A ship search and rescue path planning method, device, equipment and storage medium

Abstract

The present invention discloses a ship search and rescue path planning method, device, equipment and storage medium. It includes: constructing a multi-ship search and rescue mathematical model, wherein a ship set, a waypoint set and a waypoint set not passed by are defined in the multi-ship search and rescue mathematical model; constructing a state parameterized model diagram covering the search and rescue area based on the multi-ship search and rescue mathematical model, and constructing a search model diagram according to the state parameterized model diagram; and performing search and rescue path planning according to the state parameterized model diagram and the search model diagram. By constructing a mathematical model and two model diagrams, the complex search and rescue path planning process is simplified, the planning efficiency is significantly improved, and the planning time is shortened. Comprehensively considering multiple factors such as ship sets and waypoint sets, the planned search and rescue path is more reasonable, the coverage integrity and accuracy of the search area are improved, the search and rescue tasks and paths of multiple ships can be reasonably allocated, the optimal configuration of search and rescue resources is achieved, and the resource utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of ship search and rescue, and in particular to a ship search and rescue path planning method, device, equipment and storage medium. Background Art

[0002] In the field of marine search and rescue, the effectiveness and efficiency of multi-vessel joint search and rescue has always been the focus of attention. How to achieve efficient and rapid coverage search in the vast ocean area and ensure timely discovery of the target has long been a difficult problem that has troubled the search and rescue team.

[0003] In recent years, although artificial intelligence-based search path planning algorithms have gradually been applied to search pre-planning, when faced with complex situations involving multiple ships, especially methods based on global planning, their complexity grows exponentially with the increase in the number of search and rescue ships. This not only increases the difficulty and time cost of calculation, but also brings severe challenges to the rationality and efficiency of search and rescue path planning. Summary of the invention

[0004] The present invention provides a ship search and rescue path planning method, device, equipment and storage medium, which can efficiently and quickly cover the search area and perform efficient search.

[0005] According to one aspect of the present invention, a method for ship search and rescue path planning is provided, the method comprising:

[0006] Constructing a multi-ship search and rescue mathematical model, wherein a ship set, a waypoint set and a waypoint set not passed by are defined in the multi-ship search and rescue mathematical model;

[0007] A state parameterized model diagram covering the search and rescue area is constructed based on a multi-ship search and rescue mathematical model, and a search model diagram is constructed based on the state parameterized model diagram;

[0008] Search and rescue path planning is performed based on the state parameterized model graph and the search model graph.

[0009] Optionally, a multi-ship search and rescue mathematical model is constructed, including: defining key sets and key variables, wherein the key sets include a ship set, a waypoint set and a waypoint set not passed, and the key variables include the waypoint position coordinates; introducing time-related parameters, and determining waypoints of interest and indicator functions, wherein the time-related parameters include the time requirements of the search and rescue mission and the position of the ship at a specified time; expressing the key sets, key variables, time-related parameters, waypoints of interest and indicator functions and their relationships using mathematical formulas to construct a multi-ship search and rescue mathematical model.

[0010] Optionally, a state parameterized model graph covering the search and rescue area is constructed based on the multi-ship search and rescue mathematical model, including: combining the multi-ship search and rescue mathematical model and the search and rescue area to generate a search and rescue model; determining basic components of the graph based on the search and rescue model, wherein the basic components include nodes and edges; determining feature representations of the nodes and edges, and determining the state representation of the ship based on the feature representations of the nodes and edges, wherein the state representation of the ship includes an edge feature set and a node feature set; and generating a state parameterized model graph based on the state representation of the ship.

[0011] Optionally, basic components of a graph are determined based on the search and rescue model, including: determining each instance included in the search and rescue model, and taking each instance as a node, wherein the instance includes a ship and a waypoint; taking the edge between the waypoints as a first edge, and taking the edge between the ship and the waypoint as a second edge, wherein the first edge represents free space and the second edge represents the ability of the ship to move; and taking each node and each edge as a basic component of the graph.

