Collaborative optimization method and device for ship task operation and electronic equipment

Abstract

The invention discloses a collaborative optimization method and device for ship task operation and electronic equipment, and belongs to the technical field of ship control. The method comprises the steps of obtaining an operation task of a ship; based on the operation environment information of the ship and the working characteristics of sailors, task demands of operation tasks are subjected to collaborative analysis, a multi-person-machine-ring collaborative model is constructed, and the task demands comprise a visual task demand, an auditory task demand, a cognitive task demand and a motion task demand; the task execution process of the operation task is simulated through a multi-person-machine-ring collaborative model, a simulation result is obtained, and the simulation result comprises task resources of the operation task and collaborative operation efficiency among sailors, equipment and the environment in a ship; and according to the task resources and the collaborative operation efficiency, the collaborative relationship of each element in the simulation result is optimized, and the elements comprise sailors, equipment and environments corresponding to the operation tasks. According to the method, the overall operation efficiency of the task is improved.

Description

Technical Field

[0001] This application belongs to the field of ship control technology, and in particular relates to a collaborative optimization method, device and electronic equipment for ship mission operations. Background Technology

[0002] During ship operation and work, crew members in long-term confined environments face unique work and living challenges, requiring efficient and reliable collaboration between personnel, equipment, and the environment to ensure the successful completion of tasks and the physical and mental health of personnel.

[0003] In traditional ship operation systems, the coordination between crew, equipment, and the environment is often isolated, which can lead to a lack of coordination and synchronization in resource allocation, crew operations, and equipment responses during mission execution, resulting in low overall operational efficiency.

[0004] Therefore, in order to improve the overall operational efficiency of the mission, there is an urgent need for a collaborative optimization method for ship mission operations. Summary of the Invention

[0005] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a collaborative optimization method, apparatus, and electronic equipment for ship mission operations, thereby improving the overall operational efficiency of the mission.

[0006] Firstly, this application provides a collaborative optimization method for ship mission operations, the method comprising: Obtain the operational tasks of the ships; Based on the ship's operating environment information and the crew's work characteristics, the task requirements of the operation are analyzed collaboratively to construct a multi-person-machine-environment collaborative model. The task requirements include visual task requirements, auditory task requirements, cognitive task requirements, and kinematic task requirements. The task execution process of the operation is simulated using the multi-person-machine-environment collaborative model, and the simulation results are obtained. The simulation results include the task resources of the operation and the collaborative operation efficiency between the crew, equipment and environment in the ship. Based on the task resources and the collaborative operation efficiency, the collaborative relationship of each element in the simulation results is optimized. The elements include the crew, equipment, and environment corresponding to the operation task.

[0007] According to one embodiment of this application, the step of collaboratively analyzing the task requirements of the operational task based on the ship's operational environment information and the crew's work characteristics, and constructing a multi-person-machine-environment collaborative model, includes: Based on the crew operation tasks, equipment operation tasks, and environmental requirements in the operation task, the operation task is decomposed into multiple sub-tasks. The crew operation tasks refer to the operational activities that the crew needs to perform manually in the task execution process. The equipment operation tasks are the operations that the equipment on the ship needs to perform according to the operation task. The environmental requirements are the specific environmental conditions required when the operation task is executed, including the human environment and the physical environment. By comparing and analyzing the work characteristics of the crew members with the task requirements of the sub-tasks, the crew members' ability to perform each sub-task is determined. Based on the execution capability and the work environment information, each element in the work task is configured collaboratively to determine the niche of the element. The niche is the position and role of the element in the multi-person-machine-environment collaborative model, as well as the way and scope of its interaction with other elements. Based on the dependencies and priorities among the multiple subtasks, the niche of the elements is adjusted to construct the multi-person-machine-ring collaborative model.

[0008] According to one embodiment of this application, the operating environment information includes equipment status and environmental parameters. The step of coordinating the configuration of each element in the task based on the execution capability and the operating environment information to determine the niche of the element includes: Based on the equipment status and the environmental parameters, the operating requirements and performance limitations of the equipment are determined. The equipment status refers to the operating condition and performance of the equipment, including equipment availability, fault status, and performance indicators. The environmental parameters are environmental parameters that affect the execution of the task, including the natural environment and the electromagnetic environment. Based on the execution capability, determine the operating equipment, operating position, and work scope corresponding to each crew member; Based on the operational requirements, performance limitations, operating equipment, operating location, and work scope, determine the working rhythm and interaction frequency of the crew, the equipment, and the environment; Based on the working rhythm and the interaction frequency, the interaction relationships and energy flow patterns between the elements are analyzed to determine the ecological niche of each element.

[0009] According to one embodiment of this application, adjusting the niche of the elements based on the dependencies and priorities among the plurality of subtasks to construct the multi-user-machine-ring collaborative model includes: Based on the dependencies and priorities, determine the execution order and time constraints of each subtask; Based on the execution order and time constraints, an execution time window is allocated to each of the subtasks; Determine the crew's operating authority over specific equipment based on their performance capabilities and mission requirements; Based on the execution time window, the ship's resource limitations, and the operation permissions, resources are allocated to each subtask, and the subtasks are assigned to crew members with the corresponding permissions to obtain an allocation scheme. Obtain and analyze the execution feedback information corresponding to the allocation scheme, determine the element tasks and interaction methods of the element, and adjust the ecological niche of the element, the workload of the crew, and the operating parameters of the equipment; Based on the element tasks, the interaction methods, and the ecological niche, the multi-person-machine-environment collaborative model is constructed.

[0010] According to one embodiment of this application, the step of simulating the task execution process of the job task through the multi-person-machine-environment collaborative model and obtaining simulation results includes: The multi-person-machine-environment collaborative model is used to simulate the task execution process of the job, which includes multiple job stages. Based on the importance of task requirements in the aforementioned work process and the weight of resources in the task execution process, the task resources called in the task execution process are divided into resource units. The categories of resource units include key resources, auxiliary resources, and alternative resources. Based on the task execution process, a multi-level model is constructed according to the importance of the resource units, task dependencies, and dynamic scheduling requirements. Based on the multi-level model, the task resources are configured and scheduled to simulate the task execution process of the job. Based on the resource utilization information and task completion information of the simulated mission execution process, the collaborative operation efficiency between the crew, equipment and environment on the ship is calculated as the simulation result.

[0011] According to one embodiment of this application, calculating the collaborative operational efficiency between the crew, equipment, and environment of the ship based on resource utilization information and task completion information from the simulated task execution process includes: Obtain the first resource utilization information and the first task completion information of the resource unit corresponding to each of the aforementioned work stages; Based on the first resource utilization information and the first task completion information, the load balance status of the resource unit is determined to calculate the resource utilization rate. Based on the time constraints of the aforementioned work process, and with the goal of maximizing resource utilization, the task resources are reconfigured and scheduled until the load balance state reaches a preset balance threshold, thereby obtaining optimized second resource utilization information and second task completion information. The collaborative operation efficiency is calculated based on the second resource utilization information and the second task completion information.

[0012] According to one embodiment of this application, optimizing the collaborative relationship of each element in the simulation result based on the task resources and the collaborative operation efficiency includes: Based on the aforementioned collaborative operation efficiency analysis, the efficiency change trend among crew, equipment, and environment is analyzed; Based on the performance change trend and the task resources, identify the performance bottlenecks in the task execution process and the key influencing factors corresponding to the performance bottlenecks; Analyze the task execution process to determine the time loss corresponding to the key influencing factors, as well as conflict items and risk items; Based on the time loss, conflict items, and risk items, the crew's operating procedures, the equipment's operating status, and the environment's configuration parameters are optimized and adjusted to improve the collaborative relationship.

[0013] According to one embodiment of this application, the optimization and adjustment of the crew's operating procedures, the equipment's operating status, and the environmental configuration parameters based on the time loss, the conflict items, and the risk items includes: A collaborative network is constructed for the intelligent agents corresponding to the crew members, the equipment, and the environment; Based on the time loss, the conflict items, and the risk items, a reward mechanism for the collaborative network is set. Based on the reward mechanism, the agents in the collaborative network are trained to optimize the operation process, the running state, and the configuration parameters.

[0014] Secondly, this application provides a collaborative optimization device for ship mission operations, the device comprising: The acquisition module is used to acquire the ship's operational tasks; The first processing module is used to perform collaborative analysis of the task requirements of the operation based on the ship's operating environment information and the crew's work characteristics, and to construct a multi-person-machine-environment collaborative model. The task requirements include visual task requirements, auditory task requirements, cognitive task requirements and motion task requirements. The second processing module is used to simulate the task execution process of the operation task through the multi-person-machine-environment collaborative model and obtain simulation results. The simulation results include the task resources of the operation task and the collaborative operation efficiency between the crew, equipment and environment in the ship. The third processing module is used to optimize the collaborative relationship of each element in the simulation result based on the task resources and the collaborative operation efficiency. The elements include the crew, equipment and environment corresponding to the operation task.

