Converter station auxiliary space map path planning method based on SLAM

Abstract

The invention is suitable for the technical field of converter station operation and maintenance, and provides a converter station auxiliary space map path planning method based on SLAM, and the method comprises the steps: S1, connecting a converter station management system with AR glasses through a WAPI protocol, and enabling the converter station management system to carry out the real-time mapping of the space environment of a converter station through the SLAM technology, setting task priorities, predicted processing time and positions for the plurality of maintenance / detection tasks based on the map data; s2, performing path search by using a # imgabs0 # algorithm, and calculating an actual path cost g (n) and a heuristic cost h (n) of each task; according to the method, the problem that a traditional system cannot flexibly cope with the change of the equipment state and the requirement of multi-task parallel processing when facing a real-time and complex converter station environment is solved, and the purposes of optimizing path planning, dynamically adjusting the task priority and time, carrying out real-time conflict detection, improving the maintenance efficiency and accuracy of the converter station and reducing the maintenance cost are achieved through the SLAM and # imgabs1 # algorithms. And the AR glasses are used for feeding back and guiding the operation.

Description

Technical Field

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

[0002] As an important component of the power system, converter stations are widely used in high-voltage direct current transmission systems. Their main function is to convert AC into DC, or DC into AC, and connect to the grid through converters to ensure the transmission and distribution of electricity. The operation and maintenance of converter stations are crucial to the stability and reliability of the power system, so regular maintenance and inspection are indispensable. In modern converter stations, the equipment is diverse and complex, and maintenance tasks usually require inspectors to adopt different maintenance strategies according to the different conditions of the equipment to ensure that the equipment operates in the best condition.

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

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

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

[0006] In view of the deficiencies in the prior art, the object of the present invention is to provide a converter station auxiliary space map path planning method based on SLAM.

[0007] To achieve the above object, the present invention provides the following technical solutions: The converter station auxiliary space map path planning method based on SLAM includes the following steps: 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 algorithm performs path search and calculates 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 respond to environmental changes.

[0008] By adopting the above technical solution, this method combines SLAM technology and The path planning algorithm can accurately construct a spatial map of the converter station and optimize the path based on task priority, estimated processing time, location and other information. By dynamically calculating the path cost and heuristic cost of each task, it can intelligently evaluate conflicts between tasks and avoid path overlap through conflict penalty items to ensure that tasks are executed in the optimal order. In addition, it is also possible to monitor task progress in real time and adjust path planning in a timely manner to avoid task delays. Operators obtain real-time path feedback and equipment information through AR glasses and make decisions directly in their field of view, which improves the accuracy and efficiency of operations, thereby greatly improving the maintenance and inspection efficiency of the converter station.

[0009] The present invention is further configured as follows: 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 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: ; When among them, 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.

[0010] The present invention is further configured as follows: the conflict penalty term between the tasks The calculation formula is: ; in, is the conflict penalty coefficient, is the overlap time between task n and task m.

[0011] By adopting the above technical solution, combining task priority, estimated processing time and conflict information between tasks, and dynamically adjusting the weight coefficient, the impact of priority and time can be flexibly balanced according to the specific needs of the task. The calculation of the heuristic cost h(n) not only takes into account the time and importance of the task itself, but also introduces conflict penalty items between tasks, which can effectively avoid overlap and conflict during task execution. This comprehensive calculation method enables path planning to ensure that high-priority tasks are executed first 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 allows the system to adapt to different types of tasks and different working environments, further optimizing the execution order and path selection of maintenance and inspection tasks.

[0012] The present invention is further configured as follows: 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; Path search module, based on The algorithm calculates the path cost g(n) and heuristic cost h(n) of each task and generates 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.

[0013] The present invention is further configured as follows: the path search module comprises: 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.

[0014] The present invention is further configured as follows: 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, such as equipment failure, time conflict, etc., 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.

[0015] The present invention is further configured as follows: the status information displayed by the data feedback unit to the AR glasses includes the current status of task execution, the execution order of predetermined tasks, conflict prompts, and path adjustment instructions.

[0016] The present invention is further configured as follows: the output module comprises: The 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, path distance, etc. 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, such as task progress, conflict conditions, etc., 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.

[0017] The present invention is further configured as follows: 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.

