A dual-observation cooperative control method, system, computer device and storage medium for a multi-agent surveying system

Abstract

The present application relates to a kind of dual observation collaborative control method, system, computer device and storage medium for multi-agent survey system.The present application includes: constructing the state space model of complex seabed topography switching multi-agent survey system;Simulate exogenous disturbance signal, monitor and collect exogenous disturbance information;Control multi-agent to carry out survey work, and collect the state information of each multi-agent by state observer;Optimize the task allocation and path planning of leader and non-leader;Verify the positivity and consistency of complex seabed topography switching multi-agent survey system.Improve the response speed and flexibility of survey task, better adapt to complex and changeable seabed environment, effectively reduce the energy consumption in survey process, reduce operating cost, improve economic benefit;By verifying the positivity and consistency of complex seabed topography switching multi-agent survey system, ensure the stability and consistency of system, enhance the reliability of entire survey process.

Description

Technical Field

[0001] This invention relates to the field of seabed topographic surveying technology, and in particular to a dual-observation collaborative control method, system, computer equipment, and storage medium for a multi-agent surveying system. Background Technology

[0002] In the vast field of marine scientific exploration and resource development, seabed topographic surveying, as a fundamental and crucial link, is of great significance for understanding ocean dynamics, assessing the marine ecological environment, guiding marine engineering construction, and developing oil and gas resources. However, the complex and varied seabed topography, especially the extreme environments with many mountains, canyons, undercurrents, and eddies, poses a significant challenge to traditional surveying methods. These complex topography conditions not only require surveying equipment to possess high precision and stability but also to flexibly adapt to changing environmental conditions, ensuring the continuity and accuracy of data acquisition.

[0003] Traditional seabed topographic survey methods, such as single-ship towed sonar and submersible exploration, while meeting survey requirements to some extent, often suffer from low efficiency, limited data accuracy, and high operational risks when dealing with complex seabed topography. In recent years, the rapid development of multi-agent system (MAS) technology has provided a new solution for seabed topographic surveying through its collaborative capabilities in complex environments. A MAS consists of multiple agents with autonomous decision-making and communication capabilities, which cooperate to complete complex tasks. In seabed topographic surveying, MAS systems can be deployed in a distributed manner, each carrying or mounting survey equipment such as sonar and lidar, achieving comprehensive, efficient, and accurate surveying of the seabed topography through collaborative work. Compared to traditional methods, MAS systems offer greater flexibility and robustness, better adapting to complex and changing seabed environments.

[0004] However, applying multi-agent systems to the survey of complex seabed terrain still faces many technical challenges. First, the complexity and variability of the seabed environment require the system to perceive and respond accurately to environmental changes in real time to ensure the accuracy and consistency of survey data. Second, collaborative operations among multiple agents require efficient communication mechanisms and collaborative control strategies to optimize information sharing and task allocation. In addition, the system must also have the ability to quickly switch between various terrains to meet the survey needs of different terrains. Summary of the Invention

[0005] Based on this, in order to solve the above-mentioned technical problems, a dual-observation collaborative control method, system, computer equipment and storage medium for multi-agent survey systems are provided, which can realize accurate perception of the seabed environment and efficient collaborative operation among agents.

[0006] A dual-observation cooperative control method for a multi-agent survey system, the method comprising:

[0007] Construct a state-space model for a multi-agent survey system that switches between complex seabed topography;

[0008] External disturbance signals are simulated in the state space model, and external disturbance information is collected by a disturbance observer and sent to the cooperative controller.

[0009] The collaborative controller controls the leader among the multi-agents to perform surveying work based on the leader control protocol, controls the non-leaders among the multi-agents to perform surveying work based on the control protocol, and collects the state information of each multi-agent through the state observer;

[0010] The collaborative controller optimizes the task allocation and path planning for the leader and non-leaders based on the status information.

[0011] The state observer collects the optimized state information of each multi-agent, and verifies the positivity and consistency of the multi-agent survey system for complex seabed topography based on the optimized state information.

[0012] In one embodiment, a state-space model of a multi-agent survey system for complex seabed topography switching is constructed, including:

[0013] Collect the state vectors of each agent and determine the control input vector and output vector of each agent;

[0014] Acquire switching signals between various agents to determine the system matrix of a multi-agent survey system for complex seabed topography switching;

[0015] A state-space model is constructed based on the state vector, control input vector, output vector, switching signal, and system matrix.