[0012] Optionally, a search model graph is constructed according to the state parameterized model graph, including: determining an initial node according to the state parameterized model graph; determining each critical node in each initial node; and updating a feature vector of each initial node and each critical node using an indicator function to construct the search model graph.

[0013] Optionally, determining the initial node according to the state parameterized model graph includes: obtaining sensor observation results and determining each waypoint in the state parameterized model graph; matching each waypoint through the sensor observation results, and using the waypoint that matches the sensor observation results as the initial node.

[0014] Optionally, search and rescue path planning is performed based on the state parameterized model graph and the search model graph, including: performing signal conversion on the state parameterized model graph and the search model graph through a graph signal conversion function to generate a characteristic graph signal; aggregating the characteristic graph signal to generate an aggregation matrix, wherein the aggregation matrix includes each target waypoint; and generating a search and rescue path based on each target waypoint.

[0015] According to another aspect of the present invention, a ship search and rescue path planning device is provided, the device comprising:

[0016] A mathematical model building module is used to build a multi-ship search and rescue mathematical model, wherein a ship set, a waypoint set and a waypoint set not passed by are defined in the multi-ship search and rescue mathematical model;

[0017] A model graph construction module is used to construct a state parameterized model graph covering the search and rescue area based on a multi-ship search and rescue mathematical model, and to construct a search model graph based on the state parameterized model graph;

[0018] The search and rescue path planning module is used to perform search and rescue path planning based on the state parameterized model graph and the search model graph.

[0019] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0020] at least one processor;

[0021] and a memory communicatively coupled to the at least one processor;

[0022] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a ship search and rescue path planning method described in any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a ship search and rescue path planning method described in any embodiment of the present invention when executed.

[0024] The technical solution of the embodiment of the present invention simplifies the complex search and rescue path planning process by constructing a mathematical model and two model diagrams, significantly improves the planning efficiency, and shortens the planning time. Comprehensively considering multiple factors such as ship collection and waypoint collection, the planned search and rescue path is more reasonable, the coverage integrity and accuracy of the search area are improved, the search and rescue tasks and paths of multiple ships can be reasonably allocated, the optimal configuration of search and rescue resources is achieved, and the efficiency of resource utilization is improved.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 is a flow chart of a ship search and rescue path planning method provided according to Embodiment 1 of the present invention;

[0028] Figure 2 This is a node schematic diagram provided according to Embodiment 1 of the present invention;

[0029] Figure 3 is a schematic diagram of node motion capability provided according to Embodiment 1 of the present invention;

[0030] Figure 4 is a flow chart of another ship search and rescue path planning method provided according to Embodiment 2 of the present invention;

[0031] Figure 5 is a schematic diagram of the structure of a ship search and rescue path planning device provided according to Embodiment 3 of the present invention;

[0032] Figure 6 It is a structural schematic diagram of an electronic device for implementing a ship search and rescue path planning method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Embodiment 1

[0036] Figure 1 A flow chart of a ship search and rescue path planning method is provided for the first embodiment of the present invention. This embodiment is applicable to sea search and rescue. The method can be executed by a ship search and rescue path planning device. The ship search and rescue path planning device can be implemented in the form of hardware and / or software. The ship search and rescue path planning device can be configured in a computer controller. Figure 1 As shown, the method includes:

[0037] S110, constructing a multi-ship search and rescue mathematical model, wherein the multi-ship search and rescue mathematical model defines a ship set, a waypoint set, and a waypoint set that has not been passed.

