Marine survey task planning method and system based on distributed cooperative control

Abstract

The invention relates to an ocean survey task planning method and system based on distributed cooperative control, and relates to the technical field of data processing, and the method comprises the steps: determining the information transmission amount from a first platform to a second platform; evaluating the difficulty and priority of each measurement task of the to-be-measured ocean region based on the environmental information; predicting a task allocation suggestion value of the first platform and the second platform in the next negotiation round of the current negotiation round; performing path planning on the first platform and the second platform based on an improved algorithm of a potential field method, and determining planned paths of the first platform and the second platform; simulating a measurement task based on the planned paths of the first platform and the second platform, enabling the first platform and the second platform to carry out resource coordination sharing through a distributed resource sharing protocol, determining a resource sharing proportion and the updated resource quantity of the first platform, and completing the measurement task planning of the to-be-measured ocean region. According to the invention, the efficiency and precision of ocean measurement tasks can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method, system, electronic device, and non-transitory computer-readable storage medium for ocean measurement task planning based on distributed collaborative control. Background Art

[0002] Currently, ocean measurement task planning usually relies on centralized or traditional algorithm-based methods. These methods mostly execute measurement tasks through preset paths, control instructions, and task allocation strategies. For example, based on traditional path planning methods, greedy algorithms, A* algorithms, etc. are used for static or dynamic path planning to determine the action trajectory of the measurement platform in the sea area. In addition, common centralized control systems will set up a central scheduling platform, which is responsible for uniformly coordinating multiple platforms to execute measurement tasks, and realizes task allocation and execution scheduling through centralized decision-making.

[0003] However, in the ocean environment, factors such as meteorological conditions, ocean current changes, obstacles, and equipment failures often cause measurement tasks to need dynamic adjustment, and centralized control methods are difficult to respond to these sudden changes in real time. In addition, traditional methods usually assume that platforms execute independently, lacking a collaborative cooperation mechanism between platforms, resulting in low efficiency of task allocation, resource sharing, and data fusion in multi-platform collaborative operations, thus affecting the overall task completion efficiency and accuracy. Summary of the Invention

[0004] The present invention aims at the technical problems existing in the prior art, and provides a method, system, electronic device, and non-transitory computer-readable storage medium for ocean measurement task planning based on distributed collaborative control, which can improve the accuracy and efficiency of ocean measurement tasks.

[0005] The technical solution for the present invention to solve the above technical problems is as follows:

[0006] The present invention provides a method for ocean measurement task planning based on distributed collaborative control, and the method includes:

[0007] Perceive the environmental information of the ocean area to be measured through multiple sensors and share it among platforms under distributed collaborative control, and determine the information transmission volume from the first platform to the second platform;

[0008] Evaluate the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information;

[0009] Perform task allocation through a distributed negotiation mechanism, and predict the task allocation suggestion value of the first platform and the second platform in the next negotiation round of the current negotiation round;

[0010] An improved algorithm based on the potential field method performs path planning for the first platform and the second platform to determine the planned paths of the first platform and the second platform;

[0011] Simulate the measurement task based on the planned paths of the first platform and the second platform, and enable the first platform and the second platform to perform resource coordination and sharing through the distributed resource sharing protocol, determine the resource sharing ratio and the updated resource amount of the first platform, and complete the measurement task planning for the ocean area to be measured.

[0012] Optionally, the environmental information of the ocean area to be measured is sensed by multiple sensors and shared among the platforms under distributed collaborative control, and the information transmission volume from the first platform to the second platform is determined, including:

[0013] Obtain the position, ocean meteorological data, obstacle information, and measurement task area information obtained by the first platform, as well as the speed of the first platform;

[0014] Perform weighted processing on the position, ocean meteorological data, obstacle information, and measurement task area information obtained by the first platform, as well as the speed of the first platform, to obtain an information weighting function;

[0015] Obtain the distance between the first platform and the second platform, and a first constant representing the communication range and signal attenuation;

[0016] Construct an information attenuation factor based on the distance between the first platform and the second platform and the first constant;

[0017] Determine the information transmission volume from the first platform to the second platform according to the information weighting function and the information attenuation factor.

[0018] Optionally, the information transmission volume from the first platform to the second platform is expressed as:

[0019]

[0020] where I ij is the information transmission volume from the i-th platform to the j-th platform, the i-th platform represents the first platform, the j-th platform represents the second platform, P i =(x i , y i , z i ) is the position obtained by the i-th platform, V i is the speed of the i-th platform, M i =(t i , w i , p i ) is the ocean meteorological data obtained by the i-th platform, t iis temperature, w i is wind speed, p i is air pressure, O i is the obstacle information obtained by the i-th platform, A is the measurement task area information obtained by the i-th platform, d ij is the distance from the i-th platform to the j-th platform, k is the first constant related to the communication range and signal attenuation, f(P i ,V i ,M i ,O i ,A) is the information weighting function, is the information attenuation factor.

[0021] Optionally, evaluating the difficulty and priority of each measurement task for the to-be-measured ocean area based on the environmental information includes:

[0022] Obtain the reference meteorological conditions of the to-be-measured ocean area and the obstacle positions of each obstacle;

[0023] Calculate the first distance between the position of the first platform and the obstacle positions of all obstacles;

[0024] Calculate the gap between the current ocean meteorological data and the reference meteorological conditions;

[0025] Calculate the second distance between the position of the first platform and the target point in the measurement task area information;

[0026] Determine a task difficulty evaluation value for evaluating the difficulty of each measurement task for the to-be-measured ocean area according to the gap, the first distance, and the second distance;

[0027] Obtain the remaining time of the measurement task, and determine the priority of the measurement task based on the remaining time of the measurement task and the task difficulty evaluation value.

[0028] Optionally, the task difficulty evaluation value and the task priority evaluation value are expressed as:

[0029]

[0030] where D i is the task difficulty evaluation value, α, β, and γ are the first weight, the second weight, and the third weight respectively, M ref is the reference meteorological condition;

[0031]

[0032] where Pr i is the task priority evaluation value, T ri is the remaining time of the task.

[0033] Optionally, the task assignment through the distributed negotiation mechanism to predict the task assignment recommended value for the next negotiation round of the first platform and the second platform in the current negotiation round includes:

[0034] Obtain the task priority evaluation value, trust weight, and task completion ability evaluation value between the first platform and the second platform;

[0035] Determine the first task assignment recommended value for the first platform and the second platform in the current negotiation round according to the task priority evaluation value, trust weight, and task completion ability evaluation value between the first platform and the second platform;

[0036] Obtain the second task assignment recommended value for the first platform and all its neighbor platforms in the current negotiation round;

[0037] Predict the task assignment recommended value for the next negotiation round of the first platform and the second platform in the current negotiation round according to the first task assignment recommended value and the second task assignment recommended value.

[0038] Optionally, the improved algorithm based on the potential field method performs path planning for the first platform and the second platform to determine the planned paths of the first platform and the second platform, including:

[0039] For the first platform and the second platform, construct an attractive potential field that makes the platform move towards the target point according to the coordinates of the current position and the target position of the platform;

[0040] Construct a repulsive potential field that makes the platform move away from the obstacle according to the current position of the platform and the obstacle position of the obstacle;

[0041] Construct a potential field function that guides the platform to move towards the target point and avoids collisions with the obstacle according to the attractive potential field and the repulsive potential field;

[0042] Obtain the gradient of the potential field function, and determine the speed of the platform according to the gradient of the potential field function;

[0043] Determine the planned path for the platform to move towards the target point at the speed and avoid collisions with the obstacle according to the potential field function and the speed of the platform.