[0016] In one embodiment, the collaborative controller optimizes the task allocation and path planning for the leader and non-leaders based on the state information, including:

[0017] The cooperative controller determines a cooperative control strategy based on the state information, and performs path planning for each agent using a linear programming method based on the cooperative control strategy.

[0018] The collaborative controller allocates and adjusts the tasks of the leader and non-leaders based on the collaborative control strategy, and plans the survey paths of the leader and non-leaders based on the linear programming method.

[0019] In one embodiment, the state space model includes a first state space model of the leader conducting surveying work and a second state space model of the non-leader conducting surveying work.

[0020] The complex seabed topography switching multi-agent survey system includes a leader system where the leader conducts the survey, and a non-leader system where the non-leader conducts the survey.

[0021] In one embodiment, verifying the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the optimized state information includes:

[0022] Based on the optimized state information, the leader system and the non-leader system are verified using matrix decomposition and copositive Lyapunov function, respectively, and the verification results are obtained.

[0023] The positivity and consistency of the complex seabed topography switching multi-agent survey system are determined based on the verification results.

[0024] In one embodiment, the method further includes:

[0025] Set the operating conditions for the smooth operation of the leader system and the non-leader system respectively;

[0026] Verify the positivity and consistency of the leader system and the non-leader system based on the aforementioned operating conditions.

[0027] In one embodiment, the method further includes:

[0028] Design a leader control protocol based on the leader in a multi-agent system, and design a control protocol based on the non-leader in a multi-agent system.

[0029] The leader control protocol is used to control the leader to perform surveying work; the control protocol is used to control the non-leader to perform surveying work.

[0030] A dual-observation collaborative control system for a multi-agent survey system, the system comprising:

[0031] The state space model construction module is used to construct the state space model of a multi-agent survey system for complex seabed topography switching.

[0032] The disturbance simulation module is used to simulate external disturbance signals in the state space model and to monitor and collect external disturbance information through the disturbance observer and send it to the cooperative controller.

[0033] The state acquisition module is used by the collaborative controller to control the leader in the multi-agent group to perform surveying work based on the leader control protocol, to control the non-leaders in the multi-agent group to perform surveying work based on the control protocol, and to collect the state information of each multi-agent group through the state observer.

[0034] The task optimization module is used by the collaborative controller to optimize the task allocation and path planning of the leader and non-leaders based on the status information.

[0035] The system verification module is used to collect the optimized state information of each multi-agent through the state observer, and to verify the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the optimized state information.

[0036] A computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of a dual-observation cooperative control method for a multi-agent survey system.

[0037] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a dual-observation cooperative control method for a multi-agent survey system.

[0038] The aforementioned dual-observation collaborative control method, system, computer equipment, and storage medium for multi-agent survey systems construct a state-space model of a complex seabed topography switching multi-agent survey system. This model simulates external disturbance signals and controls the leader and non-leaders to perform survey work through a collaborative controller. Task allocation and path planning are optimized based on the survey status, improving the response speed and flexibility of survey tasks, better adapting to complex and changing seabed environments, effectively reducing energy consumption during the survey process, lowering operating costs, and improving economic efficiency. Furthermore, by verifying the positivity and consistency of the complex seabed topography switching multi-agent survey system, the stability and consistency of the system are ensured, enhancing the reliability of the entire survey process. Attached Figure Description

[0039] Figure 1 This is an application environment diagram of a dual-observation collaborative control method for a multi-agent survey system in one embodiment.

[0040] Figure 2 This is a flowchart illustrating a dual-observation collaborative control method for a multi-agent survey system in one embodiment.

[0041] Figure 3 This is a block diagram of a dual-observation collaborative control system for a multi-agent survey system in one embodiment;

[0042] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0044] It is understood that the terms "first," "second," etc., used in this application may be used herein to describe state-space models, but these state-space models are not limited by these terms. These terms are only used to distinguish the first state-space model from the other state-space model. For example, without departing from the scope of this application, the first state-space model may be referred to as the second state-space model, and similarly, the second state-space model may be referred to as the first state-space model. Both the first and second state-space models are state-space models, but they are not the same state-space model.