[0038] The ship set refers to the set of all ships participating in maritime search and rescue. A waypoint set is a set of points with specific geographical locations within the search and rescue area. The initial state of the unpassed waypoint set is the same as the waypoint set. As the search and rescue process progresses, when the ship passes a waypoint, this waypoint is removed from the set. The unpassed waypoint set can reflect in real time which waypoints have not been searched, assist in planning subsequent search and rescue routes, and avoid missing important areas. The multi-ship search and rescue mathematical model is a model constructed using mathematical formulas and logic by defining key elements such as ship sets, waypoint sets, and unpassed waypoint sets, as well as the relationships and constraints between the elements. It is used to abstract and describe the search and rescue scenario involving multiple ships, and provide a theoretical basis and framework for subsequent path planning.

[0039] Optionally, a multi-ship search and rescue mathematical model is constructed, including: defining key sets and key variables, wherein the key sets include a ship set, a waypoint set and a waypoint set not passed, and the key variables include the waypoint position coordinates; introducing time-related parameters, and determining waypoints of interest and indicator functions, wherein the time-related parameters include the time requirements of the search and rescue mission and the position of the ship at a specified time; expressing the key sets, key variables, time-related parameters, waypoints of interest and indicator functions and their relationships using mathematical formulas to construct a multi-ship search and rescue mathematical model.

[0040] Among them, when defining key sets and key variables, first determine the ship set and waypoint collection , as the basic structure of the entire model. ,use Represents its position coordinates, Indicates waypoint The definition of the set and variables provides the basis for the subsequent description of the relationship between the ship and the waypoints, for example, when considering the choice of the ship's movement path, It can help determine the range of adjacent waypoints that a ship can go to at a certain waypoint. Secondly, set the time requirements for the search and rescue mission , and ships At the moment Location , time requirements It constrains the entire search and rescue operation, ensuring that the planned path can complete the search mission within the specified time. It changes dynamically over time and is the key variable for subsequent calculation of the ship's movement path and judgment of the relative position of the ship and the waypoint. In addition, Indicated in Time, waypoint Is it a waypoint of interest? At the same time, an indication function is introduced Indicates ship Is it at a waypoint? The determination of the waypoints of interest may be based on historical accident data in the area, environmental factors, etc., which affect the focus of the ship's search.

[0041] Specifically, the multi-ship search and rescue mathematical model is shown in the following formula (1):

[0042] (1)

[0043] in, represents a collection of ships, Represents a set of waypoints, Indicates a waypoint that has not been passed, where . Is a waypoint The location coordinates of Indicates waypoint A collection of surrounding waypoints. Indicated in Time, waypoint Is this a waypoint of interest? Indicates the time requirement for this search and rescue mission. exist The position at time is , and the indicator function Indicates ship Is it at a waypoint? superior, Indicates waypoint The location coordinates of Ships At the moment location.

[0044] In summary, constructing a multi-ship search and rescue mathematical model can provide a basic quantitative description for the entire search and rescue path planning, and can clearly define key elements such as ships and waypoints and their attributes in time and space. It is the data and logical basis for subsequent steps, so that the entire search and rescue path planning process can be analyzed and calculated based on accurate mathematical expressions.

[0045] S120, constructing a state parameterized model diagram covering the search and rescue area based on the multi-ship search and rescue mathematical model, and constructing a search model diagram according to the state parameterized model diagram.

[0046] Among them, the state parameterized model graph refers to a graph structure constructed based on the mathematical model of multi-ship search and rescue. The nodes in the state parameterized model graph represent the different states of the ship during the search and rescue process. The states are characterized by multiple parameters, such as the ship's position and time; the edges represent the transfer relationship between states, which is generated based on factors such as the movement of the ship and the advancement of time. The state parameterized model graph can intuitively display the changes in the state during the search and rescue process, and assist in analyzing and planning the path.

[0047] Optionally, a state parameterized model graph covering the search and rescue area is constructed based on the multi-ship search and rescue mathematical model, including: combining the multi-ship search and rescue mathematical model and the search and rescue area to generate a search and rescue model; determining basic components of the graph based on the search and rescue model, wherein the basic components include nodes and edges; determining feature representations of the nodes and edges, and determining the state representation of the ship based on the feature representations of the nodes and edges, wherein the state representation of the ship includes an edge feature set and a node feature set; and generating a state parameterized model graph based on the state representation of the ship.