[0018] The present invention is further configured such that: after the map update module provides a spatial map update, the path search module re-plans the task path to ensure that task execution is not affected by environmental changes, and provides new path guidance through AR glasses.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application combines SLAM technology and The path planning algorithm can accurately construct a spatial map of the converter station and optimize the path based on task priority, estimated processing time, location and other information. By dynamically calculating the path cost and heuristic cost of each task, it can intelligently evaluate conflicts between tasks and avoid path overlap through conflict penalty items to ensure that tasks are executed in the optimal order. In addition, it is also possible to monitor task progress in real time and adjust path planning in a timely manner to avoid task delays. Operators obtain real-time path feedback and equipment information through AR glasses and make decisions directly in their field of view, which improves the accuracy and efficiency of operations, thereby greatly improving the maintenance and inspection efficiency of the converter station.

[0020] 2. The path search module designed in this application combines task priority, estimated processing time, and conflict information between tasks. By dynamically adjusting the weight coefficient, it can flexibly balance the impact of priority and time according to the specific needs of the task. The calculation of the heuristic cost h(n) not only takes into account the time and importance of the task itself, but also introduces conflict penalty items between tasks, which can effectively avoid overlaps and conflicts during task execution. This comprehensive calculation method enables path planning to ensure that high-priority tasks are executed first 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 allows the system to adapt to different types of tasks and different working environments, further optimizing the execution order and path selection of maintenance and inspection tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a module schematic diagram of the converter station management system in the present invention. DETAILED DESCRIPTION

[0022] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meanings as commonly understood by ordinary technicians in the technical field to which this application belongs.

[0024] See also Figure 1 , the present invention provides the following technical solutions: Embodiment 1, a converter station auxiliary space map path planning method based on SLAM, comprises the following steps: 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. It should be noted that through the WAPI protocol, AR glasses can exchange real-time data with the converter station management system and ensure that operators 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 inspection personnel.

[0025] S2. Use The algorithm performs path search and calculates 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: ; in, , are the weight coefficients of task priority Pn and 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. These weight coefficients are used for dynamic adjustment to balance the impact of task priority and time, ensuring that path planning will not cause unnecessary delays due to long task processing time while meeting task priority. The setting of weight coefficients depends on the nature of the task and actual needs, and can be dynamically adjusted according to the actual scenario.

[0026] Pn is the priority of task n. Each task is assigned a priority value based on its importance and urgency. Tasks with high priority need to be processed first.

[0027] Tn is the estimated processing time of task n (this estimated processing time is predicted based on the average time previously required for task n). This value represents the time required to complete a task and is used to assess the impact of a task on the total working time. The longer the estimated processing time, the greater the disruption of the task to the overall scheduling.

[0028] The purpose of designing the heuristic cost h(n) is to ensure that in the task planning process, high-priority tasks that require a shorter time to complete are given priority, while avoiding conflicts between tasks. By introducing conflict penalty items, the system can automatically avoid situations where tasks overlap for too long, avoid task conflicts and resource waste in the system, and improve the efficiency and accuracy of task execution.

[0029] 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 respond to environmental changes.

[0030] Specifically, in the heuristic cost h(n), the weight coefficient of the task priority Pn is and the weight coefficient of the estimated processing time Tn It can be dynamically adjusted according to the nature of the task to balance the impact 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 take into account the urgency and importance of the task, the risk of equipment failure, and changes in the working environment. For example, in emergency maintenance tasks, higher priorities may require larger weight coefficients to ensure that the task can be executed first; while in general regular inspections, the estimated processing time Tn of the task may occupy a larger weight to optimize the overall working time and path planning efficiency. By dynamically adjusting these weight coefficients, the path planning system can respond to various maintenance tasks more flexibly, ensuring efficient completion of task scheduling in complex environments, thereby achieving the best execution order and shortest execution time of tasks.

[0031] In the heuristic cost h(n), Indicates the time overlap between task n and task m. When two tasks are being executed, their start and end times overlap, and The calculation formula is: ; When among them, 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. Overlapping time usually means that task n and task m need to share the same resources (such as people, equipment, space, etc.). If these tasks are carried out at the same time, they may cause conflicts, resulting in reduced efficiency or delays.

