A mechanical dog patrol inspection method, system, device and storage medium

Abstract

The present application provides a mechanical dog patrol method, system, device and storage medium, relating to the technical field of patrol inspection. The method includes: obtaining the first aircraft position information of the first parking position in the airport and the first position of the first parking position; obtaining the second aircraft position information of the second parking position and the second position of the second parking position; combining the first position, the second position, the first aircraft position information and the second aircraft position information to determine the patrol inspection order of each parking position in the airport; obtaining the positions of multiple mechanical dogs in the airport and the remaining power of each mechanical dog; combining the positions of each mechanical dog, the remaining power of each mechanical dog and the patrol inspection order of each parking position in the airport to generate the patrol inspection routes of each mechanical dog. The technical effect of the present application is: reasonably allocating patrol inspection resources and improving the patrol inspection efficiency of each parking position in the airport.

Description

Technical Field

[0001] This application relates to the technical field of patrol inspection, and specifically relates to a mechanical dog patrol inspection method, system, device, and storage medium. Background Art

[0002] With the rapid development of the civil aviation industry, the complexity of airport operation and management has been continuously increasing. Among them, how to efficiently conduct patrol inspections and management of airport parking positions is a technical problem that urgently needs to be solved. The traditional manual patrol inspection method not only consumes time and effort, but is also easily affected by human factors, making it difficult to ensure the comprehensiveness and timeliness of patrol inspections. This method is difficult to meet the fast-paced and high-density operation requirements of modern airports, and it is impossible to promptly detect and handle potential safety hazards, thus affecting the operation efficiency and safety of the airport.

[0003] To solve this problem, some airports currently adopt mechanical patrol inspection equipment with fixed routes, such as automatic patrol inspection robots or unmanned vehicles. Although this method improves the patrol inspection efficiency and coverage to a certain extent, the fixed patrol inspection route cannot be dynamically adjusted according to the real-time situation of the airport, resulting in some areas being repeatedly patrolled while other areas are not inspected in a timely manner, uneven distribution of patrol inspection resources, and low patrol inspection efficiency. Summary of the Invention

[0004] This application provides a mechanical dog patrol inspection method for reasonably allocating patrol inspection resources and improving the patrol inspection efficiency of each parking position in the airport.

[0005] In a first aspect, this application provides a mechanical dog patrol inspection method, which includes: obtaining the first aircraft position information of the first parking position in the airport and the first position of the first parking position; where the first parking position is a parking position with an aircraft, and the first aircraft position information is the departure time of the aircraft at the first parking position; obtaining the second aircraft position information of the second parking position and the second position of the second parking position; where the second parking position is a parking position without an aircraft, and the second aircraft position information is the occupied time of the second parking position; combining the first position, the second position, the first aircraft position information, and the second aircraft position information to determine the patrol inspection order of each parking position in the airport; obtaining the positions of multiple mechanical dogs in the airport and the remaining power of each mechanical dog; combining the positions of each mechanical dog, the remaining power of each mechanical dog, and the patrol inspection order of each parking position in the airport to generate the patrol inspection routes of each mechanical dog.

[0006] By adopting the above technical solution, through comprehensively considering multi-dimensional information such as the real-time status of parking positions in the airport, the departure time of the aircraft, the occupancy of parking positions, and the position and power of the robotic dog, the intelligent allocation and optimization of inspection resources are achieved. The method first obtains the relevant information of the first parking position with an aircraft and the second parking position without an aircraft, including position and time data, and then determines the inspection sequence of the entire airport based on this information. Subsequently, the method further considers the real-time positions and remaining power of multiple robotic dogs, and combines the determined inspection sequence to generate an optimized inspection route for each robotic dog. This dynamically adjusted method can effectively improve the inspection efficiency, avoid repeated inspections or omission of important areas, and at the same time ensure the power management of the robotic dog, reducing inspection interruptions caused by insufficient power. Through this comprehensive and flexible inspection strategy, the method can adapt to the complex and changeable operating environment of the airport, reasonably allocate inspection resources, improve the inspection efficiency of each parking position in the airport, enhance the comprehensiveness and timeliness of inspections, and thus enhance the overall safety and operating efficiency of the airport.

[0007] Optionally, the determining the inspection sequence of each parking position in the airport by combining the first position, the second position, the first aircraft position information, and the second aircraft position information includes: determining the initial inspection sequence of each parking position in the airport by combining the first aircraft position information and the second aircraft position information; adjusting the initial inspection sequence by combining the first position and the second position to determine the inspection sequence of each parking position in the airport.