[0048] Among them, combining the multi-ship search and rescue mathematical model with the search and rescue area means determining whether the waypoint is within the area and the feasible movement range of the ship based on the geographical boundaries of the search and rescue area. If the search and rescue area is a specific sea area whose boundaries are defined by a range of longitude and latitude, then the coordinates of all waypoints must be within the range of longitude and latitude, and the movement path of the ship cannot exceed this sea area.

[0049] Optionally, basic components of a graph are determined based on the search and rescue model, including: determining each instance included in the search and rescue model, and taking each instance as a node, wherein the instance includes a ship and a waypoint; taking the edge between the waypoints as a first edge, and taking the edge between the ship and the waypoint as a second edge, wherein the first edge represents free space and the second edge represents the ability of the ship to move; and taking each node and each edge as a basic component of the graph.

[0050] Specifically, each instance in the search and rescue model, including ships and waypoints, is part of a single computational graph. Each ship is considered a node in the graph structure, and the topology of the graph is constantly changing as the ship moves, because the change in the position of the ship will cause the connection relationship between it and other ships and waypoints to be dynamically adjusted. For example, when a ship moves from one waypoint to another, its connection relationship with the two waypoints and its relative position relationship with the surrounding ships will change, thereby changing the overall structure of the graph. Figure 2A node diagram is provided for the present invention, wherein nodes 1-4 are waypoints, node 5 is a ship, and waypoint 2 is a point that is not passed through.

[0051] It should be noted that the constructed parameterized model diagram covering the state of the search and rescue area has two types of edges: one is the edge between waypoints, which represents free space. In the actual search and rescue area, there is a passable space between waypoints, and ships can move between waypoints along these connections. This edge reflects the spatial connectivity between waypoints. The other is the edge between ships and waypoints, which represents the ability of ships to move. It clarifies the range of waypoints that ships can reach. A ship may be connected to multiple waypoints through the second edge, indicating that the ship has the ability to move to these waypoints, thereby providing a basic connection relationship for the ship's path selection. When planning the search path of the ship, the feasible movement direction can be determined based on the edge. Figure 3 A schematic diagram of node movement capability is provided for the present invention, where nodes 1-4 are waypoints, node 5 is a ship, waypoint 2 is a point that is not passed through, and arrows indicate the direction of movement, i.e., the ship at node 5 can move to waypoints 1, 3, and 4.

[0052] In a specific implementation, each node in the constructed coverage search and rescue area state parameterized model graph The eigenvector of As shown in formula (2), the feature vector represents the type of node:

[0053] (2)

[0054] in, , and is the indicator function. Each edge Each contains a sending node and a receiving node , then the distance of the edge is expressed as shown in formula (3):

[0055] (3)

[0056] in, represents the distance to the edge, Indicates the sending node location, Indicates accepting node positions.

[0057] Furthermore, the state parameterized model diagram is represented as ,exist At this moment, the status of all ships is expressed as ,in, , is the set of all edge features; , is the set of all node features.

[0058] Optionally, a search model graph is constructed according to the state parameterized model graph, including: determining an initial node according to the state parameterized model graph; determining each critical node in each initial node; and updating a feature vector of each initial node and each critical node using an indicator function to construct the search model graph.

[0059] Optionally, determining the initial node according to the state parameterized model graph includes: obtaining sensor observation results and determining each waypoint in the state parameterized model graph; matching each waypoint through the sensor observation results, and using the waypoint that matches the sensor observation results as the initial node.