[0032] Furthermore, the conflict penalty between tasks The calculation formula is: ; in, is the conflict penalty coefficient, which quantifies the negative impact of the overlap time. is the overlap time between task n and task m, and is an important measure of the time conflict between tasks. It helps the path planning algorithm identify and avoid overlaps between tasks when optimizing task scheduling to ensure efficient and conflict-free task execution order.

[0033] In this embodiment, a converter station auxiliary space map path planning method based on SLAM is implemented by connecting a converter station management system with AR glasses, wherein the converter station management system includes: 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; Path search module, based on The algorithm calculates the path cost g(n) and heuristic cost h(n) of each task and generates 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; Output module: The output module 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.

[0034] The map update module uses SLAM technology to scan and model the space environment of the converter station in real time, build a dynamic space map of the converter station, and update the space map in real time according to the changes in equipment and environment during the task execution, ensuring that changes in the task path and equipment status can be reflected in the map in a timely manner. After the map update module provides space map updates, the path search module replans the task path to ensure that the task execution is not affected by environmental changes, and provides new path guidance through AR glasses.

[0035] Specifically, the path search module includes: The task information receiving unit is used to receive and store the priority, estimated processing time, location and conflict information between multiple maintenance / inspection tasks from the task management module; through the effective storage and organization of this information, the task information receiving unit can provide accurate data support for subsequent path planning and optimization, ensuring the efficient operation of the task management system.

[0036] 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. The heuristic cost calculation unit is used to calculate the heuristic cost h(n) based on the task priority, estimated processing time and conflict information with other tasks; the calculation of the heuristic cost not only takes into account the characteristics of the task itself, but also makes adjustments based on the conflict between tasks to ensure the rationality and efficiency of task scheduling.

[0037] 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; optimize the execution order of tasks, 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 execution efficiency of tasks.

[0038] 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.

[0039] 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.

[0040] Specifically, the monitoring module includes: 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, such as equipment failure, time conflict, etc., 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.

[0041] 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.

[0042] Output modules include: The 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, path distance, etc. 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, such as task progress, conflict conditions, etc., 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.

[0043] In summary, the SLAM-based converter station auxiliary space map path planning method combines SLAM technology and A* path planning algorithm, which can accurately construct the space map of the converter station and optimize the path based on task priority, estimated processing time, location and other information. By dynamically calculating the path cost and heuristic cost of each task, it can intelligently evaluate the conflicts between tasks, avoid path overlap through conflict penalty items, and ensure that tasks are executed in the optimal order. In addition, it is also possible to monitor the progress of tasks in real time, adjust path planning in time, and avoid task delays. Operators obtain real-time path feedback and equipment information through AR glasses, and make decisions directly in the field of vision, which improves the accuracy and work efficiency of operations, thereby greatly improving the maintenance and inspection efficiency of converter stations.

[0044] The device embodiments described above are merely illustrative and are 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 example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces, indirect coupling or communication connection of devices or units, which may be electrical, mechanical or other forms. All other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection 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 algorithm performs path search and calculates 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 respond to environmental changes.

2. The converter station auxiliary space map path planning method based on SLAM according to claim 1 is characterized in 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 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: ； Among them, 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.

3. The converter station auxiliary space map path planning method based on SLAM according to claim 2 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 overlap_time(n,m) is the overlap time between task n and task m.

4. 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; Path search module, based on The algorithm calculates the path cost g(n) and heuristic cost h(n) of each task and generates 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.

5. The converter station auxiliary space map path planning method based on SLAM according to claim 4 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 path search based on the calculated path cost g(n) and heuristic cost h(n). Algorithmic path search, evaluates the optimal execution path for each task, and optimizes 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.

6. The converter station auxiliary space map path planning method based on SLAM according to claim 4 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, such as equipment failure, time conflict, etc., 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.

7. The converter station auxiliary space map path planning method based on SLAM according to claim 6 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.

8. The converter station auxiliary space map path planning method based on SLAM according to claim 4 is characterized in that: The output module comprises: The 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, path distance, etc. 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, such as task progress, conflict conditions, etc., 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.

9. The converter station auxiliary space map path planning method based on SLAM according to claim 4 is characterized in that: 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.

10. The converter station auxiliary space map path planning method based on SLAM according to claim 9 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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