[0015] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the collaborative optimization method for ship mission operations as described in the first aspect above.

[0016] Fourthly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the collaborative optimization method for ship mission operations as described in the first aspect above.

[0017] Fifthly, this application provides a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the collaborative optimization method for ship mission operations as described in the first aspect.

[0018] Sixthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the collaborative optimization method for ship mission operations as described in the first aspect above.

[0019] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application.

[0020] The collaborative optimization method, apparatus, and electronic equipment for ship mission operations provided in this application have the following advantages over the prior art: (1) By combining ship operation environment information and crew work characteristics, a multi-person-machine-environment collaborative model is constructed. Crew, equipment and environment are used as three core interactive elements for collaborative modeling. The collaborative relationship in the task execution process is simulated to obtain the resources required for the task. The collaborative operation efficiency between crew, equipment and environment is analyzed. It can dynamically reflect the changes in task requirements, the crew's operating status and the impact of environmental conditions, quantitatively evaluate the performance of each link in the task execution, accurately identify and optimize potential collaborative imbalances or resource waste points, optimize the collaborative relationship between crew, equipment and environment, and improve the overall operational efficiency of the task.

[0021] (2) By analyzing the efficiency change trend based on collaborative operation efficiency, we can identify efficiency bottlenecks and their key influencing factors, analyze time loss, conflict items and risk items, and optimize and adjust crew, equipment and environment to significantly improve collaborative operation efficiency in the task execution process, ensure the smooth completion of the task, reduce bottlenecks and risks, and improve the overall efficiency of task execution. Attached Figure Description

[0022] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating the collaborative optimization method for ship mission operations provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of the collaborative optimization device for ship mission operations provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0024] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0025] The following description, in conjunction with the accompanying drawings, details the collaborative optimization method, collaborative optimization device, electronic equipment, and readable storage medium for ship mission operations provided in this application, through specific embodiments and application scenarios.

[0026] Among them, the collaborative optimization method for ship mission operations can be applied to the terminal, specifically executed by the hardware or software in the terminal.

[0027] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablets with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but rather a desktop computer with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads).

[0028] The following embodiments describe a terminal including a display and a touch-sensitive surface. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and joystick.

[0029] The collaborative optimization method for ship mission operations provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the collaborative optimization method for ship mission operations. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The collaborative optimization method for ship mission operations provided in this application embodiment will be described below using an electronic device as the execution subject as an example.

[0030] like Figure 1 As shown, the collaborative optimization method for the ship's mission operations includes: Step 110: Obtain the ship's operational tasks.

[0031] Understandably, a ship's operational tasks are the specific work that a ship needs to complete when performing various missions, such as marine scientific surveys, marine archaeological searches, and carrier-based aircraft support operations.

[0032] In step 110, the specific work content of the task is determined according to the role to be undertaken in the specific application scenario.

[0033] For example, in military exercises, the mission of ships is to patrol and guard specific sea areas and be ready to respond to simulated enemy situations. The specific work content of the mission includes detailed information such as patrol range, alert level, mission duration, expected results, and special requirements for ships and crew.

[0034] Step 120: Based on the ship's operating environment information and the crew's work characteristics, conduct a collaborative analysis of the task requirements of the operation, and construct a multi-person-machine-environment collaborative model. The task requirements include visual task requirements, auditory task requirements, cognitive task requirements, and motion task requirements.

[0035] It is understandable that operational environment information refers to the objective conditions under which a ship performs its operational tasks. This information can affect the ship's navigation safety, equipment operation, and the working status of the crew. Operational environment information includes both human and physical environments.

[0036] The human environment includes traffic conditions in the work area, the distribution of other ships or equipment, etc.; the physical environment includes sea conditions, weather, electromagnetic interference intensity, frequency, etc.

[0037] The characteristics of a crew member's work are the individual traits that affect the effectiveness of the mission, such as their work ability, efficiency, fatigue level, experience level, and work habits.

[0038] Task requirements describe the conditions, requirements, and expected goals that must be met to complete a task, including visual task requirements, auditory task requirements, cognitive task requirements, and motor task requirements.

[0039] During shipboard operations, visual task requirements refer to the need for visual information processing, including target recognition, sea surface conditions, visual interfaces for operating equipment, and reading instrument panels, so that crew members or equipment can accurately acquire and understand visual information about the surrounding environment. Auditory task requirements refer to the need for auditory information processing, including receiving verbal instructions and listening to equipment operating sounds to diagnose malfunctions. Cognitive task requirements refer to the requirements for cognitive activities such as information processing, analysis, judgment, and decision-making, including the ability to understand, analyze, and make decisions about complex information, as well as the ability to respond to emergencies. Motion task requirements refer to the various motion activities that crew members and equipment need to perform when performing tasks, and the need for motion control of crew members or equipment, including precise operating actions, coordinated movement trajectories, and rapid reaction capabilities.

[0040] Because the execution of operational tasks involves the interrelationships, interactions, and mutual influences among crew members, equipment, and the environment, a collaborative analysis of task requirements is conducted to comprehensively examine and analyze the elements such as crew members, equipment, and the environment. This allows for the determination of how these elements can cooperate to achieve the task objectives and how to optimize this cooperation to improve operational efficiency and effectiveness.

[0041] The multi-person-machine-environment collaborative model is a mathematical model that includes the interrelationships and interactions between multiple crew members, ship equipment, and the ship's operating environment. It is used to describe and simulate the collaborative work of various elements during ship operations. By analyzing the impact of different factors on the execution of operational tasks, it can rationally allocate and coordinate the tasks and resources among crew members, ship equipment, and operational environmental information to improve overall operational efficiency.

[0042] In step 120, before the operation is carried out, meteorological forecasting equipment, sea state monitoring instruments and other environmental data of the operation area are collected, and the impact of various parameters in the environmental data on ship navigation, equipment operation and other aspects is assessed. For example, strong winds and waves may cause the ship to roll more violently, affecting the stability of the crew's operation.

[0043] By analyzing crew members' physical examination records, psychological test results, training files, and past mission performance, we can determine the specific tasks that different crew members are suitable for, as well as their strengths and weaknesses in collaborative work, which can be used as the characteristics of crew members' work.

[0044] Based on factors such as crew, equipment, and environment, as well as collected environmental data and crew work characteristics, the interrelationships and mechanisms of action among these factors are defined, such as the crew's reaction time when operating equipment and the equipment failure rate under different environments, and a multi-person-machine-environment collaborative model is constructed.

[0045] For N crew members on a ship, the characteristic parameter vector for each crew member is: , ,in, Indicates crew It includes various characteristics such as skill proficiency with device j, operational reaction time, and cognitive ability.

[0046] For the M devices on the ship, the parameter vector of each device is: , This includes the performance indicators, failure rate, and operating status of device j.

[0047] The factor vector of environmental factors for ships is Meteorological conditions such as wind speed, temperature, and humidity, or sea conditions such as wave height and swells.

[0048] In the collaborative relationship between crew and equipment, considering factors such as crew skill level, reaction time, and equipment performance, the effect of crew member i operating equipment j is: .

[0049] For example, the collaborative relationship between crew and equipment is as follows:

[0050] In the collaborative relationship between equipment and environment, considering the variation of equipment failure rate with environmental factors, the operating state of equipment j under the influence of environmental factors is as follows: :

[0051] In the collaborative relationship between crew members and the environment, considering the impact of environmental factors on crew members' cognitive abilities and operational efficiency, the work suitability of crew member i in a specific environment is:

[0052] in, These are weighting coefficients, representing the importance of each factor in the collaborative relationship; This is the normalization constant; This represents the skill proficiency of crew member i, measured by the accuracy rate of completing operations, with a value ranging from [value range missing]. The larger the value, the more skilled the crew member i is. This represents the reaction time of crew member i, in seconds. The smaller the value, the faster the reaction speed of crew member i. This represents the cognitive ability of crew member i; the larger the value, the stronger the cognitive ability of crew member i. Indicates the endurance of crew member i; The failure rate of device j is expressed in times per hour; a smaller value indicates higher reliability of the device. The operating efficiency of device j is represented by the ratio of the speed at which the device completes the task to its theoretical maximum speed, and its value ranges from [value missing]. A higher value indicates higher equipment operating efficiency; This represents the operational complexity of device j; a larger value indicates higher operational complexity. This represents the energy consumption of device j; This indicates the environmental adaptability of device j; This indicates the ambient temperature, expressed in degrees Celsius. Indicates ambient humidity; Wind speed is expressed in meters per second. Indicates vibration; This indicates the ambient noise level, measured in decibels.