[0044] Optionally, the first platform and the second platform perform resource coordination and sharing through the distributed resource sharing protocol to determine the resource sharing ratio, including:

[0045] Obtain the cooperation information between the first platform and the second platform; the cooperation information includes the degree of trust, resource status, and importance of historical cooperation tasks between the first platform and the second platform;

[0046] Determine the resource sharing ratio between the first platform and the second platform according to the cooperation information between the first platform and the second platform.

[0047] Optionally, the updated resource amount of the first platform is determined through the following steps:

[0048] Obtain the current resource amount of the first platform and the resource demand of the first platform;

[0049] Determine the resource sharing amount between the first platform and the second platform according to the resource sharing ratio between the first platform and the second platform, and the current resource amount and resource demand of the first platform;

[0050] Update the current resource amount of the first platform according to the resource sharing amount between the first platform and the second platform to obtain the updated resource amount of the first platform.

[0051] In addition, to achieve the above object, the present invention also proposes an ocean measurement task planning system based on distributed cooperative control, including:

[0052] An information transmission module, configured to sense the environmental information of the ocean area to be measured through multiple sensors and share it among the platforms in distributed cooperative control, and determine the information transmission amount from the first platform to the second platform;

[0053] A task evaluation module, configured to evaluate the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information;

[0054] A task allocation module, configured to perform task allocation through a distributed negotiation mechanism and predict the task allocation recommendation value of the first platform and the second platform in the next negotiation round of the current negotiation round;

[0055] A path planning module, configured to perform path planning on the first platform and the second platform based on an improved algorithm of the potential field method, and determine the planned paths of the first platform and the second platform;

[0056] A resource sharing module, configured to simulate measurement tasks based on the planned paths of the first platform and the second platform, and enable the first platform and the second platform to perform resource coordinated sharing through a distributed resource sharing protocol, determine the resource sharing ratio and the updated resource amount of the first platform, and complete the measurement task planning for the ocean area to be measured.

[0057] In addition, to achieve the above object, the present invention further provides an electronic device, including: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby implementing a method for ocean measurement task planning based on distributed collaborative control as described above.

[0058] In addition, to achieve the above object, the present invention further provides a non-transitory computer-readable storage medium, in which a computer software program is stored, and when the computer software program is executed by a processor, a method for ocean measurement task planning based on distributed collaborative control as described above is implemented.

[0059] The beneficial effects of the present invention are:

[0060] (1) The present invention can effectively coordinate multiple unmanned platforms (such as unmanned aerial vehicles and unmanned surface vehicles) to jointly execute ocean measurement tasks. Each platform dynamically exchanges information and collaborates on tasks with other platforms according to its own environmental perception, task assessment, and priority setting. This collaborative working mode avoids the bottleneck and delay problems that may occur in a centralized control system, enabling multiple platforms to complete tasks in parallel and efficiently. Through information sharing and task allocation among platforms, the task completion time can be greatly shortened, and the coverage and accuracy of measurement data can be improved.

[0061] (2) Through the real-time environmental perception and information sharing mechanism of the present invention, each platform can quickly perceive the surrounding environmental changes (such as wind speed, air pressure, underwater obstacles, etc.) and share this information with other platforms. This provides a reliable basis for dynamic task adjustment and path planning. The platform can respond to environmental changes in real time, flexibly adjust the task execution strategy, and avoid task failure or delay caused by sudden environmental changes.

[0062] (3) The distributed collaborative mechanism of the present invention enables multiple platforms to perform dynamic task adjustment and resource allocation according to the actual situation during task execution. When a platform fails or cannot complete the task on time, other platforms can supplement through task reallocation and resource sharing to ensure the continuity and integrity of the task. It improves the fault tolerance of the system to faults or abnormal situations, enhances the robustness of the system, and avoids the problem of task failure caused by a single platform failure.

[0063] In summary, the present invention can improve task efficiency, enhance adaptability and robustness, optimize resource utilization, precisely plan paths and avoid obstacles, dynamically adjust task priorities, support intelligent decision-making and multi-task collaboration, etc. It has high application potential in complex ocean measurement tasks and can effectively improve the accuracy, efficiency, and safety of task execution. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 Scenario diagram of a marine survey task planning method based on distributed collaborative control provided by the present invention;

[0065] Figure 2 Flowchart of a marine survey task planning method based on distributed collaborative control provided by the present invention;

[0066] Figure 3 Schematic structural diagram of a marine survey task planning system based on distributed collaborative control provided by the present invention;

[0067] Figure 4 Schematic hardware structure diagram of a possible electronic device provided by the present invention;

[0068] Figure 5 Schematic hardware structure diagram of a possible computer-readable storage medium provided by the present invention. Detailed implementation manners

[0069] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0070] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality of" means two or more, unless otherwise specifically defined.

[0071] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or having more advantages than other embodiments. In order for any person skilled in the art to implement and use the present invention, the following description is given. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0072] Please refer to Figure 1 ,Figure 1 This is a scenario diagram of a marine survey task planning method based on distributed collaborative control provided by the present invention. As Figure 1 shown, the terminal and the server are connected through a network, for example, through a wired or wireless network connection, etc. Among them, the terminal may include, but is not limited to, portable terminals such as mobile phones and tablets installed with various network platform applications, as well as fixed terminals such as computers, inquiry machines, and advertising machines. Among them, the server provides various business services for users, including service push servers, user recommendation servers, etc.

[0073] It should be noted that Figure 1 the scenario diagram of a marine survey task planning method based on distributed collaborative control shown is only an example. The terminals, servers, and application scenarios described in the embodiments of the present invention are for more clearly explaining the technical solutions of the embodiments of the present invention, and do not generate limitations on the technical solutions provided by the embodiments of the present invention. Those of ordinary skill in the art know that with the evolution of the system and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.

[0074] Among them, the terminal can be used for:

[0075] Perceiving the environmental information of the marine area to be measured through various sensors and sharing it among platforms under distributed collaborative control, and determining the information transmission volume from the first platform to the second platform;

[0076] Evaluating the difficulty and priority of each measurement task for the marine area to be measured based on the environmental information;

[0077] Conducting task allocation through a distributed negotiation mechanism and predicting the task allocation proposed value of the first platform and the second platform in the next negotiation round of the current negotiation round;

[0078] Performing path planning for the first platform and the second platform based on an improved algorithm of the potential field method, and determining the planned paths of the first platform and the second platform;

[0079] Simulating the measurement task based on the planned paths of the first platform and the second platform, and enabling the first platform and the second platform to conduct resource coordination and sharing through a distributed resource sharing protocol, determining the resource sharing ratio and the updated resource volume of the first platform, and completing the measurement task planning for the marine area to be measured.

[0080] Please refer to Figure 2 , which provides a flowchart of a marine survey task planning method based on distributed collaborative control of the present invention, including the following steps:

[0081] Step 201: Sense the environmental information of the ocean area to be measured through multiple sensors and share it among the platforms with distributed collaborative control, and determine the information transmission volume from the first platform to the second platform.

