SLAM-Based Path Planning Method for the Auxiliary Spatial Map of Converter Stations

Abstract

The present invention is applicable to the technical field of operation and maintenance of converter stations, and provides a method for path planning of an auxiliary space map of a converter station based on SLAM. S1: The converter station management system is connected to the AR glasses through the WAPI protocol. The converter station management system uses SLAM technology to perform real-time mapping of the spatial environment of the converter station, and sets task priorities, estimated processing times, and locations for multiple maintenance / detection tasks based on the map data. S2: Use an algorithm to perform path search, and calculate the actual path cost g(n) and heuristic cost h(n) of each task. This method solves the problem that traditional systems cannot flexibly respond to changes in equipment status and the need for multi-task parallel processing in the face of real-time and complex converter station environments, achieving the purpose of optimizing path planning through SLAM and algorithms, dynamically adjusting task priorities and times, performing real-time conflict detection, improving the maintenance efficiency and accuracy of converter stations, and providing feedback guidance for operations through AR glasses.

Description

Technical Field

[0001] The present invention relates to the technical field of map path planning, and more specifically, it relates to a method for auxiliary spatial map path planning of a converter station based on SLAM. Background Art

[0002] As an important part of the power system, converter stations are widely used in high-voltage direct current transmission systems. Its main function is to convert alternating current into direct current, or convert direct current into alternating current, and connect to the power grid through converters to ensure the transmission and distribution of electricity. The operation and maintenance of converter stations are crucial for the stability and reliability of the power system. Therefore, regular maintenance and inspection work are essential. In modern converter stations, there are a wide variety of complex equipment, and maintenance tasks usually require inspection personnel to adopt different maintenance strategies according to the different conditions of the equipment to ensure that the equipment operates in the best state.

[0003] During the maintenance and inspection process of converter stations, AR glasses can display the status of equipment in real time, provide path planning information, and effectively assist operators in making quick decisions. Through AR glasses, users can overlay digital information in their field of vision, which makes AR glasses an important tool for on-site operation guidance, data visualization, and information feedback. However, traditional path planning and task management methods are difficult to handle complex equipment layouts, task priorities, and conflicts in maintenance time. Therefore, the intelligent assistance and efficient path planning technology combined with AR glasses are particularly important.

[0004] Existing path planning systems usually rely on static preset schemes or simple algorithms and lack dynamic task scheduling and conflict management. When facing the real-time and complex converter station environment, these traditional systems cannot flexibly respond to changes in equipment status and the requirements of multi-task parallel processing. Especially in an environment with a complex equipment layout and complicated maintenance tasks, traditional systems cannot effectively handle task priorities, estimated processing times, and possible conflicts between tasks, resulting in unnecessary path overlaps or time waste for maintenance personnel when performing tasks. In addition, the support for operators by traditional systems is relatively limited, lacking real-time information feedback and dynamic adjustment functions, and often unable to respond to on-site changes in a timely manner. Therefore, existing maintenance and inspection path planning schemes have obvious limitations when facing complex and dynamic working environments.

[0005] Therefore, the present invention proposes a method for auxiliary spatial map path planning of a converter station based on SLAM to solve the above problems. Summary of the Invention

[0006] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a method for auxiliary spatial map path planning of a converter station based on SLAM.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for path planning of an auxiliary spatial map of a converter station based on SLAM, comprising the following steps:

[0009] S1. The converter station management system is connected to the AR glasses through the WAPI protocol. The converter station management system uses SLAM technology to perform real-time mapping of the spatial environment of the converter station, and sets task priorities, estimated processing times, and locations for multiple maintenance / inspection tasks based on the map data;

[0010] S2. Use the A* algorithm to perform path search, calculate the actual path cost g(n) and heuristic cost h(n) of each task. Among them, the heuristic cost h(n) is comprehensively evaluated by the priority of the task, the estimated processing time, and the conflict with other tasks, and the conflict penalty term is used to avoid conflicts, and the calculation formula of h(n) is:

[0011] ;

[0012] Where, wpriority is the weight coefficient of the task priority Pn, wtime is the weight coefficient of the estimated processing time Tn, n is task n, m is task m, α is the conflict penalty coefficient, and Conflicting is a set of conflicting tasks;

[0013] S3. Evaluate the optimal path according to the path cost and heuristic cost of the task, and avoid conflicts between tasks;

[0014] S4. Output the processing order and corresponding start and end times of the maintenance / inspection tasks, and provide real-time path feedback to the operator through the AR glasses to guide the task execution order and coordination between tasks;

[0015] S5. Display the path planning result, task execution progress, and suggestions for dynamically adjusting the task order through the AR glasses to ensure smooth task execution and respond to environmental changes.

[0016] By adopting the above technical solutions, this method combines SLAM technology and A* path planning algorithm, can accurately construct the spatial map of the converter station, and optimize the path based on information such as the priority of the task, the estimated processing time, and the location. By dynamically calculating the path cost and heuristic cost of each task, it can intelligently evaluate the conflicts between tasks, and avoid path overlap through the conflict penalty term to ensure that tasks are executed in the optimal order. In addition, it can also monitor the task progress in real time, adjust the path planning in time, and avoid task lag. The operator obtains real-time path feedback and device information through the AR glasses, makes decisions directly in the field of vision, improves the accuracy and work efficiency of the operation, and thus greatly improves the maintenance and inspection work efficiency of the converter station.

[0017] The present invention is further configured such that: in the heuristic cost h(n), the weight coefficient wpriority of the task priority Pn and the weight coefficient wtime of the estimated processing time Tn can be dynamically adjusted according to the nature of the task, so as to balance the influence of priority and time according to actual requirements;

[0018] In the heuristic cost h(n), overlap_time(n,m) represents the overlapping part of task n and task m in terms of time. When two tasks are in the process of execution and there is an intersection between the start time and the end time, and the calculation formula of overlap_time(n,m) is:

[0019] ;

[0020] When, is the start time of task n, is the end time of task n, is the start time of task m, is the end time of task m.

[0021] The present invention is further configured such that: the calculation formula of the conflict penalty term penalty(n, m) between tasks is:

[0022] ;

[0023] Wherein, α is the conflict penalty coefficient, and overlap_time(n,m) is the overlapping time between task n and task m.

[0024] By adopting the above technical solution, the task priority, the estimated processing time and the conflict information between tasks are combined. By dynamically adjusting the weight coefficients, the influence of priority and time can be flexibly balanced according to the specific requirements of the tasks. The calculation of the heuristic cost h(n) not only considers the time and importance of the task itself, but also introduces the conflict penalty term between tasks, which can effectively avoid the overlap and conflict during the task execution process. This comprehensive calculation method enables the path planning to ensure the priority execution of high-priority tasks while avoiding the conflict between low-priority tasks and other tasks, thereby improving the efficiency and accuracy of task execution. In addition, the flexibility of the calculation formula enables the system to adapt to different types of tasks and different working environments, further optimizing the execution order and path selection of maintenance and detection tasks.

[0025] The present invention is further configured such that: the converter station management system includes:

[0026] The task management module is used to set the priorities, estimated processing times, and locations of multiple maintenance / detection tasks, and dynamically adjust the task priority weight coefficients and processing time weight coefficients to meet the balance requirements of priorities and times among tasks;

[0027] The path search module calculates the path cost g(n) and heuristic cost h(n) for each task based on the A* algorithm to generate the optimal path;

[0028] The monitoring module is used to monitor the progress of maintenance / detection tasks in real time to ensure that tasks are executed as planned. If it is found that the task progress lags or there are abnormalities, the task order and path are automatically adjusted;

[0029] The output module is used to output the task planning results, path information, and task execution instructions to the operator's AR glasses to facilitate the operator's real-time guidance and task execution;

[0030] The map update module is used to update the spatial map of the converter station in real time and provide real-time spatial information to the operator through the AR glasses to ensure the accuracy of path planning and task execution.