[0053] Step 130: Simulate the task execution process of the operation task through the multi-person-machine-environment collaborative model to obtain simulation results. The simulation results include the task resources of the operation task and the collaborative operation efficiency between the crew, equipment and environment in the ship.

[0054] The simulation results are the output obtained after simulating the task execution process of ship operations using a multi-person-machine-environment collaborative model. The results include the usage of various task resources required for the operation, as well as the efficiency of collaborative operations between crew, equipment and environment on the ship, which are used to evaluate the feasibility and effectiveness of the operation plan.

[0055] The task execution process is used to characterize the various operational stages experienced from start to finish when completing a task, involving the interaction and cooperation between crew, equipment and environment, including the task initiation phase, task execution phase, task monitoring and scheduling phase and evaluation phase.

[0056] In the task execution process, the initial phase involves defining the task, scheduling crew members, preparing equipment, and assessing the environment. Next, the execution phase begins, where crew members operate the equipment, the equipment responds to environmental changes, and crew members collaborate. During the monitoring and scheduling phase, task progress is monitored in real time, and task execution strategies are adjusted to adapt to environmental changes. Finally, the evaluation phase monitors resource consumption and analyzes collaborative work efficiency. By simulating the task execution process using a multi-person-machine-environment collaborative model, the resource consumption, crew-equipment interaction, and collaborative work efficiency indicators can be comprehensively evaluated, providing data support for optimizing task execution strategies and improving operational efficiency.

[0057] Task resources are the various resources required to complete a task, including human resources, material resources, financial resources, time, and the performance and functions of equipment.

[0058] Collaborative work efficiency refers to the efficiency with which crew, equipment, and the environment complete tasks through mutual cooperation during collaborative operations. It describes the effectiveness of collaborative work among crew, equipment, and the environment and is measured by indicators such as task completion time, resource utilization rate, and task success rate.

[0059] In step 130, in the multi-person-machine-environment collaborative model, different simulation scenarios are set according to the actual task requirements, such as different sea conditions, weather conditions, enemy situations, etc., and the value range of each parameter is determined to simulate a variety of complex situations that may occur.

[0060] The simulation executes tasks according to the set scenarios and parameters. During the simulation, the interaction between crew members, equipment and environment can be observed in real time, and the consumption of various task resources and the efficiency indicators of collaborative operations can be recorded. For example, the simulation can simulate crew members' operations in different environments and calculate operational efficiency, equipment failure frequency, etc.

[0061] First, establish a simulation model of the operational task that includes three elements: crew, equipment, and environment. These three elements can interact and provide feedback within the virtual environment.

[0062] In the task simulation model, for crew members, the model defines their behavioral patterns, workflows, decision-making rules, and collaborative relationships and interactions. It also sets up tasks such as time management, equipment operation, and collaborative work. For shipboard equipment, a physical model is established based on the topology of the equipment to describe its operating states, including startup, operation, pause, shutdown, and malfunction. The model also describes the equipment's operating parameters, such as speed, energy efficiency, and operating time, as well as the interaction between the equipment and the crew, including equipment maintenance, inspection, and resource consumption. For the ship's environment, the model sets parameters such as weather conditions, sea state, spatial layout, and physical obstacles, as well as environmental change rules such as weather changes and sea state fluctuations, to determine the impact of the environment on crew and equipment operations.

[0063] Based on the task simulation model, specific simulation scenarios and task parameters are set, including the types of tasks such as search and rescue, transportation, and equipment maintenance, as well as the types, initial quantities, and consumption of resources; the duration of the simulated tasks, including real-time monitoring of task execution progress, and environmental factors such as weather, sea conditions, and available equipment.

[0064] The AnyLogic simulation software is used to simulate the work task and advance the task execution according to the set time step. The operation of crew and equipment, the interaction between equipment and environment, and the cooperation between crew members are fed back in real time. During the simulation, the crew behavior, equipment parameters and environmental configuration are dynamically adjusted according to different situations such as equipment failure and crew operation errors. During the simulation, the consumption of task resources and the efficiency indicators of collaborative operation are recorded in real time.

[0065] Consumption includes crew resource consumption, equipment resource consumption, and environmental resource consumption. Crew resources include crew working hours, rest time, and operational efficiency; equipment resources include equipment energy consumption, workload, and maintenance time; and environmental resources include energy use and the impact of weather changes on equipment and crew.

[0066] Efficiency indicators include task completion time, equipment utilization rate, collaborative efficiency, and resource utilization rate. For task completion time, the actual completion time of the task is compared with the expected completion time. Equipment utilization rate is used to characterize the ratio of equipment operating time to total working time. Collaborative efficiency between crew and equipment, between crew and the environment, and between equipment and the environment is assessed by calculating the delay time, error, and effectiveness of collaborative operations. Resources for resource utilization rate include fuel, equipment, and time.

[0067] During the simulation, task execution data, collaborative operation data, and resource consumption data are recorded in real time. For example, the start time, end time, resource consumption, and coordination status of each task are recorded, as well as the behavior of crew, equipment, and environment during task execution. This is to evaluate the collaborative effect and the consumption of all resources. The recorded data is then presented in the form of charts, reports, etc. The recorded data is analyzed to optimize the task execution process, identify bottlenecks and high-consumption links, and evaluate the accuracy and feasibility of the simulation results.

[0068] Based on the performance of crew, equipment, and environment during the simulation, the reward mechanism is modified to encourage agents to adopt efficient operating modes. Based on the resource consumption during task execution, the resource allocation strategy is re-evaluated to reduce resource waste. Conflicts and inefficient links in collaboration are analyzed, and new collaboration rules are formulated to improve overall efficiency.

[0069] The real-time dynamic monitoring interface displays the changes in the status of crew, equipment, and environment, highlighting key mission nodes. The performance evaluation panel displays key data such as efficiency indicators and resource consumption. Through interactive analysis tools, users can adjust parameters and view changes in simulation results in real time.

[0070] Step 140: Optimize the collaborative relationship of each element in the simulation results based on the task resources and the collaborative operation efficiency. The elements include the crew, equipment and environment corresponding to the operation task.

[0071] Elements are the basic building blocks in the task execution process of a work operation, including crew members, equipment, and environment. Elements interact and influence each other, and together determine the execution effect of the work operation.

[0072] In step 140, the simulated data on task resource usage and collaborative work efficiency are analyzed to identify problems and bottlenecks in the collaborative relationship. For example, frequent equipment failures in specific environments may cause task delays, or poor communication among crew members may affect overall work efficiency.

[0073] To address issues related to collaborative relationships, corresponding optimization measures are implemented. These measures include improving equipment to enhance its anti-interference capabilities, adjusting crew positions and task assignments to fully leverage their strengths, and optimizing communication and collaboration methods among crew members.

[0074] Based on the optimized solution, the multi-person-machine-environment collaborative model is reconfigured, the collaborative relationships between elements are optimized, and simulations are performed. The simulation results before and after optimization are compared to evaluate the effectiveness of the optimization solution, including whether the collaborative work efficiency has been improved and whether the utilization rate of task resources is more reasonable. If the expected results are not achieved, the optimization solution is further adjusted until the task requirements are met.

[0075] According to the collaborative optimization method for ship mission operations provided in this application, a multi-person-machine-environment collaborative model is constructed by combining ship operation environment information and crew work characteristics. Crew, equipment, and environment are regarded as three core interactive elements for collaborative modeling. The collaborative relationship in the mission execution process is simulated to obtain the resources required for the mission, analyze the collaborative operation efficiency between crew, equipment, and environment, dynamically reflect the changes in mission requirements, the crew's operating status, and the impact of environmental conditions, quantitatively evaluate the performance of each link in mission execution, accurately identify and optimize potential collaborative imbalances or resource waste points, optimize the collaborative relationship between crew, equipment, and environment, and improve the overall operational efficiency of the mission.