[0082] In some embodiments, step 201 may include:

[0083] Obtain the position, ocean meteorological data, obstacle information, and measurement task area information acquired by the first platform, as well as the speed of the first platform;

[0084] Perform weighted processing on the position, ocean meteorological data, obstacle information, and measurement task area information acquired by the first platform, as well as the speed of the first platform, to obtain an information weighting function;

[0085] Obtain the distance between the first platform and the second platform, and a first constant representing the communication range and signal attenuation;

[0086] Construct an information attenuation factor based on the distance between the first platform and the second platform and the first constant;

[0087] Determine the information transmission volume from the first platform to the second platform according to the information weighting function and the information attenuation factor.

[0088] In some embodiments, the information transmission volume from the first platform to the second platform is expressed as:

[0089]

[0090] where I ij is the information transmission volume from the i-th platform to the j-th platform, the i-th platform represents the first platform, the j-th platform represents the second platform, P i =(x i ,y i ,z i ) is the position acquired by the i-th platform, V i is the speed of the i-th platform, M i =(t i ,w i ,p i ) is the ocean meteorological data acquired by the i-th platform, t i is the temperature, w i is the wind speed, p i is the air pressure, O i is the obstacle information acquired by the i-th platform, A is the measurement task area information acquired by the i-th platform, d ij is the distance between the i-th platform and the j-th platform, k is the first constant related to the communication range and signal attenuation, f(P i ,Vi , M i , O i , A) is an information weighting function, is an information attenuation factor.

[0091] In a specific implementation, P i is the position of platform i. Platform i is the i-th platform, i.e., the first platform, and this position is a three-dimensional coordinate (usually the longitude, latitude, and altitude in a geographic coordinate system). The position of the platform plays a key role in information transmission because the relative positions of the platforms determine the distance d for their information exchange ij .

[0092] V i is the velocity of platform i, usually represented by three components of velocity (v xi , v yi , v zi ), representing the velocity components of the platform in the x, y, and z directions respectively. The velocity of the platform affects the speed of change in its relative position with other platforms, thus affecting the update frequency of information and the timeliness of transmission.

[0093] M i is the marine meteorological data collected by platform i, including temperature, wind speed, and air pressure. Marine meteorological data is very important environmental information, which affects the actions, mission planning, and mission priorities of the platform. Different meteorological data may lead to different adjustments in the priority or sharing method of information sharing by the platform.

[0094] O i is the obstacle information obtained by platform i, including the position and type of the obstacle. Obstacle information is crucial for platform path planning and obstacle avoidance. Therefore, the platform needs to share the obstacle information with other platforms to jointly optimize the path selection during task execution.

[0095] A is the measurement task area information obtained by platform i, which defines the spatial scope of task execution. The nature of the task area (such as size, geographical distribution) affects the task allocation and execution strategy of the platform.

[0096] d ij is the distance from platform i to platform j, i.e., the spatial distance between the platforms. An increase in distance usually leads to a decrease in information transmission efficiency, so the amount of information transmitted is affected by the distance.

[0097] k is the first constant related to the communication range and signal attenuation. It controls the attenuation speed of information transmission, that is, the farther the distance between the platforms, the faster the amount of information transmitted attenuates. This constant reflects the relationship between signal strength and communication quality between platforms.

[0098] f(P i , Vi ,M i ,O i ,A) is the information weighting function, which is weighted according to the type of information obtained by platform i, reflecting the importance of different information to the information transmission between platforms. Specifically, the platform adjusts the weight of the information to be transmitted according to its own position, speed, meteorological data, obstacle information and mission area information. For example, when the position of platform i is close to other platforms, or encounters important marine meteorological events during mission execution, the amount of information transmission may increase; while if the distance between platforms is far or they are in unfavorable environmental conditions, the amount of information transmission may decrease.

[0099] The information weighting function can be used to dynamically adjust the amount of information transmitted, which is to adjust the importance of information transmission according to the status of the platform and the mission requirements. For example, if a platform needs urgent weather information during the mission, or the location of other platforms overlaps with the mission area, then the amount of information transmitted by this platform will be greater.

[0100] Information decay factor The amount of information transmitted is attenuated by the distance between the platforms. When the distance between the two platforms increases, the amount of information transmitted decreases sharply, which reflects the physical limitations of wireless communications in reality: the signal gradually attenuates during the propagation process.

[0101] f(P i ,V i ,M i ,O i ,A) Weighted adjustment of the importance of information based on the specific situation of the platform. The attenuation of information is controlled by the distance between the platforms, ensuring that the information transmission between the platforms gradually decreases at long distances. This allows the present invention to flexibly reflect the communication efficiency and task requirements between the platforms through the amount of information transmission between the two platforms, while taking into account environmental factors, the relative positions between the platforms, and the motion states of the platforms.

[0102] Step 202: Evaluate the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information.

[0103] In some embodiments, step 202 may include:

[0104] Obtaining reference meteorological conditions of the ocean area to be measured and obstacle positions of various obstacles;

[0105] Calculating a first distance between the position of the first platform and the obstacle positions of all obstacles;

[0106] Calculate the difference between current marine meteorological data and reference meteorological conditions;

[0107] Calculate the second distance between the position of the first platform and the target point in the measurement task area information;

[0108] Determine a task difficulty evaluation value for evaluating the difficulty of each measurement task in the to-be-measured ocean area according to the gap, the first distance, and the second distance;

[0109] Obtain the remaining time of the measurement task, and determine the priority of the measurement task based on the remaining time of the measurement task and the task difficulty evaluation value.

[0110] In some cases, the task difficulty evaluation value and the task priority evaluation value are expressed as:

[0111]

[0112] where D i is the task difficulty evaluation value, α, β, and γ are the first weight, the second weight, and the third weight respectively, and M ref is the reference meteorological condition;

[0113]

[0114] where Pr i is the task priority evaluation value, and T ri is the remaining time of the task.

[0115] In specific implementation, D i is the task difficulty evaluation value of a certain task of the i-th platform. The larger the value, the more difficult the task. This task difficulty value affects the platform's priority evaluation of the task, and further determines whether the platform selects or is more inclined to execute the task. The calculation of the task difficulty considers multiple factors such as obstacles, meteorological data, and the task area, and comprehensively evaluates the challenge degree of these factors to task completion.

[0116] O i represents the set of obstacles perceived by platform i. Each obstacle has a position o = (o xi , o yi , o zi ), and these obstacles may affect the path planning and obstacle avoidance decision-making of the platform.

[0117] This part represents the sum of the distances between platform i and all the obstacles it perceives. The farther the obstacle, the lower the task difficulty; the closer the obstacle, the greater the task difficulty, and the platform needs more complex path planning to avoid the obstacle.

[0118] M i represents the ocean meteorological data collected by platform i, including temperature, wind speed, and air pressure. M refis the reference meteorological condition, usually the ideal meteorological state or a certain standard meteorological condition. The platform evaluates the task difficulty based on the deviation between its own meteorological data and the reference meteorological condition. ∣M i -M ref ∣ This item reflects the gap between the meteorological data actually collected by the platform and the ideal meteorological condition. If the meteorological condition is abnormal (such as strong wind, big waves, etc.), the task difficulty will increase.