[0060] Specifically, when a waypoint is observed by a sensor within a certain range, the waypoint is added to the search model graph. In actual search and rescue scenarios, sensors are distributed on ships or in specific areas, which can detect the surrounding waypoint information. Once a waypoint is within the effective detection range of the sensor, that is, when , , where S represents the sensor observation range, Indicates the distance to the edge of the waypoint, express The set of all waypoints at the moment, express The set of all waypoints at the moment, Indicates The location of waypoints, a critical waypoint is defined as an observed waypoint with no unobserved adjacent waypoints. The set of critical waypoints is defined as , and use the indicator function to update the feature vector of the node .

[0061] S130: Perform search and rescue path planning according to the state parameterized model graph and the search model graph.

[0062] It should be noted that the search model graph is essentially an abstract representation of the possible state transition paths of the entire search and rescue process. By constructing the search model graph, the ship search and rescue path planning problem can be transformed into the problem of finding the optimal path in the graph. The optimal path may be the path with the minimum total cost, that is, it can complete the search of all important waypoints in the shortest time or with the least resource consumption, thereby achieving effective coverage of the search and rescue area.

[0063] Specifically, after the state parameterized model graph and the search model graph are constructed, search and rescue path planning can be performed, for example, by combining an aggregate neural network. In practical applications, the initial path found may need to be optimized and adjusted according to the real-time situation. For example, if new information is obtained during the search and rescue process, such as finding that a target is more likely to exist in a certain area, or that a certain ship has a malfunction, it is necessary to re-evaluate the state parameterized model graph and the search model graph, and adjust the planned path to ensure that the search and rescue operation is always carried out in the most effective direction.

[0064] The technical solution of the embodiment of the present invention simplifies the complex search and rescue path planning process by constructing a mathematical model and two model diagrams, significantly improves the planning efficiency, and shortens the planning time. Comprehensively considering multiple factors such as ship collection and waypoint collection, the planned search and rescue path is more reasonable, the coverage integrity and accuracy of the search area are improved, the search and rescue tasks and paths of multiple ships can be reasonably allocated, the optimal configuration of search and rescue resources is achieved, and the efficiency of resource utilization is improved.

[0065] Embodiment 2

[0066] Figure 4 This is a flow chart of a ship search and rescue path planning method provided in the second embodiment of the present invention. This embodiment adds a specific process of searching and rescuing the path according to the state parameterized model diagram and the search model diagram on the basis of the above-mentioned first embodiment. Among them, the specific contents of steps S210-S220 are roughly the same as steps S110-S120 in the first embodiment, so they will not be repeated in this embodiment. Figure 4 As shown, the method includes:

[0067] S210: construct a multi-ship search and rescue mathematical model, wherein the multi-ship search and rescue mathematical model defines a ship set, a waypoint set, and a waypoint set that has not been passed.

[0068] Optionally, a multi-ship search and rescue mathematical model is constructed, including: defining key sets and key variables, wherein the key sets include a ship set, a waypoint set and a waypoint set not passed, and the key variables include the waypoint position coordinates; introducing time-related parameters, and determining waypoints of interest and indicator functions, wherein the time-related parameters include the time requirements of the search and rescue mission and the position of the ship at a specified time; expressing the key sets, key variables, time-related parameters, waypoints of interest and indicator functions and their relationships using mathematical formulas to construct a multi-ship search and rescue mathematical model.

[0069] S220, constructing a state parameterized model diagram covering the search and rescue area based on the multi-ship search and rescue mathematical model, and constructing a search model diagram according to the state parameterized model diagram.

[0070] Optionally, a state parameterized model graph covering the search and rescue area is constructed based on the multi-ship search and rescue mathematical model, including: combining the multi-ship search and rescue mathematical model and the search and rescue area to generate a search and rescue model; determining basic components of the graph based on the search and rescue model, wherein the basic components include nodes and edges; determining feature representations of the nodes and edges, and determining the state representation of the ship based on the feature representations of the nodes and edges, wherein the state representation of the ship includes an edge feature set and a node feature set; and generating a state parameterized model graph based on the state representation of the ship.