[0031] The present invention is further configured as: The path search module includes:

[0032] The task information receiving unit is used to receive and store the priorities, estimated processing times, locations, and conflict information between tasks of multiple maintenance / detection tasks from the task management module;

[0033] The path cost calculation unit is used to calculate the actual path cost g(n) of each task. The path cost is calculated through the distance between the spatial map constructed based on the SLAM technology and the current location of the task, and the shortest path algorithm is used to estimate the spatial distance between tasks;

[0034] The heuristic cost calculation unit is used to calculate the heuristic cost h(n) according to the priority of the task, the estimated processing time, and the conflict information with other tasks;

[0035] The path search unit is used to perform A* algorithm path search according to the calculated path cost g(n) and heuristic cost h(n), evaluate the optimal execution path of each task, and optimize the task execution order according to the priorities, processing times, and conflict situations between tasks;

[0036] The conflict detection unit is used to detect and identify conflicts between tasks in real time, especially during the path planning process, to avoid task overlap or path conflicts and ensure the smooth execution of tasks;

[0037] A path feedback unit, which is used to output the optimized task path and task sequence to the control system and provide them to the AR glasses of the operator, so as to ensure that the operator executes the task according to the path recommended by the system.

[0038] The present invention is further configured that: the monitoring module includes:

[0039] A task status acquisition unit, which is used to acquire the current status information of the maintenance / detection task, including task progress, execution time, equipment status and potential conflict situations;

[0040] A real-time monitoring unit, which is used to track the progress of task execution in real time, check whether the task is executed according to the predetermined plan, and monitor possible delays or progress lags;

[0041] An anomaly detection unit, which is used to detect possible anomalies during task execution, such as equipment failures, time conflicts, etc., and generate alarm information;

[0042] A task adjustment unit, which is used to automatically adjust the task sequence, path planning and execution time when anomalies occur during task execution, so as to ensure that the task continues to be executed according to the plan or the optimized plan;

[0043] A data feedback unit, which is used to feedback the task status information, progress report and anomaly situations to the task scheduling system, and display the status information to the AR glasses of the operator in real time, so as to ensure that the operator obtains real-time feedback and guidance.

[0044] The present invention is further configured that: the status information displayed by the data feedback unit to the AR glasses includes the current status of task execution, the execution sequence of the predetermined task, conflict prompts, and path adjustment guidelines.

[0045] The present invention is further configured that: the output module includes:

[0046] A task path generation unit, which is used to generate the optimal path for each task according to the path planning result, and the path information includes task execution sequence, estimated execution time, path distance, etc.;

[0047] A task execution instruction generation unit, which generates corresponding operation instructions according to the task execution plan to guide the operator to execute the task according to the task priority, schedule and path;

[0048] An AR output unit, which is used to transmit the generated path information and task execution instructions to the AR glasses worn by the operator in real time, and provide visual path planning and task guidance for the operator through the AR glasses, including direction guidance, task execution steps and time prompts;

[0049] A real-time adjustment functional unit is used to dynamically adjust the task execution order according to the status information fed back during the task execution, such as task progress, conflict situation, etc., and update the path information and task instructions to the operator in real time through the AR glasses to ensure the smooth completion of the task.

[0050] The present invention is further configured such that: the map update module uses SLAM technology to perform real-time scanning and modeling of the spatial environment of the converter station, constructs a dynamic spatial map of the converter station, and updates the spatial map in real time according to the changes of equipment and environment during the task execution, so as to ensure that the changes of the task path and equipment status can be reflected in the map in time.

[0051] The present invention is further configured such that: after the map update module provides the spatial map update, the path search module re-plans the task path to ensure that the task execution is not affected by the environmental changes, and provides new path guidance through the AR glasses.