[0045] The dual-observation cooperative control method for multi-agent survey systems provided in this application can be applied to, for example... Figure 1 The application environment shown. For example... Figure 1 As shown, the application environment includes computer device 110. Computer device 110 can construct a state-space model of a multi-agent survey system for complex seabed topography switching; computer device 110 can simulate external disturbance signals in the state-space model and monitor and collect external disturbance information through a disturbance observer, sending it to the cooperative controller; the cooperative controller controls the leader among the multi-agents to perform survey work based on a leader control protocol, and controls the non-leaders among the multi-agents to perform survey work based on the control protocol, and collects the state information of each multi-agent through a state observer; the cooperative controller optimizes the task allocation and path planning of the leader and non-leaders based on the state information; computer device 110 can collect the optimized state information of each multi-agent through the state observer, and verify the positivity and consistency of the multi-agent survey system for complex seabed topography switching based on the optimized state information. Wherein, computer device 110 can be, but is not limited to, various personal computers, laptops, smartphones, robots, unmanned aerial vehicles, etc.

[0046] In one embodiment, such as Figure 2 As shown, a dual-observation cooperative control method for a multi-agent survey system is provided, comprising the following steps:

[0047] Step 202: Construct the state space model of the complex seabed topography switching multi-agent survey system.

[0048] Among them, the state-space model can be used by various intelligent agents to carry out surveying activities.

[0049] Specifically, in one embodiment, a dual-observation collaborative control method for a multi-agent survey system may further include a process of constructing a state-space model. The specific process includes: acquiring the state vectors of each agent and determining the control input vector and output vector of each agent; acquiring the switching signal between the agents and determining the system matrix of the multi-agent survey system for complex seabed topography switching; and constructing a state-space model based on the state vectors, control input vectors, output vectors, switching signals, and system matrix.

[0050] The state space model of the complex seabed topography switching multi-agent survey system is constructed in the following form: ;in, , indicating the first The state vector of an agent contains the agent's state in time. All state information, such as position, velocity, etc.; , indicating the first The control input vector of an agent contains the agent's time... All external commands or signals received; This indicates that this is the [number]. The output vector of each agent contains the agent's time... All signals or information sent; switching signals exist Take the value from, in An agent Switching between multiple intelligent systems; , , , and It is a system matrix with appropriate dimensions. Assume... It is a Metzler matrix, and the matrix , , , .

[0051] Step 204: Simulate external disturbance signals in the state space model, and monitor and collect external disturbance information through a disturbance observer and send it to the cooperative controller.

[0052] The external disturbance signal is described as follows: ; ;in, It is the addition signal for each agent. , , and It is a Metzler matrix.

[0053] In one embodiment, the state space model includes a first state space model for leader-led surveying and a second state space model for non-leader-led surveying; the complex seabed topography switching multi-agent surveying system includes a leader system for leader-led surveying and a non-leader system for non-leader-led surveying.

[0054] The construction of the multi-agent reconnaissance leader system for switching complex seabed topography is as follows: ,in, , and It is the status and control input of the leader system. It is the Metzler matrix and It is the corresponding coefficient matrix.

[0055] Step 206: The collaborative controller controls the leader among the multi-agents to perform surveying work based on the leader control protocol, controls the non-leaders among the multi-agents to perform surveying work based on the control protocol, and collects the state information of each multi-agent through the state observer.

[0056] In one embodiment, a dual-observation collaborative control method for a multi-agent survey system may further include a process of designing a control protocol, specifically including: designing a leader control protocol based on the leader among the multi-agents, and designing a control protocol based on the non-leaders among the multi-agents; the leader control protocol is used to control the leader to perform survey work; and the control protocol is used to control the non-leaders to perform survey work.

[0057] Specifically, the leader control protocol for the complex seabed topography switching multi-agent survey system is designed as follows: in, It is a constant vector. , and It is an auxiliary item.

[0058] The control protocol for the multi-agent survey system for complex seabed topography switching is designed as follows:

[0059]

[0060] in, , , and These are control protocol, state estimation, disturbance estimation, and output. , , , , and This is the control gain matrix.

[0061] Step 208: The collaborative controller optimizes the task allocation and path planning for leaders and non-leaders based on the status information.

[0062] In one embodiment, a dual-observation cooperative control method for a multi-agent survey system may further include a process of optimizing paths and task allocation. The specific process includes: the cooperative controller determines a cooperative control strategy based on state information, and performs path planning for each agent using a linear programming method based on the cooperative control strategy; the cooperative controller adjusts the allocation of tasks for the leader and non-leaders based on the cooperative control strategy, and plans the survey paths for the leader and non-leaders based on the linear programming method.