[0071] Optionally, basic components of a graph are determined based on the search and rescue model, including: determining each instance included in the search and rescue model, and taking each instance as a node, wherein the instance includes a ship and a waypoint; taking the edge between the waypoints as a first edge, and taking the edge between the ship and the waypoint as a second edge, wherein the first edge represents free space and the second edge represents the ability of the ship to move; and taking each node and each edge as a basic component of the graph.

[0072] Optionally, a search model graph is constructed according to the state parameterized model graph, including: determining an initial node according to the state parameterized model graph; determining each critical node in each initial node; and updating a feature vector of each initial node and each critical node using an indicator function to construct the search model graph.

[0073] Optionally, determining the initial node according to the state parameterized model graph includes: obtaining sensor observation results and determining each waypoint in the state parameterized model graph; matching each waypoint through the sensor observation results, and using the waypoint that matches the sensor observation results as the initial node.

[0074] S230. Perform signal conversion on the state parameterized model graph and the search model graph through a graph signal conversion function to generate a characteristic graph signal.

[0075] The image signal conversion process is expressed by the following formula (4):

[0076] (4)

[0077] in, represents the characteristic graph signal, The graph representing the input, including the state parameterized model graph and the search model graph, Represents the graph signal conversion function, which is , , To express.

[0078] S240, performing an aggregation operation on the characteristic graph signal to generate an aggregation matrix, wherein the aggregation matrix includes each target waypoint.

[0079] It can be seen that the feature graph signal not only has the same connectivity as the original graph signal, but also has new feature information at the edges and nodes. ,in, , , , , , Represents the feature map signal after edge feature conversion, Represents the feature graph signal after node feature conversion, and Respectively represent the learnable nonlinear transformation functions of edge features and node features, Represents the receiving node characteristics, Indicates the characteristics of the sending node, represents the aggregation matrix, represents the distance to the edge, Represents each node The characteristic vector of and are all three-layer perceptrons with 16 hidden units. Representation Node The chaotic edge features after transformation. Represents an aggregation operation, which can represent nodes The chaotic edge features after transformation Arranged into a fixed-size latent vector, also known as the aggregation matrix , the polymerization process is expressed by the following formula (5):

[0080] (5)

[0081] in, Represents the feature map signal after edge feature conversion, Representation Node The chaotic edge features after transformation, Represents an aggregation operation.

[0082] S250: Generate a search and rescue path according to each target waypoint.

[0083] The technical solution of the embodiment of the present invention can accurately extract key features in the state parameterized model graph and the search model graph by performing signal conversion through the graph signal conversion function, and provide an accurate data basis for the subsequent generation of effective search and rescue paths. By performing aggregation operations on the characteristic graph signals to generate an aggregation matrix, efficient integration of a large amount of complex information is achieved, data redundancy and confusion are reduced, and the efficiency of path planning is improved. Generating a search and rescue path based on accurate target waypoints can avoid invalid or dangerous areas, improve the rationality of path planning, and shorten the search and rescue time.

[0084] Embodiment 3

[0085] Figure 5 This is a schematic diagram of the structure of a ship search and rescue path planning device provided by Embodiment 3 of the present invention. Figure 5 As shown, the device includes: a mathematical model construction module 310, which is used to construct a multi-ship search and rescue mathematical model, wherein a ship set, a waypoint set and a waypoint set not passed by are defined in the multi-ship search and rescue mathematical model;

[0086] A model graph construction module 320 is used to construct a state parameterized model graph covering the search and rescue area based on the multi-ship search and rescue mathematical model, and to construct a search model graph according to the state parameterized model graph;

[0087] The search and rescue path planning module 330 is used to perform search and rescue path planning according to the state parameterized model graph and the search model graph.