[0119] A = (A x , A y , A z ) represents the coordinates or spatial range of the task area. The platform needs to plan the path and execute the task according to the distribution of the task area. ∣∣P i -A∣∣ This item represents the distance between the current position P i of platform i and the target position in the task area A. If the platform is far from the task area, the task difficulty is higher because more time and energy are required to move into the task area.

[0120] α controls the influence degree of obstacles on the task difficulty assessment. If the obstacles are close to the platform, the task difficulty will increase significantly. Therefore, the larger the value of α, the greater the influence of obstacles on the task difficulty.

[0121] β reflects the influence of meteorological conditions on task execution. Extreme meteorological conditions (such as strong wind, big waves, etc.) will increase the task difficulty. Therefore, the larger the value of β, the greater the influence of meteorological conditions on the task difficulty.

[0122] γ controls the influence of the task area on the task difficulty. If the task area is far from the platform, or the task area is very large or complex, the task difficulty will increase. Therefore, the larger the value of γ, the greater the influence of the task area.

[0123] This part measures the distance between the platform and all obstacles. The closer the obstacles are, the greater the task difficulty. The platform needs more complex path planning to avoid colliding with obstacles. Therefore, the influence of obstacles occupies an important part of the task difficulty assessment.

[0124] β∣M i -M ref ∣ This part measures the gap between the current marine meteorological condition and the ideal meteorological condition. Meteorological conditions have a great influence on task execution, especially in the marine environment. Factors such as wind speed, temperature, and air pressure may cause difficulties in the platform's movement or low task completion accuracy. Therefore, it is necessary to adjust the task difficulty according to these changes.

[0125] γ∣∣P i-A||This part measures the distance between the current position of the platform and the target point in the task area. If the platform is far from the task area, the task difficulty is greater. The larger the task area, or the more complex the measurement area that the platform needs to cover, the task difficulty will also increase.

[0126] D i Comprehensively considering the obstacles, meteorological data, and the situation of the task area, it evaluates the difficulty level of platform i to execute the task. The weight coefficients in the formula determine the importance of each factor in the task difficulty evaluation.

[0127] The distance of obstacles, the deviation of meteorological conditions, and the distance to the task area jointly affect the task difficulty. Through such an evaluation, the platform can dynamically adjust the task priority, resource allocation, and path planning strategy according to the actual difficulty of the task, so as to complete the ocean measurement task more efficiently.

[0128] In summary, the mechanism based on task difficulty evaluation of the present invention enables the platform to flexibly adjust the task execution strategy according to different environmental and task requirements, thereby improving the task execution efficiency, adapting to complex environmental changes, and optimizing resource utilization.

[0129] In the specific implementation, D i represents the overall difficulty of the task, comprehensively considering factors such as obstacles, meteorological conditions, and the task area. The greater the task difficulty, the greater the challenge for the platform to execute the task.

[0130] The influence of task difficulty on task priority is negative: the higher the task difficulty, the lower the priority evaluation value Pr i the lower, which means that the platform tends to place high-difficulty tasks at a low priority, unless other conditions require urgent completion.

[0131] T ri is the remaining time of task for platform i, indicating the remaining time to complete the task. The smaller this value, the more urgent the task and the need to complete it as soon as possible. The influence of the remaining time of the task on task priority is positive: the less the remaining time of the task, the higher the priority evaluation value Pr i the higher, which means that the platform will give priority to tasks with less remaining time to ensure the timely completion of the tasks.

[0132] Task priority is a comprehensive evaluation of difficulty and remaining time: this formula determines the task priority by adding the task difficulty D i and the remaining time T ri and using their reciprocals. In this way, tasks with high priority should be tasks with moderate difficulty and urgent remaining time. The significance of the priority evaluation formula: Since the formula is a reciprocal relationship, lower task difficulty and shorter remaining task time will result in higher priority. The higher the priority of the task, the more inclined the platform is to give priority to processing this task.

[0133] D i Its impact on task priority is negative, that is, the more difficult the task, the lower the priority. This can prevent the platform from being too eager to process high-difficulty tasks and reduce unreasonable priorities in task allocation.

[0134] For complex tasks, the platform will be more inclined to wait for the right time, or perform more collaboration and resource scheduling during execution to reduce the complexity of task execution.

[0135] T ri Its impact on priority evaluation is positive. Tasks with shorter remaining time will be given higher priorities. This is because when the remaining time of a task is short, more urgent resource scheduling and task arrangement are needed to ensure the task is completed on time.

[0136] If the remaining time of a task is long, the platform can appropriately postpone its execution and give priority to those tasks with more urgent time until the remaining time of the task becomes tight.

[0137] By calculating Pr i , the platform can reasonably allocate time and resources according to the difficulty and urgency of tasks. For example:

[0138] For a task with a little remaining time but moderate difficulty, the platform will assign it a higher priority, so it will be executed first.

[0139] For a task with high difficulty but sufficient remaining time, the platform will assign a lower priority to this task and allow other tasks to be executed first until the remaining time of the task becomes tight.

[0140] The advantage of this priority mechanism is to dynamically balance the difficulty and urgency of tasks, ensure that the platform makes reasonable decisions among multiple tasks, and improve the efficiency and coordination of task execution.

[0141] Suppose platform i faces two tasks:

[0142] Task 1: Task difficulty D 1 = 5, remaining time T r1 = 2 hours, Task 2: Task difficulty D 2 = 3, remaining time T r2 = 1 hour. Then Pr 1 ≈0.1429, Pr 2 ≈0.25. In this case, since Task 2 has a shorter remaining time, its priority Pr 2 is higher, so the platform will execute Task 2 first.

[0143] The present invention dynamically determines the priority of tasks by comprehensively considering the difficulty and remaining time of the tasks. This mechanism ensures that the platform can prioritize the processing of urgent and moderately difficult tasks, improving the flexibility and efficiency of task execution. At the same time, it also avoids resource waste and task delay problems caused by overly difficult or time-consuming tasks.

[0144] Step 203: Perform task allocation through a distributed negotiation mechanism, and predict the task allocation recommendation value of the first platform and the second platform in the next negotiation round of the current negotiation round.

[0145] In some embodiments, step 203 may include:

[0146] Obtain the task priority evaluation value, trust weight, and task completion ability evaluation value between the first platform and the second platform;

[0147] Determine the first task allocation recommendation value of the first platform and the second platform in the current negotiation round according to the task priority evaluation value, trust weight, and task completion ability evaluation value between the first platform and the second platform;

[0148] Obtain the second task allocation recommendation value of the first platform and all its neighbor platforms in the current negotiation round;

[0149] Predict the task allocation recommendation value of the first platform and the second platform in the next negotiation round of the current negotiation round according to the first task allocation recommendation value and the second task allocation recommendation value.

[0150] In some embodiments, the task allocation recommendation value can be expressed as:

[0151] S ij =Pr i ·ω ij ·c ij ;

[0152] where S ij is the task allocation recommendation value between the i-th platform and the j-th platform, ω ij is the trust weight between the i-th platform and the j-th platform, and c ij is the task completion ability evaluation value between the i-th platform and the j-th platform.

[0153] In a specific implementation, Pr i represents the priority of platform i in task allocation, which is calculated from the task difficulty D i and the remaining task time T ri of platform i. Tasks with higher priority are usually more likely to be executed by platform i. Therefore, the task priority Pr iReflects the urgency of task execution and the adaptability of the platform to the task.