[0063] Step 210: Collect the optimized state information of each multi-agent through the state observer, and verify the positivity and consistency of the multi-agent survey system for complex seabed topography based on the optimized state information.

[0064] In one embodiment, a dual-observation collaborative control method for a multi-agent survey system may further include a process of setting operating conditions, specifically including: setting operating conditions for the smooth operation of the leader system and the non-leader system respectively; and verifying the positivity and consistency of the leader system and the non-leader system based on the operating conditions.

[0065] Among them, the conditions for the stable operation of a multi-agent, multi-leader system for complex seabed topography survey are: design constants. , , , , , vector , Make:

[0066]

[0067] Therefore, the multi-agent survey leader system for switching complex seabed topography achieves positivity and consistency, with the gain matrix being: ;in, yes An identity matrix of dimension 1 Indicates the first One element is 1 and the rest are 0. 3D column vectors, gain matrix .

[0068] In this embodiment, the positive condition for the complex seabed topography switching multi-agent survey system is: design constant. , , , , , vector , Make:

[0069]

[0070]

[0071] The consistency condition for the multi-agent survey system for complex seabed topography switching is: design constant. , , , , , vector , Make:

[0072]

[0073]

[0074]

[0075]

[0076]

[0077] Therefore, the multi-agent reconnaissance leader system for complex seabed topography switching achieves positive results and consistency under a dual-observer and control protocol, with the gain matrix being:

[0078] in, , , , , and , , , , , .

[0079] In one embodiment, a dual-observation collaborative control method for a multi-agent survey system may further include a system verification process, which specifically includes: verifying the leader system and the non-leader system respectively using matrix decomposition and copositive Lyapunov function based on the optimized state information, and obtaining verification results; and determining the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the verification results.

[0080] The positive and consistency verification process of the multi-agent reconnaissance multi-leader system for complex seabed topography switching is as follows: Let We can obtain:

[0081]

[0082] in, , The Laplace matrix represents the communication topology between multiple agents. Define variables. , making .choose ,So Then we can get:

[0083]

[0084] Based on the conditions for stable operation of a multi-agent survey and multi-leader system for complex seabed topography and the gain matrix, we can conclude that:

[0085] because It is a Metzler matrix, and is derived using the positivity and consistency verification conditions of a multi-agent survey system with complex seabed topography switching and the conditions for the stable operation of such a system: ; ;in, Therefore, there is .for You can get This indicates that the multi-agent, multi-leader system for complex seabed topography survey is positive.

[0086] Therefore, the multi-leader system in multi-agent survey of complex seabed topography is positive. That is, during the execution of survey tasks, the positivity of survey coverage and data acquisition quality can be verified; in collaborative operations, the positivity of information interaction and task allocation among multiple agents can be verified; in environmental adaptation activities, the positivity of agents' response to changes in complex seabed environment and adjustment strategies can be verified; and in energy management activities, the positivity of endurance and energy utilization efficiency can be verified.

[0087] The consistency verification process for a multi-agent survey leader system in complex seabed topography switching is as follows: Selecting... Then we have:

[0088]

[0089] Based on the conditions for stable operation of a multi-agent survey and multi-leader system for complex seabed topography and the gain matrix, we can obtain: Based on the conditions for the stable operation of a multi-agent survey and multi-leader system for complex seabed topography, we can conclude that:

[0090] ;

[0091] but .Right now Therefore, the multi-agent survey leader system for switching complex seabed topography exhibits consistency.

[0092] Therefore, it can be concluded from the above that the multi-agent survey leader system for complex seabed topography switching has consistency. That is, when designing and implementing the distributed decision-making mechanism, the system can ensure that the operation behavior and working status of each intelligent survey device, navigation system, data acquisition module and collaborative operation unit can be coordinated and synchronized with each other while meeting the diverse survey task requirements. This achieves the goal of efficient and orderly overall survey process and optimal resource allocation, thereby improving survey efficiency, reducing energy consumption and flexibly adapting to changes in complex seabed environment.

[0093] In this embodiment, the positive and consistency verification process of the complex seabed topography switching multi-agent survey system is as follows:

[0094] pass and Then there is

[0095]

[0096] The system consists of two parts: when hour,

[0097] when hour,

[0098]

[0099] make , We can obtain:

[0100]

[0101] in,

[0102]

[0103]

[0104] make , can be obtained ,but Therefore, we can obtain:

[0105] .

[0106] Therefore, we can deduce that:

[0107]

[0108] Among them, matrix , , .