[0052] In summary, the present application includes at least one of the following beneficial technical effects:

[0053] 1. The present application combines SLAM technology and A* path planning algorithm, can accurately construct the spatial map of the converter station, and optimize the path based on information such as task priority, estimated processing time, location, etc. By dynamically calculating the path cost and heuristic cost of each task, it can intelligently evaluate the conflicts between tasks, and avoid path overlap through the conflict penalty term to ensure that tasks are executed in the optimal order. In addition, it can also monitor the task progress in real time, adjust the path planning in time, and avoid task lag. The operator obtains real-time path feedback and device information through the AR glasses, makes decisions directly in the field of vision, improves the operation accuracy and work efficiency, and thus greatly improves the maintenance and detection work efficiency of the converter station.

[0054] 2. The path search module designed in the present application combines task priority, estimated processing time and task conflict information. By dynamically adjusting the weight coefficient, it can flexibly balance the influence of priority and time according to the specific requirements of the task. The calculation of the heuristic cost h(n) not only considers the time and importance of the task itself, but also introduces the conflict penalty term between tasks, which can effectively avoid overlap and conflict during the task execution. This comprehensive calculation method enables the path planning to ensure the priority execution of high-priority tasks while avoiding conflicts between low-priority tasks and other tasks, thereby improving the efficiency and accuracy of task execution. In addition, the flexibility of the calculation formula enables the system to adapt to different types of tasks and different working environments, and further optimizes the execution order and path selection of maintenance and detection tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the modules of the converter station management system in the present invention. Specific Embodiments

[0056] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0057] It should be pointed out that, unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0058] Please refer to Figure 1 , the present invention provides the following technical solutions:

[0059] Embodiment 1, a method for path planning of an auxiliary spatial map of a converter station based on SLAM, includes the following steps:

[0060] S1. The converter station management system is connected to the AR glasses through the WAPI protocol. The converter station management system uses SLAM technology to perform real-time mapping of the spatial environment of the converter station, and sets task priorities, estimated processing times, and locations for multiple maintenance / detection tasks based on the map data;

[0061] It should be noted that through the WAPI protocol, the AR glasses can perform real-time data exchange with the converter station management system, and ensure that the operator can obtain instant task information and spatial feedback. The converter station management system uses spatial data for task scheduling and path planning, and combines augmented reality technology (AR) to provide real-time operation guidance for the inspection personnel.

[0062] S2. Use the A* algorithm to perform path search, calculate the actual path cost g(n) and heuristic cost h(n) of each task. Among them, the heuristic cost h(n) is comprehensively evaluated by the task priority, estimated processing time, and conflicts with other tasks, and conflict penalties are used to avoid conflicts, and the calculation formula of h(n) is:

[0063]

[0064] Where wpriority and wtime are the weight coefficients of the task priority Pn and the estimated processing time Tn respectively, n is task n, m is task m, α is the conflict penalty coefficient, and Conflicting is a set of conflicting tasks. These weight coefficients are used for dynamic adjustment to balance the influence of task priority and time, and ensure that the path planning meets the task priority while not causing unnecessary delays due to long-term processing of tasks. The setting of the weight coefficients is based on the nature and actual requirements of the tasks, and can be dynamically adjusted according to the actual scenario.

[0065] Pn is the priority of task n. Each task is assigned a priority value according to its importance and urgency. Tasks with higher priorities need to be processed first.

[0066] Tn is the estimated processing time of task n (this estimated processing time is predicted based on the average time required for task n previously). This value represents the time required to complete the task and is used to evaluate the impact of the task on the total working time. The longer the estimated processing time, the greater the interference of the task on the overall scheduling.

[0067] The heuristic cost h(n) is designed to ensure that during the task planning process, tasks with high priorities and short completion times are given priority, while avoiding conflicts between tasks. By introducing a conflict penalty term, the system can automatically avoid situations where task overlapping times are too long, prevent task conflicts and resource waste in the system, and improve the efficiency and accuracy of task execution.