[0088] Optionally, the mathematical model building module 310 is specifically used to: define key sets and key variables, wherein the key sets include a ship set, a waypoint set and a waypoint set not passed, and the key variables include the waypoint position coordinates; introduce time-related parameters, and determine the waypoints of interest and indicator functions, wherein the time-related parameters include the time requirements of the search and rescue mission and the position of the ship at a specified time; express the key sets, key variables, time-related parameters, waypoints of interest and indicator functions and their relationships using mathematical formulas to construct a multi-ship search and rescue mathematical model.

[0089] Optionally, the model graph construction module 320 specifically includes: a state parameterized model graph generation unit, used to: combine the multi-ship search and rescue mathematical model and the search and rescue area to generate a search and rescue model; determine the basic components of the graph based on the search and rescue model, wherein the basic components include nodes and edges; determine the feature representations of the nodes and edges, and determine the state representation of the ship based on the feature representations of the nodes and edges, wherein the state representation of the ship includes an edge feature set and a node feature set; generate a state parameterized model graph based on the state representation of the ship.

[0090] Optionally, the model graph construction module 320 specifically includes: a basic component element determination unit, used to: determine each instance included in the search and rescue model, and use each instance as a node, wherein the instance includes a ship and a waypoint; use the edge between the waypoints as the first edge, and use the edge between the ship and the waypoint as the second edge, wherein the first edge represents free space and the second edge represents the ability of the ship to move; use each node and each edge as the basic component element of the graph.

[0091] Optionally, the model graph construction module 320 specifically includes: a search model graph construction unit, used to: determine the initial node according to the state parameterized model graph; determine each critical node in each initial node; use an indicator function to update the feature vector of each initial node and each critical node to construct a search model graph.

[0092] Optionally, the model graph construction module 320 specifically includes: an initial node determination unit, used to: obtain sensor observation results and determine each waypoint in the state parameterized model graph; match each waypoint through the sensor observation results, and use the waypoint that matches the sensor observation results as the initial node.

[0093] Optionally, the search and rescue path planning module 330 is specifically used to: perform signal conversion on the state parameterized model graph and the search model graph through a graph signal conversion function to generate a characteristic graph signal; aggregate the characteristic graph signal to generate an aggregate matrix, wherein the aggregate matrix includes each target waypoint; and generate a search and rescue path according to each target waypoint.

[0094] The technical solution of the embodiment of the present invention simplifies the complex search and rescue path planning process by constructing a mathematical model and two model diagrams, significantly improves the planning efficiency, and shortens the planning time. Comprehensively considering multiple factors such as ship collection and waypoint collection, the planned search and rescue path is more reasonable, the coverage integrity and accuracy of the search area are improved, the search and rescue tasks and paths of multiple ships can be reasonably allocated, the optimal configuration of search and rescue resources is achieved, and the efficiency of resource utilization is improved.

[0095] A ship search and rescue path planning device provided in an embodiment of the present invention can execute a ship search and rescue path planning method provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0096] Embodiment 4

[0097] Figure 6 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device 10 can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0098] like Figure 6As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0099] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0100] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a ship search and rescue path planning method.

[0101] In some embodiments, a ship search and rescue path planning method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the ship search and rescue path planning method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute a ship search and rescue path planning method in any other appropriate manner (e.g., by means of firmware).