[0154] ω ij Represents the trust weight of platform i in platform j for executing task j. The trust weight measures the degree of trust of platform i in platform j for completing the task. The level of the trust weight may be determined by the following factors:

[0155] Historical performance: How platform j performed in past tasks, whether the tasks were completed on time, and the quality of task completion.

[0156] Platform performance: Whether the hardware and software performance of platform j are sufficient to undertake task execution.

[0157] Current status: Whether the current resource status of platform j (such as battery power, sensor function, network connection status, etc.) supports task execution.

[0158] The higher the trust value, the more inclined platform i is to assign tasks to platform j. If the trust is low, platform i may choose other platforms or request platform j to provide more information to increase the trust level.

[0159] c ij Represents the ability evaluation value of platform i for platform j to complete task j. This evaluation value is based on various characteristics of platform j and determines the ability of platform j in executing this task.

[0160] The task completion ability evaluation value usually considers the following factors:

[0161] Platform performance: Whether the hardware capabilities of platform j, such as processor speed, sensor accuracy, etc., meet the task requirements.

[0162] Platform status: Whether the current status of platform j, such as battery power, status stability, etc., is suitable for task completion.

[0163] Task matching degree: Whether platform j has the ability to complete this specific task. For example, drones are suitable for executing aerial tasks, and unmanned boats are suitable for executing underwater tasks, etc.

[0164] The stronger the task completion ability of c ij The larger the value, the more inclined platform i will be to assign tasks to platform j.

[0165] S ij The larger the value of S, the more inclined platform i is to assign tasks to platform j. If the value of S ij is small, platform i may choose to assign the task to other platforms or request platform j to provide more information or improve the status.

[0166] In summary, S ijIt reflects the suggestion of platform i for platform j to execute task j, integrating factors such as task priority, trust weight, and task completion ability assessment. This suggested value helps the platform make decisions in task allocation, ensuring that tasks are reasonably and efficiently allocated to the most suitable platform.

[0167] In some embodiments, the task allocation suggested value of the first platform and the second platform in the next negotiation round is expressed as:

[0168]

[0169] Where is the task allocation suggested value between the i-th platform and the j-th platform in the (t + 1)-th round, is the first task allocation suggested value between the i-th platform and the j-th platform in the t-th round, t is the negotiation round, N i is the set of neighbor platforms of the i-th platform, k is the platform number, a ik is the negotiation weight between the i-th platform and the j-th platform, is the second task allocation suggested value between the k-th platform and the j-th platform in the t-th round.

[0170] In specific implementation, during the negotiation process, platform i will continuously update the suggested value for platform j to execute the task by exchanging information with other platforms (neighbor platforms). Each round of negotiation will adjust the task allocation suggested value S ij of platform i, so as to be closer to a final consensus.

[0171] represents the task allocation suggested value of platform i for platform j at the (t + 1)-th round. This value is the result of platform i updating based on the suggested value in the current round and the suggested values of other neighbor platforms.

[0172] This term represents that platform i updates the task allocation suggested value through negotiation with all neighbor platforms. Specifically: is the difference between the task allocation suggested value of platform k for platform j and the task allocation suggested value of platform i for platform j. If the suggestion of platform k for the task is higher than that of platform i, then platform i will consider raising its own suggested value.

[0173] a ik plays a role in determining whether platform i adopts the suggestion of platform k in this formula. The higher the trust level or negotiation weight, the more inclined platform i is to accept the task allocation suggestion of platform k, and thus adjust its own task allocation suggested value.

[0174] If a ikLarger, indicating that platform i highly trusts platform k, so platform i is more inclined to adjust the task assignment value according to the suggestions of platform k.

[0175] If a ik is smaller, the suggestions of platform k will have less influence on the task assignment decision of platform i.

[0176] The task assignment suggestion value of platform i is not only affected by factors such as its own task priority and ability assessment, but also by the neighboring platforms it negotiates with. By exchanging information and negotiating with multiple neighboring platforms, platform i can gradually correct its task assignment suggestion value until multiple platforms reach an agreement.

[0177] The negotiation process gradually approaches a final consensus through multiple rounds of updates. In each round of negotiation, platform i will update according to the suggestion value of the current round and the opinions of neighboring platforms, gradually adjusting its task assignment suggestion value until after a certain number of rounds, the platforms reach an agreement and the task assignment result is finally determined.

[0178] Through multiple rounds of negotiation, platform i will gradually accept the suggestions of more neighboring platforms, making the task assignment result more universal and reasonable. This process helps to resolve the differences in task assignment, enabling multiple platforms to reach a consistent decision and ensuring the efficient completion of tasks.

[0179] The negotiation process can dynamically adjust the task assignment strategy according to the actual situation of the platform. For example, platform i may propose a preliminary task assignment suggestion at the beginning, and through multiple rounds of negotiation, it will gradually correct and improve this suggestion according to the feedback of neighboring platforms, ultimately achieving a better task assignment.

[0180] Multi-platform negotiation can avoid the inefficiency caused by resource competition or task assignment conflicts among multiple platforms. Through reasonable negotiation and update of task assignment suggestions, platforms can coordinate resources and optimize the task execution order in cooperation.

[0181] The influence of the degree of trust of each platform in other platforms during the negotiation process on task assignment helps to promote cooperation and mutual trust among platforms. This cooperation is not only reflected in task assignment but also helps platforms better coordinate resources and share information during task execution.

[0182] In summary, through continuous information exchange with neighboring platforms and adjustment of suggestion values, the platforms can finally reach a consistent task assignment decision, thereby optimizing the task execution efficiency and resource utilization.

[0183] Step 204: Perform path planning on the first platform and the second platform based on an improved potential field method, and determine the planned paths of the first platform and the second platform.

[0184] In some embodiments, step 204 may include:

[0185] For the first platform and the second platform, construct an attractive potential field that causes the platform to move towards the target point according to the coordinates of the current position and the target position of the platform;

[0186] Construct a repulsive potential field that causes the platform to move away from the obstacle according to the current position of the platform and the obstacle position of the obstacle;

[0187] Construct a potential field function that guides the platform to move towards the target point and avoids collisions with the obstacle according to the attractive potential field and the repulsive potential field;

[0188] Obtain the gradient of the potential field function, and determine the speed of the platform according to the gradient of the potential field function;

[0189] Determine the planned path for the platform to move towards the target point at the speed and avoid collisions with the obstacle according to the potential field function and the speed of the platform.

[0190] In some embodiments, the potential field function can be expressed as:

[0191] U(P) = U att (P) + U rep (P);

[0192] Wherein, U(P) is the potential field function, U att (P) is the attractive potential field that guides the platform towards the target, U rep (P) is the repulsive potential field that causes the platform to move away from the obstacle, K att is the attractive potential field coefficient, G is the target position, K rep is the repulsive potential field coefficient, r 0 is the safety distance.

[0193] In specific implementation, U(P) synthesizes the attraction of the platform to the target point and the repulsion of the platform from the obstacle. U att (P) is used to guide the platform to move towards the target point G and avoid the platform from colliding with the obstacle O.