[0076] In some embodiments, the step of collaboratively analyzing the task requirements of the operational task based on the ship's operational environment information and the crew's work characteristics, and constructing a multi-person-machine-environment collaborative model, includes: Based on the crew operation tasks, equipment operation tasks, and environmental requirements in the operation task, the operation task is decomposed into multiple sub-tasks. The crew operation tasks refer to the operational activities that the crew needs to perform manually in the task execution process. The equipment operation tasks are the operations that the equipment on the ship needs to perform according to the operation task. The environmental requirements are the specific environmental conditions required when the operation task is executed, including the human environment and the physical environment. By comparing and analyzing the work characteristics of the crew members with the task requirements of the sub-tasks, the crew members' ability to perform each sub-task is determined. Based on the execution capability and the work environment information, each element in the work task is configured collaboratively to determine the niche of the element. The niche is the position and role of the element in the multi-person-machine-environment collaborative model, as well as the way and scope of its interaction with other elements. Based on the dependencies and priorities among the multiple subtasks, the niche of the elements is adjusted to construct the multi-person-machine-ring collaborative model.

[0077] Among them, crew operation tasks refer to the operational activities that crew members need to personally complete in the task execution process of the operation task, such as driving the ship, operating the weapon system, monitoring the equipment status, and conducting communication.

[0078] Equipment operation tasks are the operations that the equipment on the ship is required to perform according to the job duties. For example, starting and running the engine, scanning and tracking the radar, setting the parameters of various instruments and collecting data, etc., can be achieved through automated control systems or by the crew.

[0079] Environmental requirements are the specific environmental conditions required for the execution of operational tasks, including both human and physical environments, which can affect the performance and efficiency of ships, crew, and equipment.

[0080] The human environment includes traffic conditions in the work area, the distribution of other ships or equipment, etc.; the physical environment includes sea conditions, weather, electromagnetic interference intensity, frequency, etc.

[0081] Subtasks are used to decompose complex tasks into multiple relatively independent and smaller, more specific task units. Each subtask has a relatively independent objective and operational content, corresponding to specific task requirements, which facilitates separate analysis and processing.

[0082] Task requirements are used to characterize the various conditions and resources needed to complete a subtask, including resources such as manpower, material resources, time, and technology, as well as specific requirements for various operations in the task execution process, such as specific requirements for vision, hearing, cognition, and movement.

[0083] The crew's ability to perform sub-tasks is determined by the impact of their skill level, experience, fatigue level, and other work characteristics on the execution of sub-tasks under specific work conditions. This ability includes the efficiency, accuracy, and reliability of sub-task execution.

[0084] Collaborative configuration is the rational arrangement and combination of elements such as crew, equipment, and environment based on the requirements of the task and the characteristics of each element, so that crew, equipment, and environment can cooperate and work together to improve operational efficiency and quality.

[0085] The niche of an element is the position and role of the element in a multi-machine-environment collaborative model, as well as the way and scope of its interaction with other elements. It reflects the element's functional positioning in the system, its relationship with other elements, and its adaptability.

[0086] Dependency is a relationship between subtasks that involves their order of execution, mutual dependence, and mutual influence. The completion of one subtask depends on the completion or reaching a certain state of another one or more subtasks. It is used to determine the order of execution and coordination of subtasks.

[0087] Priority is used to measure the importance and urgency of a subtask within a task. Subtasks with higher priority are allocated more resources and manpower for execution.

[0088] In actual execution, by analyzing the overall objectives of the task, the key elements such as the scope, time limit, and expected results of the task are determined. Based on the nature of the task and the task execution process, the main operational links are identified, such as the navigation of rescue ships, locating the distressed location, preparation and use of rescue equipment, and transfer and treatment of distressed personnel.

[0089] Each major operational phase is further subdivided into specific sub-tasks. For example, the navigation phase can be broken down into sub-tasks such as departure, route planning, and speed control; the rescue equipment usage phase can be broken down into sub-tasks such as lifeboat deployment and rescue crane operation. Each sub-task has a clear target and completion standard. For each sub-task, a detailed analysis is conducted on its specific requirements for crew members in terms of vision, hearing, cognition, and movement. For example, the sub-task of operating radar equipment requires crew members to have good eyesight and the ability to recognize radar signals; the sub-task of piloting a ship requires crew members to have strong concentration and proficient ship handling skills.

[0090] The characteristics of elements such as crew, equipment, and environment are analyzed to obtain the crew's work characteristics. These characteristics are then compared with the task requirements of sub-tasks, and a quantitative scoring method is used to evaluate the crew's ability to perform each sub-task. For example, scores are given based on the crew's skill proficiency and physical fitness to determine their ability level when performing a specific sub-task.

[0091] Based on the objectives and requirements of the task, combined with execution capabilities and the aforementioned work environment information, a collaborative configuration model is established, encompassing the relationships between crew members, equipment, and the environment. In this model, each element is treated as a node, and the collaborative relationships between elements are represented by connecting lines. Attributes of the nodes and connecting lines are defined, such as crew member capabilities, equipment performance, and the degree of environmental impact. Optimization algorithms, such as genetic algorithms and simulated annealing, are used to seek the optimal combination and configuration scheme of elements within the collaborative configuration model. By adjusting crew member job positions, equipment allocation and usage, and environmental adaptability measures, efficient collaborative work among the elements is achieved, determining the optimal niche for each element within the multi-person-machine-environment collaborative model.

[0092] By analyzing the task execution flow and logical relationships of the job tasks, the dependencies between the subtasks are identified. For example, subtask 1 can only start after subtask 2 is completed, or subtask 3 and subtask 4 can be performed simultaneously but need to share resources. The priority of each subtask is determined according to the goal and urgency of the job task.

[0093] By treating subtasks as nodes, arrows between nodes indicate the direction and order of dependencies, and the priority of each subtask is marked, a subtask dependency graph is constructed.

[0094] Based on the dependencies and priorities in the subtask dependency graph, the niches of the elements that have been determined are adjusted. For example, for high-priority subtasks, capable crew members and high-performance equipment can be assigned to them first, and environmental adaptability measures can be optimized. For subtasks with dependencies, the niches of the relevant elements need to be adjusted to ensure smooth connection between subtasks, such as adjusting the work order of crew members and the usage arrangement of equipment, so as to obtain a highly efficient multi-person-machine-environment collaborative model.

[0095] In some embodiments, the operating environment information includes equipment status and environmental parameters. The step of collaboratively configuring each element in the task based on the execution capability and the operating environment information to determine the niche of the element includes: Based on the equipment status and the environmental parameters, the operating requirements and performance limitations of the equipment are determined. The equipment status refers to the operating condition and performance of the equipment, including equipment availability, fault status, and performance indicators. The environmental parameters are environmental parameters that affect the execution of the task, including the natural environment and the electromagnetic environment. Based on the execution capability, determine the operating equipment, operating position, and work scope corresponding to each crew member; Based on the operational requirements, performance limitations, operating equipment, operating location, and work scope, determine the working rhythm and interaction frequency of the crew, the equipment, and the environment; Based on the working rhythm and the interaction frequency, the interaction relationships and energy flow patterns between the elements are analyzed to determine the ecological niche of each element.

[0096] During crew operations, equipment and environment together constitute the crew's working environment. Equipment status refers to the operating status and performance of the equipment, including its availability, fault status, and performance indicators. Environmental parameters are environmental parameters that affect the execution of the mission, including natural and electromagnetic environments, such as temperature, humidity, light intensity, and noise level.

[0097] Operational requirements include the operational procedures and conditions required for the equipment to complete its tasks, including operational steps, operational sequence, and operational environment requirements.

[0098] Performance limitations are the performance boundary conditions determined by factors such as technology, design, or environment during actual operation of equipment. These limitations change with changes in equipment status and environmental parameters, such as maximum processing capacity and minimum operating conditions.

[0099] Execution capability refers to the crew's ability and efficiency in completing various sub-tasks within a work operation, including the impact of skill level, experience, and fatigue on task execution.

[0100] Operating equipment refers to shipboard equipment assigned to crew members for specific operations based on their capabilities and mission requirements. Examples include various equipment in a ship's navigation control system, weapon system, communication system, radar system, and power system. Crew members need to operate these devices correctly according to operational requirements and mission execution procedures to complete the corresponding sub-tasks.

[0101] Operating position describes the specific working location of a crew member on a ship and is associated with the equipment the crew member operates. Different equipment is distributed in different areas of the ship, such as the bridge, engine room, turret, and communications room. Determining the operating position requires consideration of factors such as equipment layout, crew member's ease of operation, and mission efficiency, ensuring that the crew member can effectively operate the equipment from the appropriate location.

[0102] The scope of operations defines the range of activities and job responsibilities of crew members when performing sub-tasks. This includes the areas crew members need to access within the ship, such as entering specific parts of the engine room for equipment maintenance; it also includes the scope of crew members' influence over the external environment during mission execution, such as the sea area and airspace they need to observe during lookout missions. Defining the scope of operations helps clarify crew members' job responsibilities and mission priorities, avoiding overlap or omissions.