[0068] S3. Evaluate the optimal path based on the path cost and heuristic cost of the task to avoid conflicts between tasks;

[0069] S4. Output the processing order of the repair / detection tasks and the corresponding start and end times, and provide real-time path feedback to the operator through AR glasses to guide the task execution order and coordination between tasks;

[0070] S5. Display the path planning results, task execution progress, and suggestions for dynamically adjusting the task order through AR glasses to ensure smooth task execution and respond to environmental changes.

[0071] Specifically, in the heuristic cost h(n), the weight coefficient wpriority of the task priority Pn and the weight coefficient wtime of the estimated processing time Tn can be dynamically adjusted according to the nature of the task to balance the influence of priority and time according to actual needs; specifically, the adjustment of the weight coefficients of the task priority Pn and the estimated processing time Tn should consider the urgency, importance, equipment failure risk, and changes in the working environment of the task. For example, in an emergency repair task, a higher priority may require a larger weight coefficient to ensure that the task can be executed first; while in a general regular inspection, the estimated processing time Tn of the task may occupy a greater weight to optimize the overall working time and path planning efficiency. By dynamically adjusting these weight coefficients, the path planning system can more flexibly handle various different repair tasks, ensure efficient task scheduling in a complex environment, and thus achieve the best execution order and shortest execution time of tasks.

[0072] In the heuristic cost h(n), overlap_time(n,m) represents the overlapping part of task n and task m in terms of time. When two tasks are in execution and there is an intersection between their start times and end times, the calculation formula for overlap_time(n,m) is as follows:

[0073] ;

[0074] When, is the start time of task n, is the end time of task n, is the start time of task m, is the end time of task m. The overlapping time usually means that tasks n and m need to share the same resources (such as personnel, equipment, space, etc.). If these tasks are carried out simultaneously, they may cause conflicts, resulting in a decline in efficiency or delays.

[0075] Furthermore, the calculation formula for the conflict penalty term penalty(n, m) between tasks is:

[0076] ;

[0077] Among them, α is the conflict penalty coefficient, which quantifies the negative impact caused by the overlapping time. overlap_time(n,m) is the overlapping time between task n and task m, and it is an important measure to evaluate the time conflict between tasks. It helps the path planning algorithm to identify and avoid the overlap between tasks when optimizing task scheduling, so as to ensure an efficient and conflict-free task execution order.

[0078] In this embodiment, the method for path planning of the auxiliary space map of the converter station based on SLAM is realized by connecting the converter station management system with the AR glasses. Among them, the converter station management system includes:

[0079] A task management module, which is used to set the priorities, estimated processing times, and locations of multiple maintenance / detection tasks, and dynamically adjust the task priority weight coefficient and the processing time weight coefficient to adapt to the balance requirements of priorities and times between tasks;

[0080] A path search module, which calculates the path cost g(n) and the heuristic cost h(n) of each task based on the A* algorithm to generate an optimal path;

[0081] A monitoring module, which is used to monitor the progress of maintenance / detection tasks in real time to ensure that tasks are executed according to the plan. If it is found that the task progress lags behind or there are abnormalities, it will automatically adjust the task order and path;

[0082] An output module, which is used to output the task planning result, path information, and task execution instructions to the operator's AR glasses for the operator to perform real-time guidance and execute tasks.

[0083] A map update module, which is used to update the spatial map of the converter station in real time and provide real-time spatial information to the operator through the AR glasses to ensure the accuracy of path planning and task execution.

[0084] The map update module uses SLAM technology to scan and model the spatial environment of the converter station in real time, construct a dynamic spatial map of the converter station, and update the spatial map in real time according to the changes of equipment and environment during the task execution to ensure that the changes of task paths and equipment status can be reflected in the map in time. After the map update module provides the spatial map update, the path search module re-plans the task path to ensure that the task execution is not affected by environmental changes and provides new path guidance through the AR glasses.