[0109] Therefore, we can conclude that:

[0110]

[0111] Depend on It is a Metzler matrix, which indicates that the multi-agent survey system for complex seabed topography is positive.

[0112] In this embodiment, a copositive Lyapunov function can be selected:

[0113]

[0114] in, , , , Then, we have

[0115]

[0116] Therefore, we can conclude that:

[0117] in, .

[0118]

[0119] in, .therefore:

[0120]

[0121] The conditions for the stable operation of a multi-agent survey system for complex seabed topography switching can be obtained as follows:

[0122]

[0123] in, .

[0124]

[0125] in, .therefore, .

[0126] The conditions for the stable operation of a multi-agent survey system in complex seabed topography are derived as follows:

[0127]

[0128] in, .

[0129]

[0130] in, .therefore,

[0131]

[0132] The conditions for the stable operation of a multi-agent survey system in complex seabed topography are derived as follows:

[0133]

[0134] in, .

[0135] The conditions for the stable operation of a multi-agent survey system in complex seabed topography are derived as follows:

[0136]

[0137] in, .

[0138]

[0139] in, , .therefore,

[0140]

[0141] The conditions for the stable operation of a multi-agent survey system in complex seabed topography are derived as follows:

[0142]

[0143] in, , .

[0144] Therefore, it can be seen that the multi-agent survey system for complex seabed topography switching has consistency.

[0145] It should be understood that although the steps in each flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the above flowcharts may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0146] In one embodiment, such as Figure 3 As shown, a dual-observation collaborative control system for a multi-agent survey system is provided, comprising: a state-space model construction module 310, a disturbance simulation module 320, a state acquisition module 330, a task optimization module 340, and a system verification module 350, wherein:

[0147] State space model construction module 310 is used to construct the state space model of a multi-agent survey system for complex seabed topography switching.

[0148] The disturbance simulation module 320 is used to simulate external disturbance signals in the state space model and to monitor and collect external disturbance information through the disturbance observer and send it to the cooperative controller.

[0149] The state acquisition module 330 is used by the collaborative controller to control the leader in the multi-agent group to carry out surveying work based on the leader control protocol, to control the non-leaders in the multi-agent group to carry out surveying work based on the control protocol, and to collect the state information of each multi-agent group through the state observer.

[0150] The task optimization module 340 is used by the collaborative controller to optimize the task allocation and path planning of the leader and non-leader based on the status information.

[0151] The system verification module 350 is used to collect the optimized state information of each multi-agent through the state observer, and to verify the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the optimized state information.

[0152] In one embodiment, the state space model construction module 310 is further used to collect the state vectors of each agent and determine the control input vector and output vector of each agent; obtain the switching signal between agents and determine the system matrix of the complex seabed terrain switching multi-agent survey system; and construct a state space model based on the state vectors, control input vectors, output vectors, switching signals, and system matrix.

[0153] In one embodiment, the task optimization module 340 is further configured to use the cooperative controller to determine the cooperative control strategy based on the state information, and to use linear programming techniques to plan the paths of each agent based on the cooperative control strategy; the cooperative controller allocates and adjusts the tasks of the leader and non-leaders based on the cooperative control strategy, and plans the survey paths of the leader and non-leaders based on the linear programming method.

[0154] In one embodiment, the state space model includes a first state space model for leader-led surveying and a second state space model for non-leader-led surveying; the complex seabed topography switching multi-agent surveying system includes a leader system for leader-led surveying and a non-leader system for non-leader-led surveying.

[0155] In one embodiment, the system verification module 350 is further configured to verify the leader system and the non-leader system respectively using matrix decomposition and copositive Lyapunov function based on the optimized state information, and obtain the verification results; and determine the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the verification results.

[0156] In one embodiment, the system verification module 350 is further configured to set the operating conditions for the smooth operation of the leader system and the non-leader system respectively; and to verify the positivity and consistency of the leader system and the non-leader system based on the operating conditions respectively.

[0157] In one embodiment, the state acquisition module 330 is further configured to design a leader control protocol based on the leader in a multi-agent system and a control protocol based on the non-leaders in a multi-agent system; the leader control protocol is used to control the leader to perform surveying work; and the control protocol is used to control the non-leaders to perform surveying work.

[0158] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a dual-observation cooperative control method for a multi-agent survey system. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0159] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0160] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement steps of a dual-observation cooperative control method for a multi-agent survey system.