[0103] Work rhythm is the frequency and pace of interaction and coordination between crew, equipment, and the environment. It describes the speed and degree of cooperation of each element in the task execution process. For example, the operating speed of the crew, the operating cycle of the equipment, and the frequency of the impact of the work environment information on the task together constitute the work rhythm.

[0104] Interaction frequency refers to the frequency of interaction and information exchange between crew, equipment, and the environment, reflecting the closeness of the connection between the elements, such as the frequency of transmission of operating instructions between crew and equipment, the frequency of data acquisition and feedback between equipment and the environment, and the frequency of observation and perception between crew and the environment.

[0105] Interaction relationships include the ways and patterns of mutual influence and interaction among crew members, equipment, and the environment. For example, the crew's operational control over equipment, the feedback from equipment to the crew's working status, and the constraints or promotions of environmental information on crew members and equipment.

[0106] Energy flow laws describe the ways and patterns of energy transfer, conversion, and consumption among crew members, equipment, and the environment. Energy forms can include physical energy, information energy, and human bioenergy. Physical energy includes electrical energy, thermal energy, and mechanical energy; information energy includes data transmission and command transmission; and human bioenergy includes the physical exertion of crew members.

[0107] Niche refers to the position and role of each crew member, equipment, and environment element in a multi-machine-environment collaborative model, as well as the way they interact with other elements.

[0108] In actual implementation, the equipment's operating data, including operating parameters such as temperature, pressure, voltage, and current, as well as information such as operating time, number of failures, and maintenance records, is obtained in real time through equipment monitoring systems such as sensor networks and fault diagnosis systems to determine the equipment status.

[0109] Based on the equipment status and environmental parameters, considering the impact of temperature, humidity, and electromagnetic interference on the equipment in the working environment, determine the operating requirements and performance limitations of the equipment in the current environment.

[0110] Based on the crew's performance capabilities and the needs of the operational tasks, the crew members are assigned to corresponding operational positions. Each operational position is equipped with operating equipment. The crew members' operating positions are determined according to the ship's equipment layout and the crew members' operational needs. The crew members' work scope is defined according to the task requirements of the sub-tasks and the ship's task area.

[0111] Analyze the task execution flow and time requirements of each sub-task in an operational mission, including the start and end times of the mission, the duration of each phase, and the transition time between tasks. For example, in an anti-submarine warfare mission, the sonar detection sub-task needs to complete the search of a designated sea area within a specified time, and then perform target tracking and data transmission based on the detection results to support the launch of anti-submarine weapons. Based on the equipment's operational requirements and performance limitations, evaluate the equipment's operating cycle in completing each sub-task. The operational cycle is determined by combining the crew's execution capabilities with the task time requirements. For example, it specifies the number of operational steps the crew needs to complete within a certain time, the frequency of equipment monitoring, and the number of interactions with other crew members or equipment.

[0112] By combining the impact of environmental parameters in the work environment on work rhythm and interaction frequency, and by simulating task execution under different environmental conditions or referring to historical data, the specific degree of impact of the work environment on work rhythm and interaction frequency can be evaluated.

[0113] Taking into account the impact of task execution process, equipment operation cycle, crew work rhythm and working environment, the work rhythm and interaction frequency of crew, equipment and environment in the entire multi-person-machine-environment collaborative model are determined.

[0114] In the multi-person-machine-environment collaborative model, crew, equipment, and environment are the main elements. Crew members are divided into different operational positions, equipment is divided into various shipboard equipment, and the environment is divided into human and physical environments. By establishing the connections and interaction mechanisms between these elements, the model analyzes their roles within the multi-person-machine-environment collaborative model. Examples include the crew's control over equipment operations, the feedback from equipment to the crew's work status, and the constraints of the working environment on both crew and equipment.

[0115] In the multi-person-machine-environment collaborative model, the energy flow law of the system is determined by analyzing the path, direction, magnitude and conversion efficiency of energy flow.

[0116] Based on the interactions and energy flow patterns among the elements, and considering factors such as the functional importance of each element within the system, its interdependence with other elements, and its contribution and impact on energy flow, the niche of each element in the multi-person-machine-environment collaborative model is determined. For example, in the multi-person-machine-environment collaborative model for anti-submarine warfare, sonar operators and sonar equipment occupy a crucial niche in target detection, and their functionality directly affects the success or failure of the entire anti-submarine warfare mission; while communication equipment and personnel occupy an important niche in information transmission and coordinated command, ensuring effective coordination among various combat units. By determining the niche of each element, guidance can be provided for optimizing the configuration of the multi-person-machine-environment collaborative model, improving mission execution efficiency, and achieving complementary advantages and efficient coordination among the elements.

[0117] In this embodiment, by analyzing the energy flow pattern, the energy utilization efficiency of the system can be evaluated, energy loss points can be identified, and guidance can be provided for optimizing the system's collaborative configuration and improving energy utilization efficiency.

[0118] In some embodiments, adjusting the niche of the elements based on the dependencies and priorities among the multiple subtasks to construct the multi-user-machine-environment collaborative model includes: Based on the dependencies and priorities, determine the execution order and time constraints of each subtask; Based on the execution order and time constraints, an execution time window is allocated to each of the subtasks; Determine the crew's operating authority over specific equipment based on their performance capabilities and mission requirements; Based on the execution time window, the ship's resource limitations, and the operation permissions, resources are allocated to each subtask, and the subtasks are assigned to crew members with the corresponding permissions to obtain an allocation scheme. Obtain and analyze the execution feedback information corresponding to the allocation scheme, determine the element tasks and interaction methods of the element, and adjust the ecological niche of the element, the workload of the crew, and the operating parameters of the equipment; Based on the element tasks, the interaction methods, and the ecological niche, the multi-person-machine-environment collaborative model is constructed.

[0119] The execution time window is a specific time range allocated to each subtask, taking into account factors such as the priority of subtasks, dependencies, and the overall task plan. It allows the subtask to begin execution and be completed within that timeframe. This ensures that subtasks are executed at appropriate times while avoiding time conflicts with other subtasks.

[0120] Operating authority is determined based on the crew's capabilities and mission requirements. It defines the scope of authority that allows crew members to operate specific equipment, including the authority to perform normal operations as well as the authority to perform advanced operations or emergency handling operations in specific situations.

[0121] Resource constraints refer to the limited and restrictive nature of the various resources a ship possesses, such as manpower, material resources, time, and space.

[0122] Interaction methods refer to the ways and means by which various elements exchange information and collaborate. For example, crew members can communicate in real time through voice communication devices, and crew members can interact with equipment through control panels, user interfaces, and other means to issue operating commands and provide feedback on equipment status information.

[0123] In actual execution, a task dependency graph is drawn based on the dependencies between subtasks to obtain the order of subtasks, which serves as the execution order of each subtask. Based on the priority of subtasks, time constraints such as the earliest start time and the latest end time are determined for each subtask within the overall task plan time requirements. Among them, subtasks with higher priority should be given priority in time scheduling to ensure that they do not conflict with other dependent subtasks in terms of time.

[0124] By combining the execution order and time constraints of subtasks, a reasonable execution time window is divided for each subtask on the overall task timeline. The Critical Path Method (CPM) is used to assist in optimizing the allocation of execution time windows, ensuring that the time arrangement of the entire task execution process is as reasonable and efficient as possible. The time window should allow the subtask to complete smoothly within its time, while also taking into account the connection and coordination with the time windows of other subtasks to avoid time overlaps, conflicts, or excessively long idle intervals.

[0125] Based on the task requirements of each subtask and the crew's execution capabilities, a detailed list of operational permissions is developed, clarifying the extent to which crew members can operate the equipment and obtaining each crew member's operational permissions for each piece of equipment. Based on factors such as the execution time window of each subtask, the type and quantity of required resources, and the crew members' operational permissions, resource allocation algorithms, such as integer programming or heuristic algorithms, are used to rationally allocate each subtask to crew members with corresponding permissions, determining the resource allocation required for each subtask, and ultimately forming a complete allocation scheme. This scheme includes the executor of each subtask, the execution time, the resources required, and their usage.

[0126] The execution feedback information corresponding to the allocation scheme is analyzed to determine the task execution process, workload, and potential risks of each subtask, thereby determining the element tasks undertaken by each element and the interaction methods between them.

[0127] Based on the analysis results, the niche of elements is adjusted. For example, the scope of sub-tasks or work schedules of crew members are adjusted according to their workload to ensure that their workload is within a reasonable range. The operating parameters of the equipment are optimized and adjusted according to the matching between the operating parameters of the equipment and the requirements of the sub-tasks to improve the operating efficiency and reliability of the equipment and ensure the efficient operation of the entire multi-person-machine-environment collaborative model.