[0085] Specifically, the path search module includes:

[0086] A task information receiving unit, which is used to receive and store the priorities, estimated processing times, locations, and conflict information between multiple maintenance / detection tasks from the task management module; through the effective storage and sorting of this information, the task information receiving unit can provide accurate data support for subsequent path planning and optimization to ensure the efficient operation of the task management system.

[0087] A path cost calculation unit, which is used to calculate the actual path cost g(n) of each task. The path cost is calculated by the distance between the spatial map constructed based on SLAM technology and the current task location, and the shortest path algorithm is used to estimate the spatial distance between tasks.

[0088] A heuristic cost calculation unit, which is used to calculate the heuristic cost h(n) according to the priorities, estimated processing times, and conflict information with other tasks of the task; the calculation of the heuristic cost not only considers the characteristics of the task itself but also adjusts according to the conflict situation between tasks to ensure the rationality and efficiency of task scheduling.

[0089] A path search unit, which is used to perform A* algorithm path search according to the calculated path cost g(n) and heuristic cost h(n), evaluate the optimal execution path of each task, and optimize the task execution order according to the priorities, processing times, and conflict situations between tasks; optimize the task execution order, avoid conflicts between tasks, and improve the efficiency and accuracy of path planning. This process ensures the rationality of the task execution order, effectively reduces the overlap and conflict between tasks, and improves the task execution efficiency.

[0090] The conflict detection unit is used to detect and identify conflicts between tasks in real time, especially during the path planning process, to avoid task overlap or path conflicts and ensure smooth execution of tasks. If a conflict is detected, the system will make adjustments, automatically replan the path or adjust the order of task execution to avoid interference between tasks and waste of resources, thereby ensuring the smooth completion of the task.

[0091] The path feedback unit is used to output the optimized task path and task sequence to the control system and provide it to the operator's AR glasses to ensure that the operator performs the task according to the path recommended by the system. Through AR glasses, operators can obtain real-time guidance on path planning on site, and the system can overlay digital path information in the operator's field of view, clearly marking the start and end positions and execution order of each task. This real-time path feedback can help operators quickly understand the overall picture of task execution, effectively reduce operational errors, improve task execution efficiency, and minimize time waste and resource competition caused by path conflicts.

[0092] Specifically, the monitoring module includes:

[0093] Task status collection unit, used to collect the current status information of maintenance / inspection tasks, including task progress, execution time, equipment status and potential conflicts;

[0094] Real-time monitoring unit, used to track the progress of task execution in real time, check whether the task is executed according to the predetermined plan, and monitor possible delays or progress lags;

[0095] Anomaly detection unit, used to detect abnormal situations that may occur during task execution, such as equipment failure, time conflict, etc., and generate alarm information;

[0096] The task adjustment unit is used to automatically adjust the task sequence, path planning and execution time when an exception occurs during the task execution process to ensure that the task continues to be executed according to the plan or optimized plan;

[0097] The data feedback unit is used to feed back task status information, progress reports and abnormal situations to the task scheduling system, and display status information to the operator's AR glasses in real time to ensure that the operator receives real-time feedback and guidance.

[0098] The data feedback unit displays status information to the AR glasses, including the current status of task execution, the execution order of scheduled tasks, conflict prompts, and path adjustment instructions.

[0099] Output modules include:

[0100] A task path generation unit, which is used to generate the optimal path for each task according to the path planning result. The path information includes the task execution order, estimated execution time, path distance, etc.;

[0101] A task execution instruction generation unit, which generates corresponding operation instructions according to the task execution plan to guide the operator to execute tasks according to the task priority, schedule and path;

[0102] An AR output unit, which is used to transmit the generated path information and task execution instructions to the AR glasses worn by the operator in real time, and provide visual path planning and task guidance for the operator through the AR glasses, including direction guidance, task execution steps and time prompts;

[0103] A real-time adjustment function unit, which is used to dynamically adjust the task execution order according to the status information fed back during the task execution process, such as task progress, conflict situation, etc., and update the path information and task instructions to the operator in real time through the AR glasses to ensure the smooth completion of the task.