[0194] K att controls the magnitude of the attraction of the platform to the target point. The larger the coefficient, the stronger the platform is attracted by the target. P = (x, y, z) is the current position of the platform, usually three-dimensional coordinates. G = (g x , g y , g z) are the coordinates of the target position. ||P - G|| is the Euclidean distance between the current position P of the platform and the target position G. The attractive potential field gradually weakens as the distance between the platform and the target position G decreases, thus guiding the platform towards the target point. The attractive potential field is a quadratic function, and its value increases as the distance between the platform and the target increases, resulting in an increasingly strong attractive force on the platform.

[0195] U rep (P) is a function used to avoid the platform from colliding with obstacles. The closer the obstacle is to the platform, the greater the value of the repulsive potential field, pushing the platform away from the obstacle. K rep is the repulsive potential field coefficient. The larger the coefficient, the more strongly the platform will avoid the obstacle. O = (O x , O y , O z ) is the position of the obstacle.

[0196] ||P - O|| is the Euclidean distance between the platform and the obstacle O. r 0 is the safety distance. If the distance between the platform and the obstacle is less than this value, the influence of the repulsive potential field will become very strong.

[0197] When the distance ||P - O|| between the platform and the obstacle is less than r 0 , the influence of the repulsive potential field will increase significantly, prompting the platform to move away from the obstacle to avoid collision. The repulsive potential field is non - linear. When the platform approaches the obstacle, the value of the potential field increases sharply, thus generating a strong repulsive force.

[0198] It can be understood that by optimizing this potential field function, the platform can obtain a suitable movement direction, which can both guide the platform towards the target point and avoid colliding with obstacles.

[0199] In some embodiments, the velocity of the first platform can be expressed as:

[0200]

[0201] where, V i is the velocity of the i - th platform, η is the velocity adjustment coefficient, is the gradient of the potential field function.

[0202] In specific implementation, η is used to control the velocity of the platform's movement. It indicates that the platform needs to move along this direction. The attractive potential field ensures that the platform moves towards the target point, helping the platform approach the task area or measurement target. The repulsive potential field ensures that the platform avoids colliding with obstacles. It is particularly important for complex environments and can effectively prevent the platform from colliding with underwater or surface obstacles. The platform calculates its motion trajectory according to the comprehensive potential field function U(P) and achieves the dual goals of target guidance and obstacle avoidance by adjusting its position and speed.

[0203] In summary, the potential field function of the present invention guides the platform to perform path planning and obstacle avoidance through the combination of the attractive potential field and the repulsive potential field. The attractive potential field guides the platform to move towards the target, while the repulsive potential field ensures that the platform stays away from obstacles. By optimizing this comprehensive potential field function, the platform can safely and effectively complete tasks in a dynamic environment.

[0204] Step 205: Simulate the measurement task based on the planned paths of the first platform and the second platform, and enable the first platform and the second platform to coordinate and share resources through the distributed resource sharing protocol, determine the resource sharing ratio and the updated resource amount of the first platform, and complete the measurement task planning for the to-be-measured ocean area.

[0205] In some embodiments, step 205 may include:

[0206] Obtain the cooperation information between the first platform and the second platform; the cooperation information includes the degree of trust, resource status, and the importance of historical cooperation tasks between the first platform and the second platform;

[0207] Determine the resource sharing ratio between the first platform and the second platform according to the cooperation information between the first platform and the second platform.

[0208] In some embodiments, the updated resource amount of the first platform is determined through the following steps:

[0209] Obtain the current resource amount of the first platform and the resource demand of the first platform;

[0210] Determine the resource sharing amount between the first platform and the second platform according to the resource sharing ratio between the first platform and the second platform, and the current resource amount and resource demand of the first platform;

[0211] Update the current resource amount of the first platform according to the resource sharing amount between the first platform and the second platform to obtain the updated resource amount of the first platform.

[0212] In some embodiments, the resource sharing amount between the first platform and the second platform can be expressed as:

[0213] R sij = m ij (R i - R di );

[0214] Wherein, R sij is the resource sharing amount between the i-th platform and the j-th platform, and m ij is the resource sharing ratio of the i-th platform to the j-th platform, R i is the resource amount of the i-th platform, and R di is the resource demand amount of the i-th platform.

[0215] In specific implementation, R i represents the total amount of resources currently owned by platform i. This resource amount can be resources in multiple aspects. For example:

[0216] Electricity (platform movement, running sensors, etc. consume electrical energy).

[0217] Storage space (the platform needs to store the acquired data or intermediate results).

[0218] Computing power (the processing power of the platform, which determines how much data it can process and how many tasks it can run).

[0219] Communication bandwidth (the information transmission ability between platforms). R i is the sum of all resources relied on by platform i to complete the task.

[0220] R i is the sum of all resources relied on by platform i to complete the task.

[0221] R di is the amount of resources required by platform i to complete the current task. Usually, the resource demand amount of the platform is closely related to factors such as the complexity of the task, the required data processing amount, and the execution time.

[0222] If the resource demand amount of platform i is greater than its available resource amount, platform i needs to request resource sharing from other platforms or obtain additional resources through negotiation.

[0223] m ij is the resource sharing ratio of platform i to platform j, which represents the degree to which platform i shares its resources with platform j. This ratio is usually a value between 0 and 1, which determines whether platform i is willing to provide its remaining resources to platform j.

[0224] m ij The value of m is usually determined by the following factors:

[0225] Degree of trust between platforms: If platform i has full trust in platform j, it may be willing to share more resources.

[0226] Current resource status of the platform: If platform i has sufficient resources, it may be willing to share more resources; if resources are scarce, the sharing ratio will be lower.

[0227] Cooperation relationship between platforms: The cooperation history between platforms and the importance of tasks will also affect the resource sharing ratio.

[0228] R i -R di represents the remaining resource amount of platform i. If the resource demand of platform i is small, i.e., R i -R di is large, then platform i will have more resources for sharing. If the resource demand is large, i.e., R i -R di is small, then the amount of shared resources of platform i will decrease.

[0229] m ij represents the ratio of platform i's willingness to share its remaining resources with platform j. The larger the ratio, the more resources platform i provides to platform j.

[0230] In multi-platform collaborative tasks, resources are often limited. Therefore, reasonable resource sharing can ensure that each platform can efficiently complete tasks. If a certain platform has surplus resources while another platform has insufficient resources, then through resource sharing, the overall utilization efficiency of resources will be improved.

[0231] The resource sharing mechanism encourages cooperation between platforms. For example, platform i may share its remaining power or computing power with platform j to help platform j complete tasks, especially in the case of high-load tasks or emergency tasks.

[0232] Through resource sharing, platforms can complement each other's resources to ensure that each platform is not restricted by insufficient resources when executing tasks. For example, a drone may need to request data storage resources from an unmanned boat during a task execution, or an unmanned boat may need to obtain computing power or power from a drone.

[0233] During task execution, resources may become scarce or insufficient due to various reasons (such as equipment failures, climate mutations, etc.). Through resource sharing, platforms can quickly adapt to changes and ensure that tasks are successfully completed among different platforms.

[0234] The resource sharing ratio m ijEmphasizes the trust and cooperation among platforms. When platform i has trust in platform j, it will provide more resources; conversely, platform j may not be able to obtain sufficient resources. Therefore, the trust mechanism and reasonable negotiation are crucial for successful resource sharing.

[0235] For example only, assume there are two platforms i and j, the resource quantity R of platform i i = 100 units, the resource demand quantity R di = 60 units, the remaining resource quantity R i -R di = 40 units, while the resource demand quantity R of platform j dj = 30 units, assume the resource sharing ratio m of platform i to platform j ij = 0.5.