[0128] Based on the defined element tasks, interaction methods, and adjusted ecological niches, a multi-person-machine-environment collaborative model architecture was constructed. In this model, each crew member collaborates in their respective work positions according to the assigned plan and the prescribed interaction methods. The equipment operates according to optimized operating parameters and access permissions, jointly completing the collaborative tasks of the entire model. Furthermore, corresponding system monitoring and feedback mechanisms were established to promptly identify and address problems during system operation, further optimizing the system's collaborative effectiveness.

[0129] In some embodiments, simulating the task execution process of the job using the multi-person-machine-environment collaborative model to obtain simulation results includes: The multi-person-machine-environment collaborative model is used to simulate the task execution process of the job, which includes multiple job stages. Based on the importance of task requirements in the aforementioned work process and the weight of resources in the task execution process, the task resources called in the task execution process are divided into resource units. The categories of resource units include key resources, auxiliary resources, and alternative resources. Based on the task execution process, a multi-level model is constructed according to the importance of the resource units, task dependencies, and dynamic scheduling requirements. Based on the multi-level model, the task resources are configured and scheduled to simulate the task execution process of the job. Based on the resource utilization information and task completion information of the simulated mission execution process, the collaborative operation efficiency between the crew, equipment and environment on the ship is calculated as the simulation result.

[0130] The operational phases are the specific work stages in the task execution process, including task objectives, resource requirements, and time arrangements.

[0131] Critical resources are those essential to the completion of a mission, such as a ship's power system or core equipment; auxiliary resources are those that help in mission execution, but their absence will not immediately affect mission completion, such as auxiliary equipment, tools, or technical support; and alternative resources are those that can be replaced by other resources during mission execution, such as backup equipment or one of several alternative options.

[0132] Task dependencies are the order, priority, and dependence between different task stages; a certain stage may need to be completed before it can proceed.

[0133] Dynamic scheduling requirements are the need for real-time resource scheduling and task adjustment during task execution due to factors such as task requirements, resource status, and environmental changes.

[0134] Multi-level models are used to decompose tasks into multiple levels for management and scheduling during task execution. Each level includes different resource configurations, task scheduling, and control strategies, which can more effectively cope with complex task execution environments.

[0135] Resource utilization information includes the usage, efficiency, and time spent on various resources during task execution.

[0136] Task completion information includes whether the task was completed as expected, the quality of completion, and the amount of resources consumed at the end of the task execution process.

[0137] Collaborative work efficiency refers to the collaborative effect between crew, equipment, and the environment during task execution, manifested in the maximization of resource utilization and the timeliness and quality of task completion.

[0138] In actual execution, the task is decomposed, each operational step is identified, and the resources and execution order required for each step are clarified. Based on the task requirements, each step of the task execution process is simulated through a multi-person-machine-environment collaborative model. During the simulation, task dependencies, time constraints, and resource availability are considered. Based on the task requirements and the importance of resources, task resources are divided into key resources, auxiliary resources, and substitute resources, and each resource is assigned a corresponding weight. These are the basic units for dividing the various resources required for task execution according to their importance and function, resulting in resource units. Based on resource units and task execution requirements, a multi-level model is constructed. Each layer of the model considers different resource configurations, scheduling rules, and task execution priorities. Through a dynamic scheduling algorithm, resource configuration is adjusted in real time, and task scheduling is optimized based on changes during task execution.

[0139] During the simulation, the utilization of various resources is collected, and the efficiency of collaborative operations is evaluated based on the interaction between crew, equipment, and the environment, using multi-dimensional data such as resource utilization information and task completion status.

[0140] Based on the simulation results, optimization solutions are proposed, such as improving crew scheduling, equipment maintenance plans, or environmental management strategies, thereby improving the overall efficiency of mission execution.

[0141] In this embodiment, by constructing a multi-person-machine-environment collaborative model to simulate the execution process of the task, optimizing resource allocation using a multi-level scheduling model, and finally evaluating the collaborative operation efficiency, the efficiency of task execution and resource utilization can be improved in complex tasks, especially in ship operation environments, thereby better supporting the successful completion of the task.

[0142] In some embodiments, calculating the collaborative operational efficiency between the crew, equipment, and environment on the ship based on resource utilization information and task completion information from the simulated task execution process includes: Obtain the first resource utilization information and the first task completion information of the resource unit corresponding to each of the aforementioned work stages; Based on the first resource utilization information and the first task completion information, the load balance status of the resource unit is determined to calculate the resource utilization rate. Based on the time constraints of the aforementioned work process, and with the goal of maximizing resource utilization, the task resources are reconfigured and scheduled until the load balance state reaches a preset balance threshold, thereby obtaining optimized second resource utilization information and second task completion information. The collaborative operation efficiency is calculated based on the second resource utilization information and the second task completion information.

[0143] Load balancing refers to the degree of balance in the allocation and use of resources across different tasks. If some resources are overused in a task while others are idle, then the load balancing is not optimal. Load balancing ensures that resources are allocated reasonably and efficiently.

[0144] Resource utilization rate is the ratio of the actual amount of resources used to the maximum amount available. The higher the resource utilization rate, the more fully the resources are utilized.

[0145] Time constraints are the time requirements and limitations for each step in the task execution process.

[0146] Optimizing resource allocation and scheduling refers to maximizing resource utilization efficiency by adjusting resource allocation and scheduling schemes based on real-time resource utilization information obtained during task execution.

[0147] The load balance threshold is a preset standard used to measure whether the load balance of resources has reached a reasonable level.

[0148] Collaborative work efficiency refers to the effectiveness of collaboration between crew, equipment, and the environment during task execution. It can characterize the efficiency, quality, and overall resource utilization of task completion under given resource conditions.

[0149] In actual execution, at each stage of the task execution, the actual use of resources is collected and analyzed as primary resource utilization information, and the completion status of task execution is collected as primary task completion information.

[0150] By analyzing the first resource utilization information and the first task completion information, the load allocation of each resource is determined, and the load balance status of each resource unit is calculated. By comparing the actual usage of resources with their maximum availability, the resource utilization rate is obtained. For time-constrained tasks, critical resources are prioritized based on time requirements to ensure efficient completion within the specified time. Combined with load balance analysis, the allocation of task resources is readjusted, and resources are reconfigured and scheduled until the task load balance status meets a preset balance threshold. For example, the usage of some resources may be reduced, or some resources may be allocated to lighter-loaded tasks until the load distribution tends to be balanced.

[0151] Again, at each stage of task execution, collect information on second resource utilization and second task completion to evaluate task completion, resource utilization, and resource synergy, and calculate collaborative work efficiency. For example, it can calculate the speed, quality, cost, and resource consumption of task completion under given resource conditions.

[0152] Based on the calculated collaborative work efficiency, resource allocation can be further adjusted. If the collaborative work efficiency does not meet expectations, improvements can be made through iterative optimization, such as adjusting task scheduling strategies or increasing investment in key resources.

[0153] In this embodiment, by simulating resource utilization and task completion during the task execution process, load balancing analysis and resource scheduling optimization are used to improve the collaborative work efficiency between crew, equipment and the environment. By continuously optimizing resource allocation and scheduling, the full utilization of resources during the task execution process is ensured, thereby improving the overall efficiency and quality of task completion.

[0154] In some embodiments, optimizing the collaborative relationship of each element in the simulation results based on the task resources and the collaborative operation efficiency includes: Based on the aforementioned collaborative operation efficiency analysis, the efficiency change trend among crew, equipment, and environment is analyzed; Based on the performance change trend and the task resources, identify the performance bottlenecks in the task execution process and the key influencing factors corresponding to the performance bottlenecks; Analyze the task execution process to determine the time loss corresponding to the key influencing factors, as well as conflict items and risk items; Based on the time loss, conflict items, and risk items, the crew's operating procedures, the equipment's operating status, and the environment's configuration parameters are optimized and adjusted to improve the collaborative relationship.

[0155] Among them, the efficiency change trend is used to describe the regular changes in the collaborative efficiency among crew, equipment and environment during the mission execution process as time or resource allocation changes.

[0156] A performance bottleneck describes a bottleneck that occurs during task execution when a resource or a certain step is insufficient, which restricts the progress of the task and causes a decrease in overall efficiency.

[0157] Key influencing factors are those that significantly impact performance bottlenecks, such as equipment performance limitations, crew skill deficiencies, or inappropriate environmental configurations.

[0158] Time loss is the portion of time that takes for a task to be completed that exceeds the planned time due to unreasonable arrangements or efficiency bottlenecks in collaborative operations. Examples include maintenance time that may be caused by equipment failure or additional time consumption that may be caused by improper operation by crew members.