[0104] In summary, the converter station auxiliary space map path planning method based on SLAM combines SLAM technology and A* path planning algorithm, can accurately construct the space map of the converter station, and optimize the path based on information such as task priority, estimated processing time, location, etc. By dynamically calculating the path cost and heuristic cost of each task, it can intelligently evaluate the conflicts between tasks, and avoid path overlap through the conflict penalty term to ensure that tasks are executed in the optimal order. In addition, it can also monitor the task progress in real time, adjust the path planning in time, and avoid task lag. The operator obtains real-time path feedback and device information through the AR glasses, makes decisions directly in the field of vision, improves the accuracy and work efficiency of the operation, and thus greatly improves the maintenance and inspection work efficiency of the converter station.

[0105] The device embodiments described above are only illustrative and not all embodiments. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Claims

1. A converter station auxiliary space map path planning method based on SLAM, characterized by: The following steps are involved: S1. The converter station management system is connected to the AR glasses through the WAPI protocol. The converter station management system uses SLAM technology to build a real-time map of the converter station's spatial environment and sets task priorities, estimated processing time and locations for multiple maintenance / inspection tasks based on map data. S2. Use the A* algorithm to search for paths and calculate the actual path cost g(n) and heuristic cost h(n) of each task. The heuristic cost h(n) is comprehensively evaluated by the task priority, estimated processing time, and conflict with other tasks, and conflicts are avoided through conflict penalty items. The calculation formula of h(n) is: ； Among them, wpriority is the weight coefficient of task priority Pn, wtime is the weight coefficient of expected processing time Tn, n is task n, m is task m, α is the conflict penalty coefficient, and Conflicting is a set of conflicting tasks; S3, evaluate the optimal path based on the path cost and heuristic cost of the task to avoid conflicts between tasks; S4: Output the processing sequence and corresponding start and end time of maintenance / inspection tasks, and provide real-time path feedback to operators through AR glasses to guide the task execution sequence and coordination between tasks; S5. Use AR glasses to display path planning results, task execution progress, and suggestions for dynamically adjusting the task sequence to ensure smooth task execution and cope with environmental changes; In the heuristic cost h(n), the weight coefficient wpriority of the task priority Pn and the weight coefficient wtime of the estimated processing time Tn can be dynamically adjusted according to the nature of the task to balance the impact of priority and time according to actual needs; In the heuristic cost h(n), overlap_time(n,m) represents the time overlap between task n and task m. When two tasks are being executed, their start time and end time have an intersection, and the calculation formula of overlap_time(n,m) is: ； in, is the start time of task n, is the end time of task n, is the start time of task m, is the end time of task m.

2. The converter station auxiliary space map path planning method based on SLAM according to claim 1 is characterized in that: The calculation formula of the conflict penalty term penalty(n,m) between the tasks is: ； Among them, α is the conflict penalty coefficient, and overlaptime(n, m) is the overlapping time between task n and task m.

3. The converter station auxiliary space map path planning method based on SLAM according to claim 1 is characterized in that: The converter station management system comprises: Task management module, used to set the priority, estimated processing time and location of multiple maintenance / inspection tasks, and dynamically adjust the task priority weight coefficient and processing time weight coefficient to meet the balance requirements between task priorities and time; The path search module calculates the path cost g(n) and heuristic cost h(n) of each task based on the A* algorithm to generate the optimal path; The monitoring module is used to monitor the progress of maintenance / inspection tasks in real time to ensure that the tasks are executed as planned. If the task progress is found to be lagging behind or abnormal, the task sequence and path will be automatically adjusted; An output module, which is used to output the task planning results, path information and task execution instructions to the operator's AR glasses, so that the operator can provide real-time guidance and execute tasks; The map update module is used to update the spatial map of the converter station in real time and provide real-time spatial information to operators through AR glasses to ensure the accuracy of path planning and task execution.