[0236] Then, the resource quantity R shared by platform i to platform j sij is:

[0237] R sij = 0.5·(100 - 60) = 0.5·40 = 20 units.

[0238] Therefore, platform i will share 20 units of resources to platform j to help platform j complete the task.

[0239] Through the above method, the platform of the present invention can reasonably allocate resources according to its own remaining resources and the demand of other platforms. This mechanism optimizes the utilization efficiency of resources and realizes effective resource support and cooperation in multi-platform collaborative tasks, ensuring the efficient and smooth completion of tasks.

[0240] In some embodiments, the updated resource quantity of the first platform can be expressed as:

[0241]

[0242] Wherein, is the updated resource quantity of the i-th platform, R i is the resource quantity of the i-th platform, N i is the set of neighbor platforms of the i-th platform, R sij is the resource sharing quantity between the i-th platform and the j-th platform.

[0243] In specific implementation, R i represents the total amount of resources currently owned by platform i. These resources can be various types of resources (such as power, storage space, computing power, etc.). This value reflects the resource reserve of the platform when performing tasks.

[0244] R sijis the amount of resources shared by platform i with its neighbor platform j. This shared amount is based on the remaining resources R of platform i i -R di and the trust weight m of platform i towards platform j ij calculated. For example, if the resource demand of platform i is not large, it will have more remaining resources to share with other platforms, and vice versa.

[0245] N i is the set of neighbor platforms of platform i, representing other platforms that have a resource sharing relationship with platform i. Resource sharing is not limited to just one neighbor platform but may involve collaboration with multiple platforms. The resource sharing amount is an accumulative process, and platform i will share resources with all platforms j in its neighbor set.

[0246] represents the updated resource amount of platform i after resource sharing with its neighbor platforms. Since platform i has shared a portion of its resources with other platforms, its updated resource amount is its current resource amount minus the total sum of all shared resources.

[0247] calculates the total amount of resources shared by platform i with all its neighbor platforms j. Assuming platform i shares resource R with each platform j in the neighbor platform set sij , then the updated resource amount of platform i is obtained by subtracting all the shared resource amounts from the current resource amount of platform i. The specific calculation process is to accumulate the shared amount R sij for each platform j and then deduct it from the resource amount of platform i.

[0248] This formula reflects the dynamic adjustment of resources among multiple platforms. When platform i is executing a task and has remaining resources, it will share resources with neighbor platforms according to the demand. After sharing resources with other platforms, its resource amount will decrease, thus obtaining the updated resource amount.

[0249] When multiple platforms jointly complete a task, resource sharing is a way to promote collaboration among platforms. If platform i has sufficient resources while platform j is resource-constrained, platform i can help platform j complete the task by sharing resources.

[0250] By calculating R sij , platform i and platform j can reasonably allocate resources according to their respective resource statuses to enable the task to be completed more efficiently. This formula ensures the reasonable allocation of resources. If platform i has more remaining resources R i -R di is larger, it can provide more resources for other platforms; conversely, it may need to obtain resources from other platforms. In this way, the resources within the system are optimally utilized.

[0251] R sij affected by the trust weight m ij . If platform i has more trust in platform j, it will share more resources. Therefore, the cooperation and trust mechanism between platforms will directly affect the efficiency of resource sharing.

[0252] When multiple platforms jointly complete complex tasks, resource sharing helps to balance the resource status of each platform and ensure that the tasks are not affected by the lack of resources of a single platform. Especially in some urgent or high-load tasks, resource sharing can alleviate the bottlenecks that may occur during task execution.

[0253] Suppose platform i has 100 units of resources, and the current task requires 60 units of resources. So the remaining resource amount of platform i is 40 units. If platform i shares resources with platform j and platform k, and the sharing amounts are respectively:

[0254] R sij = 15 units, the resources shared by platform i with platform j, R sik = 10 units, the resources shared by platform i with platform k. units. Therefore, platform i shares 25 units of resources with its neighbor platforms j and k, and the updated resource amount is 75 units.

[0255] In summary, the platform of the present invention can help other platforms complete tasks smoothly while maintaining its own resource balance through reasonable resource sharing. Through this mechanism, multiple platforms can work together effectively to achieve efficient task completion.

[0256] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of an ocean measurement task planning system based on distributed cooperative control provided by the present invention.

[0257] As Figure 3 shown, an ocean measurement task planning system based on distributed cooperative control proposed in an embodiment of the present invention includes:

[0258] An information transmission module 301, configured to sense the environmental information of the ocean area to be measured through multiple sensors and share it among the platforms in the distributed cooperative control, and determine the information transmission amount from the first platform to the second platform;

[0259] A task evaluation module 302, configured to evaluate the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information;

[0260] The task allocation module 303 is used to perform task allocation through a distributed negotiation mechanism, and predict the task allocation proposed values of the first platform and the second platform in the next negotiation round of the current negotiation round;

[0261] The path planning module 304 is used to perform path planning on the first platform and the second platform based on an improved algorithm of the potential field method, and determine the planned paths of the first platform and the second platform;

[0262] The resource sharing module 305 is used to simulate measurement tasks based on the planned paths of the first platform and the second platform, and enable the first platform and the second platform to perform resource coordinated sharing through a distributed resource sharing protocol, determine the resource sharing ratio and the updated resource amount of the first platform, and complete the measurement task planning for the to-be-measured ocean area.

[0263] Please refer to Figure 4 , Figure 4 which is a schematic diagram of an embodiment of the electronic device provided by an embodiment of the present invention. As Figure 4 shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored on the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0264] Perceive the environmental information of the to-be-measured ocean area through multiple sensors and share it among the platforms under distributed collaborative control, and determine the information transmission amount from the first platform to the second platform;

[0265] Evaluate the difficulty and priority of each measurement task for the to-be-measured ocean area based on the environmental information;

[0266] Perform task allocation through a distributed negotiation mechanism, and predict the task allocation proposed values of the first platform and the second platform in the next negotiation round of the current negotiation round;

[0267] Perform path planning on the first platform and the second platform based on an improved algorithm of the potential field method, and determine the planned paths of the first platform and the second platform;

[0268] Simulate measurement tasks based on the planned paths of the first platform and the second platform, and enable the first platform and the second platform to perform resource coordinated sharing through a distributed resource sharing protocol, determine the resource sharing ratio and the updated resource amount of the first platform, and complete the measurement task planning for the to-be-measured ocean area.

[0269] Please refer to Figure 5 , Figure 5 which is a schematic diagram of an embodiment of a computer-readable storage medium provided by an embodiment of the present invention. AsFigure 5 As shown in the figure, this embodiment provides a computer-readable storage medium 500, on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented:

[0270] Perceive the environmental information of the ocean area to be measured through multiple sensors and share it among the platforms with distributed collaborative control, and determine the information transmission volume from the first platform to the second platform;

[0271] Evaluate the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information;

[0272] Perform task allocation through a distributed negotiation mechanism, and predict the task allocation proposed value of the first platform and the second platform in the next negotiation round of the current negotiation round;

[0273] Perform path planning for the first platform and the second platform based on an improved algorithm of the potential field method, and determine the planned paths of the first platform and the second platform;

[0274] Simulate the measurement tasks based on the planned paths of the first platform and the second platform, and enable the first platform and the second platform to perform resource coordination and sharing through a distributed resource sharing protocol, determine the resource sharing ratio and the updated resource volume of the first platform, and complete the measurement task planning for the ocean area to be measured.