[0161] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of a dual-observation cooperative control method for a multi-agent survey system.

[0162] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0163] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A dual-observation cooperative control method for a multi-agent survey system, characterized in that, The method includes: Constructing a state-space model for a multi-agent survey system for complex seabed topography switching includes: collecting the state vectors of each agent and determining the control input vector and output vector of each agent; acquiring the switching signals between agents and determining the system matrix of the multi-agent survey system for complex seabed topography switching; and constructing a state-space model based on the state vectors, control input vectors, output vectors, switching signals, and system matrix. External disturbance signals are simulated in the state space model, and external disturbance information is collected by a disturbance observer and sent to the cooperative controller. The collaborative controller controls the leader among the multi-agents to perform surveying work based on a leader control protocol, and controls the non-leaders among the multi-agents to perform surveying work based on a control protocol, and collects the state information of each multi-agent through a state observer; wherein, the state space model includes a first state space model for the leader to perform surveying work and a second state space model for the non-leaders to perform surveying work; the complex seabed terrain switching multi-agent surveying system includes a leader system for the leader to perform surveying and a non-leader system for the non-leaders to perform surveying. The collaborative controller optimizes the task allocation and path planning of the leader and non-leaders based on the state information, including: the collaborative controller determines a collaborative control strategy based on the state information, and performs path planning for each agent using a linear programming method based on the collaborative control strategy; the collaborative controller adjusts the task allocation of the leader and non-leaders based on the collaborative control strategy, and plans the survey paths of the leader and non-leaders based on the linear programming method; The state observer collects the optimized state information of each multi-agent, and verifies the positivity and consistency of the multi-agent survey system for complex seabed topography based on the optimized state information.

2. The dual-observation cooperative control method for a multi-agent survey system according to claim 1, characterized in that, Verifying the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the optimized state information includes: Based on the optimized state information, the leader system and the non-leader system are verified using matrix decomposition and copositive Lyapunov function, respectively, and the verification results are obtained. The positivity and consistency of the complex seabed topography switching multi-agent survey system are determined based on the verification results.

3. The dual-observation cooperative control method for a multi-agent survey system according to claim 1, characterized in that, The method further includes: Set the operating conditions for the smooth operation of the leader system and the non-leader system respectively; Verify the positivity and consistency of the leader system and the non-leader system based on the aforementioned operating conditions.

4. The dual-observation cooperative control method for a multi-agent survey system according to claim 1, characterized in that, The method further includes: Design a leader control protocol based on the leader in a multi-agent system, and design a control protocol based on the non-leader in a multi-agent system. The leader control protocol is used to control the leader to perform surveying work; the control protocol is used to control the non-leader to perform surveying work.

5. A dual-observation collaborative control system for a multi-agent survey system, characterized in that, The system includes: The state space model construction module is used to construct the state space model of the complex seabed topography switching multi-agent survey system, including: collecting the state vectors of each agent and determining the control input vector and output vector of each agent; obtaining the switching signal between the agents and determining the system matrix of the complex seabed topography switching multi-agent survey system; and constructing the state space model based on the state vectors, control input vectors, output vectors, switching signals, and system matrix. The disturbance simulation module is used to simulate external disturbance signals in the state space model and to monitor and collect external disturbance information through the disturbance observer and send it to the cooperative controller. The state acquisition module is used by the cooperative controller to control the leader among the multi-agents to perform surveying work based on the leader control protocol, and to control the non-leaders among the multi-agents to perform surveying work based on the control protocol, and to collect the state information of each multi-agent through a state observer; wherein, the state space model includes a first state space model for the leader to perform surveying work and a second state space model for the non-leaders to perform surveying work; the complex seabed terrain switching multi-agent surveying system includes a leader system for the leader to perform surveying and a non-leader system for the non-leaders to perform surveying. The task optimization module is used by the collaborative controller to optimize the task allocation and path planning of the leader and non-leaders based on the state information. This includes: the collaborative controller determining a collaborative control strategy based on the state information, and using a linear programming method to plan paths for each agent based on the collaborative control strategy; the collaborative controller adjusting the task allocation of the leader and non-leaders based on the collaborative control strategy, and planning the survey paths of the leader and non-leaders based on the linear programming method. The system verification module is used to collect the optimized state information of each multi-agent through the state observer, and to verify the positivity and consistency of the complex seabed topography switching multi-agent survey system based on the optimized state information.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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