the preset communication radius threshold; when At that time, according to , obtain parameters ; The parameters , which serves as the link quality parameter between node i and node j.

3. The method according to claim 1, characterized in that, The process of determining the link quality parameters between itself and its neighboring nodes includes: according to Calculate the relative positions between node i and its neighboring node j, which have a connected link. ;in, Let i be the spatial position of node i at time t. Let j be the spatial location of node j at time t; Let be the distance between node i and node j at time t; when At that time, according to , obtain parameters ;in, , Let be the desired position offset of node i. Let be the desired position offset of node j. r is the preset coefficient; r is the preset threshold; when At that time, according to , obtain parameters ; according to Calculate parameters ;in, Let be the success rate of forward data packet transmission between node i and node j, and The success rate of reverse data packet transmission between node i and node j; The parameters , which serves as the link quality parameter between node i and node j.

4. The method according to claim 1, characterized in that, The establishment of the multi-point relay MPR set includes: Based on the one-hop neighbor set and the two-hop neighbor set constructed by the node, a one-hop neighbor node that can cover the isolated two-hop neighbor node is selected as MPR from the one-hop neighbor set; In the one-hop neighbor set, among the remaining nodes excluding those already selected as MPRs, a node is sequentially selected as an MPR according to a preset MPR selection strategy until the selected MPRs can cover all neighbor nodes in the two-hop neighbor set. The MPR selection strategy is as follows: if a first neighbor node exists in the two-hop neighbor set, a neighbor node is selected from the first neighbor node; among all paths between the first neighbor node and the currently selected neighbor node, the path with the smallest quality weight is selected, and the one-hop neighbor on that path is selected as the MPR; the first neighbor node is a two-hop neighbor node in the two-hop neighbor set that is not covered by any of the currently selected MPRs. Based on all currently selected MPRs, the set of MPRs for the node is obtained.

5. A routing device for a formation-controlled unmanned aerial vehicle (UAV) network, characterized in that, Configured in each node of the network, including: The link awareness unit is used to periodically use Hello messages to perform link awareness in order to know the neighboring nodes with which it has a connected link; the Hello message carries the spatial location and expected location offset of the node, and the expected location offset is used to characterize the expected spatial location of the node in the formation after the formation of the UAV network. The neighbor detection unit is used to construct a one-hop neighbor set and a two-hop neighbor set based on the neighboring nodes; determine the link quality parameters between itself and the neighboring nodes based on its own spatial location and expected location offset; and establish a multi-point relay (MPR) set based on the link quality parameters, the one-hop neighbor set, and the two-hop neighbor set. The topology control unit is used to send TC messages for topology control to other nodes in the network via network-wide broadcast, and to forward the received TC messages based on the MPR set; the TC messages carry the link quality parameters between the node itself and the neighboring nodes. The routing table generation unit is used to generate a routing table based on the received TC message, according to the principle of minimizing the quality weight of the routing path; the quality weight is the sum of the link quality parameters of all links on the path.

6. A routing device for a swarm control unmanned aerial vehicle (UAV) network, characterized in that, Including processor and memory; The memory stores an application program that can be executed by the processor, which causes the processor to perform the routing method for a formation-controlled unmanned aerial vehicle network as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, It contains computer-readable instructions for performing the routing method for a formation-controlled unmanned aerial vehicle network as described in any one of claims 1 to 4.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the routing method for a formation-controlled unmanned aerial vehicle network as described in any one of claims 1 to 4.

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