[0275] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0276] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0277] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and combinations of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device generate a system for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0278] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including an instruction system that implements the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0279] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0280] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0281] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for planning oceanographic survey tasks based on distributed collaborative control, characterized in that: The method comprises: The environmental information of the ocean area to be measured is sensed by a variety of sensors and shared among the platforms of distributed collaborative control to determine the amount of information transmitted from the first platform to the second platform; Evaluate the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information; Performing task allocation through a distributed negotiation mechanism, predicting a recommended value of task allocation between the first platform and the second platform in the next negotiation round of the current negotiation round; Performing path planning for the first platform and the second platform based on an improved algorithm of the potential field method to determine the planned paths of the first platform and the second platform; The measurement task is simulated based on the planned paths of the first platform and the second platform, and the first platform and the second platform coordinate and share resources through a distributed resource sharing protocol, the resource sharing ratio and the updated resource amount of the first platform are determined, and the measurement task planning for the ocean area to be measured is completed.

2. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 1 is characterized in that: The environmental information of the ocean area to be measured is sensed by multiple sensors and shared among the platforms of distributed collaborative control to determine the amount of information transmission from the first platform to the second platform, including: Acquiring the position, oceanographic meteorological data, obstacle information and measurement mission area information acquired by the first platform, and the speed of the first platform; Performing weighted processing on the position, oceanographic meteorological data, obstacle information and measurement mission area information obtained by the first platform, and the speed of the first platform to obtain an information weighting function; Acquire a distance between the first platform and the second platform, and a first constant representing a communication range and a signal attenuation; constructing an information attenuation factor according to the distance between the first platform and the second platform and the first constant; An amount of information transmitted from the first platform to the second platform is determined according to the information weighting function and the information attenuation factor.

3. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 2 is characterized in that: The amount of information transmitted from the first platform to the second platform is expressed as: Among them, I ij is the amount of information transmitted from the ith platform to the jth platform, the ith platform represents the first platform, the jth platform represents the second platform, P i =(x i ,y i ,z i ) is the position obtained by the ith platform, V i is the speed of the ith platform, M i =(t i ,w i ,p i ) is the ocean meteorological data obtained by the ith platform, t i is the temperature, w i is the wind speed, p i is the air pressure, O i is the obstacle information obtained by the ith platform, A is the measurement task area information obtained by the ith platform, and d ij is the distance from the ith platform to the jth platform, k is the first constant related to the communication range and signal attenuation, f(P i ,V i ,M i ,O i ,A) is the information weighting function, is the information decay factor.

4. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 3 is characterized in that: The difficulty and priority of each measurement task of the to-be-measured ocean area is evaluated based on the environmental information, including: Obtaining reference meteorological conditions of the ocean area to be measured and obstacle positions of various obstacles; Calculating a first distance between the position of the first platform and the obstacle positions of all obstacles; Calculate the difference between current marine meteorological data and reference meteorological conditions; Calculating a second distance between the position of the first platform and the target point in the measurement task area information; Determining a task difficulty assessment value for assessing the difficulty of each measurement task of the ocean area to be measured according to the gap, the first distance, and the second distance; The remaining task time of the measurement task is obtained, and the priority of the measurement task is determined based on the remaining task time and the task difficulty evaluation value of the measurement task.

5. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 4 is characterized in that: The task difficulty evaluation value and the task priority evaluation value are expressed as: Among them, D i is the task difficulty evaluation value, α, β, γ are the first weight, the second weight, and the third weight respectively, M ref It is the reference meteorological conditions; Among them, Pr i is the task priority evaluation value, T ri is the remaining time of the task.

6. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 5 is characterized in that: The performing task allocation by the distributed negotiation mechanism and predicting the task allocation suggestion value between the first platform and the second platform in the next negotiation round of the current negotiation round includes: Obtaining a task priority evaluation value, a trust weight, and a task completion capability evaluation value between the first platform and the second platform; Determine a first task allocation recommendation value between the first platform and the second platform in a current negotiation round according to a task priority evaluation value, a trust weight, and a task completion capability evaluation value between the first platform and the second platform; Obtaining a second task allocation suggestion value between the first platform and all its neighboring platforms in the current negotiation round; According to the first task allocation suggestion value and the second task allocation suggestion value, a task allocation suggestion value between the first platform and the second platform in the next negotiation round of the current negotiation round is predicted.

7. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 6 is characterized in that: The improved algorithm based on the potential field method performs path planning on the first platform and the second platform to determine the planned paths of the first platform and the second platform, including: For the first platform and the second platform, constructing an attractive potential field that causes the platform to move toward the target point according to the coordinates of the current position of the platform and the target position; According to the current position of the platform and the obstacle position of the obstacle, constructing a repulsive potential field for making the platform stay away from the obstacle; According to the attractive potential field and the repulsive potential field, construct a potential field function for guiding the platform to move toward the target point and avoid collision with the obstacle; Obtaining the gradient of the potential field function, and determining the velocity of the platform according to the gradient of the potential field function; The planned path is determined according to the potential field function and the speed of the platform, in which the platform moves toward the target point at the speed and avoids collision with the obstacle.

8. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 7 is characterized in that: The step of enabling the first platform and the second platform to coordinate and share resources through a distributed resource sharing protocol and determining a resource sharing ratio includes: Acquire cooperation information between the first platform and the second platform; the cooperation information includes the degree of trust, resource status, and importance of historical cooperation tasks between the first platform and the second platform; According to the cooperation information between the first platform and the second platform, a resource sharing ratio between the first platform and the second platform is determined.

9. The method for planning oceanographic survey tasks based on distributed collaborative control according to claim 8, characterized in that: The updated resource amount of the first platform is determined by the following steps: Obtaining the amount of resources currently owned by the first platform and the amount of resources required by the first platform; Determine the resource sharing amount between the first platform and the second platform according to the resource sharing ratio between the first platform and the second platform, and the resource amount and resource demand currently owned by the first platform; The resource amount currently owned by the first platform is updated according to the resource sharing amount between the first platform and the second platform to obtain the updated resource amount of the first platform.

10. A marine survey task planning system based on distributed collaborative control, characterized in that: The system comprises: An information transmission module, used to sense environmental information of the ocean area to be measured through a variety of sensors and share it among the platforms of distributed collaborative control, and determine the amount of information transmitted from the first platform to the second platform; A task evaluation module, used for evaluating the difficulty and priority of each measurement task for the ocean area to be measured based on the environmental information; A task allocation module, used to perform task allocation through a distributed negotiation mechanism, and predict a recommended value of task allocation between the first platform and the second platform in the next negotiation round of the current negotiation round; A path planning module, used to perform path planning for the first platform and the second platform based on an improved algorithm of a potential field method, and determine the planned paths of the first platform and the second platform; The resource sharing module is used to simulate the measurement task based on the planned paths of the first platform and the second platform, and coordinate and share resources between the first platform and the second platform through a distributed resource sharing protocol, determine the resource sharing ratio and the updated resource amount of the first platform, and complete the measurement task planning for the ocean area to be measured.

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