[0159] Conflicts refer to situations where resources or operations clash during mission execution. For example, operational conflicts between crew members and equipment, or incompatibility between equipment and environmental configurations, can lead to resource waste, mission delays, or decreased efficiency.

[0160] Risk items are potential risk factors that may affect the successful completion of a mission during its execution, such as equipment failure, crew operational errors, or environmental changes.

[0161] Understandably, crew operating procedures include various operations that crew members need to perform in a certain order and manner when carrying out tasks. Optimizing operating procedures is key to improving task execution efficiency, reducing resource waste, and avoiding operational conflicts.

[0162] The operating status of equipment refers to the working state of the equipment during the execution of tasks, including the on / off status, working mode, performance, etc. Optimizing the operating status of equipment helps to improve equipment efficiency and avoid failures and delays.

[0163] Environmental configuration parameters refer to external environmental factors that affect task execution, such as temperature, humidity, light, and air circulation speed. Optimizing environmental configuration parameters can improve task execution efficiency and resource utilization.

[0164] In actual execution, based on simulation results, the efficiency of collaborative operations among crew, equipment, and the environment is collected and analyzed. By analyzing data on the changing trends of collaborative efficiency in different task stages, bottleneck areas in the task execution process are identified, with a focus on areas with significant efficiency changes, which indicate uneven resource utilization or improper operation.

[0165] Based on the efficiency change trend and task resource information, identify the links or resources with efficiency bottlenecks in the task execution process, analyze the key influencing factors that form the efficiency bottlenecks, analyze the impact of each key influencing factor on task time to obtain time loss, analyze the possible conflicts that may occur in the task execution process, identify potential risks in the task, such as equipment failure, operational errors or environmental changes, assess the potential impact of these risks on the successful completion of the task, and formulate corresponding coping strategies.

[0166] Based on time loss, conflict items, and risk items, optimization adjustments are made. If the analysis finds that crew member i is causing a conflict when operating equipment j, crew member i's workflow can be adjusted to reduce repetition or conflict in operation, or the use of equipment j can be rearranged. If the performance of equipment j is insufficient, the operating status of equipment j can be adjusted or a backup equipment j+1 can be added. If the environmental parameters are not suitable for the mission requirements, corresponding adjustments can be made, such as optimizing factors such as temperature, humidity, and air circulation. By comprehensively adjusting the configuration of crew, equipment, and environment, the synergistic efficiency between various elements during mission execution can be maximized, and bottlenecks, conflicts, and risks can be effectively mitigated.

[0167] After initial optimization, we continuously monitor the efficiency of collaborative operations during mission execution. By constantly providing feedback on efficiency trends, time losses, conflicts, and risks, we gradually adjust resource allocation and operational processes, improve crew operating procedures, equipment operating status, and environmental configuration parameters, and ensure the efficiency and collaboration of mission execution.

[0168] In this embodiment, by analyzing the efficiency change trend based on collaborative operation efficiency, efficiency bottlenecks and their key influencing factors are identified. Then, time loss, conflict items and risk items are analyzed, and crew, equipment and environment are optimized and adjusted to significantly improve collaborative operation efficiency during mission execution, ensure the smooth completion of the mission, reduce bottlenecks and risks, and improve the overall efficiency of mission execution.

[0169] In some embodiments, optimizing and adjusting the crew's operating procedures, the equipment's operating status, and the environment's configuration parameters based on the time loss, the conflict items, and the risk items includes: A collaborative network is constructed for the intelligent agents corresponding to the crew members, the equipment, and the environment; Based on the time loss, the conflict items, and the risk items, a reward mechanism for the collaborative network is set. Based on the reward mechanism, the agents in the collaborative network are trained to optimize the operation process, the running state, and the configuration parameters.

[0170] It is understandable that an intelligent agent is a virtual entity constructed from crew members, equipment, and the environment, including a decision-making module, a perception module, and an execution module. The decision-making module is used to formulate decision-making strategies based on task requirements and resource status to guide the behavior of the intelligent agent. The perception module is used to acquire environmental information, resource status, and task progress in real time to provide data support for the decision-making module. The execution module performs specific operations according to the instructions of the decision-making module.

[0171] Intelligent agents collaborate with other intelligent agents by simulating and executing specific tasks, operational procedures, equipment states, or environmental configurations to achieve task objectives. Through a network of multiple intelligent agents, a collaborative network is constructed. In the collaborative network, intelligent agents interact with each other through information exchange, collaboration, and feedback mechanisms to optimize the overall task execution process.

[0172] The reward mechanism is used to incentivize agents to take effective actions. In a collaborative network, the reward mechanism evaluates the agent's performance based on the crew's operating procedures, the equipment's operating status, and the environmental configuration parameters, and gives corresponding rewards or penalties.

[0173] In actual implementation, crew members, equipment, and the environment are modeled as different intelligent agents. Each agent acquires real-time data on the environment and tasks through a perception system and makes corresponding decisions based on the current state. A collaborative network is constructed based on the cooperative relationships between the agents. The behavior of the agents can be coordinated through information exchange, collaborative task allocation, and feedback mechanisms. Based on time consumption, conflict items, and risk items, corresponding reward rules are designed for each agent in the collaborative network.

[0174] Among them, crew agents can be rewarded if they can reduce operation time loss; equipment agents can also be rewarded if they avoid operational failures or equipment conflicts; and environmental agents can also be rewarded if they successfully adjust environmental parameters to make the task execution smoother. The incentive mechanism is dynamically adjusted according to the specific task objectives to encourage agents to take the actions most beneficial to the task execution and reduce resource waste, conflicts and risks.

[0175] In a collaborative network, each agent is trained through reinforcement learning or other machine learning methods. Based on the reward signals obtained from task execution, the agent gradually adjusts its behavior to optimize the operation process, equipment status and environmental configuration, so that each step can maximize the expected benefits.

[0176] During training, when an agent optimizes its behavior to reduce time loss or avoid conflict, its successful behavior will be used as a reference by other agents to adjust their own operations.

[0177] For example, when a crew agent optimizes operational procedures and reduces time consumption, other agents may adjust the operating modes of equipment or environmental parameters based on this optimization behavior, thereby achieving more efficient collaborative work.

[0178] As the mission is executed, the collaborative network dynamically and continuously adjusts and optimizes the crew's operating procedures, equipment operating status, and environmental configuration parameters. If new conflicts or risks are discovered during mission execution, the agent will re-optimize by adjusting decisions and updating the model to ensure the mission is carried out efficiently.

[0179] In this embodiment, the solution constructs an intelligent agent collaborative network involving crew, equipment, and the environment. By combining a reward mechanism that considers time consumption, conflict items, and risk items, the behavior of the agents is gradually trained and optimized. This allows for the optimization and adjustment of crew operating procedures, equipment operating status, and environmental configuration parameters. Through continuous feedback and adjustment, task execution efficiency is continuously improved, ensuring timely and efficient task completion.

[0180] The collaborative optimization method for ship mission operations provided in this application can be executed by a collaborative optimization device for ship mission operations. This application uses the example of a collaborative optimization device for ship mission operations executing the collaborative optimization method for ship mission operations to illustrate the collaborative optimization device for ship mission operations provided in this application.

[0181] This application also provides a collaborative optimization device for ship mission operations.

[0182] like Figure 2 As shown, the collaborative optimization device for the ship's mission operations includes: Acquisition module 210 is used to acquire the ship's operational tasks; The first processing module 220 is used to perform collaborative analysis on the task requirements of the operation based on the ship's operating environment and the crew's working characteristics, and to construct a multi-person-machine-environment collaborative model. The task requirements include visual task requirements, auditory task requirements, cognitive task requirements and motion task requirements. The second processing module 230 is used to simulate the task execution process of the operation task through the multi-person-machine-environment collaborative model and obtain simulation results. The simulation results include the task resources of the operation task and the collaborative operation efficiency between the crew, equipment and environment in the ship. The third processing module 240 is used to optimize the collaborative relationship of each element in the simulation result based on the task resources and the collaborative operation efficiency. The elements include the crew, equipment and environment corresponding to the operation task.

[0183] According to the collaborative optimization device for ship mission operations provided in the embodiments of this application, a multi-person-machine-environment collaborative model is constructed by combining ship operation environment information and crew work characteristics. The crew, equipment, and environment are regarded as three core interactive elements for collaborative modeling, simulating the collaborative relationship in the mission execution process, obtaining the resources required for the mission, analyzing the collaborative operation efficiency between crew, equipment, and environment, dynamically reflecting changes in mission requirements, crew operation status, and environmental conditions, quantitatively evaluating the performance of each link in mission execution, accurately identifying and optimizing potential collaborative imbalances or resource waste points, optimizing the collaborative relationship between crew, equipment, and environment, and improving the overall operational efficiency of the mission.