[0102] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0103] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0104] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0105] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0106] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0107] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0108] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0109] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A ship search and rescue path planning method, characterized in that: include: Constructing a multi-ship search and rescue mathematical model, wherein the multi-ship search and rescue mathematical model defines a ship set, a waypoint set, and a waypoint set that has not been passed; Constructing a state parameterized model diagram covering the search and rescue area based on the multi-ship search and rescue mathematical model, and constructing a search model diagram according to the state parameterized model diagram; Perform search and rescue path planning according to the state parameterized model graph and the search model graph; Wherein, the construction of a multi-ship search and rescue mathematical model includes: Define key sets and key variables, wherein the key sets include a ship set, a waypoint set, and a waypoint set that has not been passed, and the key variables include waypoint position coordinates; Introducing time-related parameters and determining interesting waypoints and indicator functions, wherein the time-related parameters include the time requirement of the search and rescue mission and the position of the vessel at a specified time; The key set, the key variables, the time-related parameters, the interesting waypoints and the indicator functions and their relationships are expressed by mathematical formulas to construct the multi-vessel search and rescue mathematical model; Wherein, the state parameterized model diagram covering the search and rescue area is constructed based on the multi-ship search and rescue mathematical model, including: combining the multi-vessel search and rescue mathematical model with the search and rescue area to generate a search and rescue model; Determining basic components of a graph based on the search and rescue model, wherein the basic components include nodes and edges; Determine feature representations of nodes and edges, and determine a state representation of a ship according to the feature representations of nodes and edges, wherein the state representation of the ship includes an edge feature set and a node feature set; A state parameterized model diagram is generated according to the state representation of the ship.

2. The method according to claim 1, characterized in that The basic components of the graph determined based on the search and rescue model include: Determine each instance included in the search and rescue model, and use each instance as a node, wherein the instance includes a ship and a waypoint; Taking the edge between the waypoints as the first edge and the edge between the ship and the waypoint as the second edge, wherein the first edge represents free space and the second edge represents the ability of the ship to move; Each node and each edge is regarded as the basic component of the graph.

3. The method according to claim 2, characterized in that The step of constructing a search model graph according to the state parameterized model graph includes: Determine an initial node according to the state parameterized model diagram; Determining each critical node in each of the initial nodes; The characteristic vectors of each of the initial nodes and each of the critical nodes are updated using an indicator function to construct a search model graph.

4. The method according to claim 3, characterized in that: The determining of the initial node according to the state parameterized model graph comprises: Obtaining sensor observation results and determining each waypoint in the state parameterized model graph; Each of the waypoints is matched with the sensor observation result, and the waypoint that matches the sensor observation result is used as the initial node.

5. The method according to claim 1, characterized in that The performing search and rescue path planning according to the state parameterized model graph and the search model graph comprises: Performing signal conversion on the state parameterized model graph and the search model graph through a graph signal conversion function to generate a characteristic graph signal; Aggregating the characteristic graph signals to generate an aggregation matrix, wherein the aggregation matrix includes each target waypoint; A search and rescue path is generated according to each of the target waypoints.

6. A ship search and rescue path planning device, characterized in that: include: A mathematical model building module, used to build a multi-ship search and rescue mathematical model, wherein the multi-ship search and rescue mathematical model defines a ship set, a waypoint set and a waypoint set that has not been passed; A model graph construction module, used to construct a state parameterized model graph covering the search and rescue area based on the multi-ship search and rescue mathematical model, and to construct a search model graph according to the state parameterized model graph; A search and rescue path planning module, used for performing search and rescue path planning according to the state parameterized model graph and the search model graph; Wherein, the mathematical model building module is specifically used for: Define key sets and key variables, wherein the key sets include a ship set, a waypoint set, and a waypoint set that has not been passed, and the key variables include waypoint position coordinates; Introducing time-related parameters and determining interesting waypoints and indicator functions, wherein the time-related parameters include the time requirement of the search and rescue mission and the position of the vessel at a specified time; The key set, the key variables, the time-related parameters, the interesting waypoints and the indicator functions and their relationships are expressed by mathematical formulas to construct the multi-vessel search and rescue mathematical model; Wherein, the model graph construction module is specifically used for: combining the multi-vessel search and rescue mathematical model with the search and rescue area to generate a search and rescue model; Determining basic components of a graph based on the search and rescue model, wherein the basic components include nodes and edges; Determine feature representations of nodes and edges, and determine a state representation of a ship according to the feature representations of nodes and edges, wherein the state representation of the ship includes an edge feature set and a node feature set; A state parameterized model diagram is generated according to the state representation of the ship.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method according to any one of claims 1 to 5 when executed.

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