4. The converter station auxiliary space map path planning method based on SLAM according to claim 3 is characterized in that: The path search module includes: A task information receiving unit, used to receive and store the priority, estimated processing time, location and conflict information between multiple maintenance / detection tasks from the task management module; The path cost calculation unit is used to calculate the actual path cost g(n) of each task. The path cost is calculated by the distance between the spatial map built based on SLAM technology and the current position of the task. The shortest path algorithm is used to estimate the spatial distance between tasks. A heuristic cost calculation unit, used to calculate the heuristic cost h(n) according to the priority of the task, the estimated processing time and the conflict information with other tasks; The path search unit is used to perform A* algorithm path search based on the calculated path cost g(n) and heuristic cost h(n), evaluate the optimal execution path for each task, and optimize the task execution order based on the priority, processing time and conflict between tasks; The conflict detection unit is used to detect and identify conflicts between tasks in real time, especially in the path planning process, to avoid task overlap or path conflicts and ensure smooth execution of tasks; The path feedback unit is used to output the optimized task path and task sequence to the control system and provide them to the operator's AR glasses to ensure that the operator performs the task according to the path recommended by the system.

5. The converter station auxiliary space map path planning method based on SLAM according to claim 3 is characterized in that: The monitoring module comprises: Task status collection unit, used to collect the current status information of maintenance / inspection tasks, including task progress, execution time, equipment status and potential conflicts; Real-time monitoring unit, used to track the progress of task execution in real time, check whether the task is executed according to the predetermined plan, and monitor possible delays or progress lags; Anomaly detection unit, used to detect abnormal situations that may occur during task execution and generate alarm information; The task adjustment unit is used to automatically adjust the task sequence, path planning and execution time when an exception occurs during the task execution process to ensure that the task continues to be executed according to the plan or optimized plan; The data feedback unit is used to feed back task status information, progress reports and abnormal situations to the task scheduling system, and display status information to the operator's AR glasses in real time to ensure that the operator receives real-time feedback and guidance.

6. The converter station auxiliary space map path planning method based on SLAM according to claim 5 is characterized in that: The data feedback unit displays status information to the AR glasses, including the current status of task execution, the execution order of scheduled tasks, conflict prompts, and path adjustment instructions.

7. The converter station auxiliary space map path planning method based on SLAM according to claim 3 is characterized in that: The output module comprises: A task path generation unit is used to generate the optimal path for each task based on the path planning results. The path information includes the task execution order, estimated execution time, and path distance. The task execution instruction generation unit generates corresponding operation instructions according to the task execution plan and guides operators to execute tasks according to task priority, schedule and path; The AR output unit is used to transmit the generated path information and task execution instructions to the AR glasses worn by the operator in real time, and provide the operator with visual path planning and task guidance through the AR glasses, including direction guidance, task execution steps and time prompts; The real-time adjustment functional unit is used to dynamically adjust the task execution order according to the status information fed back during the task execution process, and update the path information and task instructions to the operator in real time through AR glasses to ensure the smooth completion of the task.

8. The converter station auxiliary space map path planning method based on SLAM according to claim 3 is characterized by: The map update module uses SLAM technology to scan and model the spatial environment of the converter station in real time, construct a dynamic spatial map of the converter station, and update the spatial map in real time according to changes in equipment and environment during task execution, ensuring that changes in task paths and equipment status can be reflected in the map in a timely manner.

9. The converter station auxiliary space map path planning method based on SLAM according to claim 8 is characterized in that: After the map update module provides a spatial map update, the path search module replans the task path to ensure that task execution is not affected by environmental changes and provides new path guidance through AR glasses.

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