[0184] The collaborative optimization device for ship mission operations in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or any other device besides a terminal.

[0185] The collaborative optimization device for ship mission operations in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0186] The collaborative optimization device for ship mission operations provided in this application can realize the various processes implemented in the collaborative optimization method embodiments for ship mission operations as described above. To avoid repetition, these will not be repeated here.

[0187] In some embodiments, such as Figure 3 As shown, this application embodiment also provides an electronic device 300, including a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the program is executed by the processor 301, it implements the various processes of the above-described collaborative optimization method embodiment for ship mission operations and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0188] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0189] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described collaborative optimization method embodiment for ship mission operations and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0190] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0191] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-mentioned collaborative optimization method for ship mission operations.

[0192] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0193] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described ship mission operation collaborative optimization method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0194] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0195] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0196] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the collaborative optimization method for ship mission operations of various embodiments of this application.

[0197] In the description of this application, "first feature" and "second feature" may include one or more of the features.

[0198] In the description of this application, "multiple" means two or more.

[0199] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0200] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0201] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A collaborative optimization method for ship mission operations, characterized in that, include: Obtain the operational tasks of the ships; Based on the ship's operating environment information and the crew's work characteristics, the task requirements of the operation are analyzed collaboratively to construct a multi-person-machine-environment collaborative model. The task requirements include visual task requirements, auditory task requirements, cognitive task requirements, and kinematic task requirements. The task execution process of the operation is simulated using the multi-person-machine-environment collaborative model, and the simulation results are obtained. The simulation results include the task resources of the operation and the collaborative operation efficiency between the crew, equipment and environment in the ship. Based on the task resources and the collaborative operation efficiency, the collaborative relationship of each element in the simulation results is optimized. The elements include the crew, equipment, and environment corresponding to the operation task.

2. The collaborative optimization method for ship mission operations according to claim 1, characterized in that, Based on the ship's operational environment information and the crew's work characteristics, a collaborative analysis of the task requirements for the operational mission is conducted to construct a multi-person-machine-environment collaborative model, including: Based on the crew operation tasks, equipment operation tasks, and environmental requirements in the operation task, the operation task is decomposed into multiple sub-tasks. The crew operation tasks refer to the operational activities that the crew needs to perform manually in the task execution process. The equipment operation tasks are the operations that the equipment on the ship needs to perform according to the operation task. The environmental requirements are the specific environmental conditions required when the operation task is executed, including the human environment and the physical environment. By comparing and analyzing the work characteristics of the crew members with the task requirements of the sub-tasks, the crew members' ability to perform each sub-task is determined. Based on the execution capability and the work environment information, each element in the work task is configured collaboratively to determine the niche of the element. The niche is the position and role of the element in the multi-person-machine-environment collaborative model, as well as the way and scope of its interaction with other elements. Based on the dependencies and priorities among the multiple subtasks, the niche of the elements is adjusted to construct the multi-person-machine-ring collaborative model.

3. The collaborative optimization method for ship mission operations according to claim 2, characterized in that, The operational environment information includes equipment status and environmental parameters. The step of collaboratively configuring each element in the operational task based on the execution capability and the operational environment information, and determining the niche of each element, includes: Based on the equipment status and the environmental parameters, the operating requirements and performance limitations of the equipment are determined. The equipment status refers to the operating condition and performance of the equipment, including equipment availability, fault status, and performance indicators. The environmental parameters are environmental parameters that affect the execution of the task, including the natural environment and the electromagnetic environment. Based on the execution capability, determine the operating equipment, operating position, and work scope corresponding to each crew member; Based on the operational requirements, performance limitations, operating equipment, operating location, and work scope, determine the working rhythm and interaction frequency of the crew, the equipment, and the environment; Based on the working rhythm and the interaction frequency, the interaction relationships and energy flow patterns between the elements are analyzed to determine the ecological niche of each element.

4. The collaborative optimization method for ship mission operations according to claim 2, characterized in that, The step of adjusting the niche of the elements based on the dependencies and priorities among the multiple subtasks to construct the multi-user-machine-environment collaborative model includes: Based on the dependencies and priorities, determine the execution order and time constraints of each subtask; Based on the execution order and time constraints, an execution time window is allocated to each of the subtasks; Determine the crew's operating authority over specific equipment based on their performance capabilities and mission requirements; Based on the execution time window, the ship's resource limitations, and the operation permissions, resources are allocated to each subtask, and the subtasks are assigned to crew members with the corresponding permissions to obtain an allocation scheme. Obtain and analyze the execution feedback information corresponding to the allocation scheme, determine the element tasks and interaction methods of the element, and adjust the ecological niche of the element, the workload of the crew, and the operating parameters of the equipment; Based on the element tasks, the interaction methods, and the ecological niche, the multi-person-machine-environment collaborative model is constructed.

5. The collaborative optimization method for ship mission operations according to claim 1, characterized in that, The simulation of the task execution process of the job task using the multi-person-machine-environment collaborative model yields simulation results, including: The multi-person-machine-environment collaborative model is used to simulate the task execution process of the job, which includes multiple job stages. Based on the importance of task requirements in the aforementioned work process and the weight of resources in the task execution process, the task resources called in the task execution process are divided into resource units. The categories of resource units include key resources, auxiliary resources, and alternative resources. Based on the task execution process, a multi-level model is constructed according to the importance of the resource units, task dependencies, and dynamic scheduling requirements. Based on the multi-level model, the task resources are configured and scheduled to simulate the task execution process of the job. Based on the resource utilization information and task completion information of the simulated mission execution process, the collaborative operation efficiency between the crew, equipment and environment on the ship is calculated as the simulation result.

6. The collaborative optimization method for ship mission operations according to claim 5, characterized in that, The calculation of the collaborative operational efficiency between the crew, equipment, and environment on the ship based on resource utilization information and task completion information from the simulated task execution process includes: Obtain the first resource utilization information and the first task completion information of the resource unit corresponding to each of the aforementioned work stages; Based on the first resource utilization information and the first task completion information, the load balance status of the resource unit is determined to calculate the resource utilization rate. Based on the time constraints of the aforementioned work process, and with the goal of maximizing resource utilization, the task resources are reconfigured and scheduled until the load balance state reaches a preset balance threshold, thereby obtaining optimized second resource utilization information and second task completion information. The collaborative operation efficiency is calculated based on the second resource utilization information and the second task completion information.

7. The collaborative optimization method for ship mission operations according to any one of claims 1-6, characterized in that, The step of optimizing the collaborative relationship of each element in the simulation results based on the task resources and the collaborative operation efficiency includes: Based on the aforementioned collaborative operation efficiency analysis, the efficiency change trend among crew, equipment, and environment is analyzed; Based on the performance change trend and the task resources, identify the performance bottlenecks in the task execution process and the key influencing factors corresponding to the performance bottlenecks; Analyze the task execution process to determine the time loss corresponding to the key influencing factors, as well as conflict items and risk items; Based on the time loss, conflict items, and risk items, the crew's operating procedures, the equipment's operating status, and the environment's configuration parameters are optimized and adjusted to improve the collaborative relationship.

8. The collaborative optimization method for ship mission operations according to claim 7, characterized in that, The optimization and adjustment of the crew's operating procedures, the equipment's operating status, and the environmental configuration parameters based on the time loss, the conflict items, and the risk items includes: A collaborative network is constructed for the intelligent agents corresponding to the crew members, the equipment, and the environment; Based on the time loss, the conflict items, and the risk items, a reward mechanism for the collaborative network is set. Based on the reward mechanism, the agents in the collaborative network are trained to optimize the operation process, the running state, and the configuration parameters.

9. A collaborative optimization device for ship mission operations, characterized in that, include: The acquisition module is used to acquire the ship's operational tasks; The first processing module is used to perform collaborative analysis of the task requirements of the operation based on the ship's operating environment information and the crew's work characteristics, and to construct a multi-person-machine-environment collaborative model. The task requirements include visual task requirements, auditory task requirements, cognitive task requirements and motion task requirements. The second processing module is used to simulate the task execution process of the operation task through the multi-person-machine-environment collaborative model and obtain simulation results. The simulation results include the task resources of the operation task and the collaborative operation efficiency between the crew, equipment and environment in the ship. The third processing module is used to optimize the collaborative relationship of each element in the simulation result based on the task resources and the collaborative operation efficiency. The elements include the crew, equipment and environment corresponding to the operation task.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the collaborative optimization method for ship mission operations as described in any one of claims 1-8.

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