[0008] By adopting the above technical solution, the method determines the initial inspection sequence according to the first aircraft position information and the second aircraft position information, which ensures that the inspection gives priority to parking positions with high time sensitivity. Subsequently, the method adjusts the initial sequence by combining the first position and the second position. This step takes into account the spatial distribution of the parking positions, helps to optimize the inspection path, and reduces the ineffective movement of the robotic dog between parking positions. This two-stage optimization strategy that combines time and space factors can not only ensure that important areas are inspected in a timely manner, but also minimize the energy consumption of the robotic dog and improve the overall inspection efficiency.

[0009] Optionally, combining the first aircraft position information and the second aircraft position information to determine the initial inspection sequence of each parking position in the airport includes: determining the first inspection priority of the first parking position according to the first aircraft position information, where the first inspection priority increases as the time difference between the departure time of the aircraft at the first parking position and the current time decreases; determining the second inspection priority of the second parking position according to the second aircraft position information, where the second inspection priority increases as the time difference between the occupied time of the second parking position and the current time decreases; and determining the initial inspection sequence of each parking position in the airport according to the first inspection priority and the second inspection priority.

[0010] By adopting the above technical solution, time-based inspection priorities are set for the first parking position and the second parking position respectively. The first inspection priority increases as the aircraft departure time approaches, and the second inspection priority increases as the time when the parking position is about to be occupied approaches. This time-sensitive priority setting ensures timely inspection of the parking positions about to change, effectively preventing potential safety hazards. By comprehensively considering these two priorities, the method can generate an initial inspection sequence that reflects the real-time operation requirements. This inspection strategy dynamically adjusted based on time not only improves the timeliness and pertinence of inspection, but also can optimize resource allocation and avoid unnecessary frequent inspections of parking positions that will not change in the short term.

[0011] Optionally, combining the first position and the second position to adjust the initial inspection sequence to determine the inspection sequence of each parking position in the airport includes: combining the first position and the second position to determine the distances between the parking positions in the airport; calculating the distances between adjacent parking positions in the initial inspection sequence according to the distances between the parking positions in the airport; when there are distances between adjacent parking positions in the initial inspection sequence greater than the preset distance, adjusting the order of the adjacent parking positions in the initial inspection sequence until the distances between adjacent parking positions in the initial inspection sequence are all not greater than the preset distance, to obtain the inspection sequence of each parking position in the airport.

[0012] By adopting the above technical solution, the distances between the parking positions are calculated using the first position and the second position information, and then the distances between adjacent parking positions in the initial inspection sequence are evaluated. When it is found that the distance between adjacent parking positions exceeds the preset threshold, the method dynamically adjusts the inspection sequence until the distances between all adjacent parking positions do not exceed the preset value. This distance-based optimization strategy can effectively reduce the ineffective movement of the robotic dog between the parking positions, thus significantly improving the inspection efficiency. By combining the time priority and the space optimization, this solution not only ensures the timeliness and importance of the inspection, but also maximizes the rationality of the inspection path. This dual optimization mechanism can balance the timeliness and path efficiency of the inspection, reduce the energy consumption, extend the working time of the robotic dog, and at the same time ensure the comprehensiveness of the inspection coverage.

[0013] Optionally, generating the inspection routes for the robotic dogs by combining the positions of the robotic dogs, the remaining power of the robotic dogs, and the inspection sequence of the parking positions in the airport includes: generating the initial inspection routes for the robotic dogs according to the positions of the robotic dogs and the inspection sequence of the parking positions in the airport; adjusting the initial inspection routes of the robotic dogs according to the remaining power of the robotic dogs to generate the inspection routes for the robotic dogs.

[0014] By adopting the above technical solution, the initial inspection routes are generated according to the current positions of the robotic dogs and the determined inspection sequence of the parking positions, which ensures that the basic allocation of the inspection tasks conforms to the principle of space efficiency. Subsequently, the method considers the remaining power of the robotic dogs and further adjusts the initial inspection routes. This step effectively solves the power management problem and avoids the interruption of the inspection caused by insufficient power. By combining the position information and the power status, this solution not only optimizes the inspection path, reduces the ineffective movement of the robotic dog between the parking positions, but also can reasonably allocate tasks according to the actual energy status of each robotic dog to ensure that each robotic dog can complete the specified inspection tasks within its power range. This method that comprehensively considers the space efficiency and the energy management significantly improves the reliability and sustainability of the entire inspection system, and at the same time maximizes the working efficiency of the robotic dog group.

[0015] Optionally, generating the initial inspection routes for the robotic dogs according to the positions of the robotic dogs and the inspection sequence of the parking positions in the airport includes: determining the distances between the robotic dogs and the parking positions in the airport; allocating the initial inspection parking positions for the robotic dogs according to the distances between the robotic dogs and the parking positions in the airport; determining the subsequent inspection parking positions of the initial inspection parking positions of the robotic dogs according to the inspection sequence of the parking positions in the airport; using the initial inspection parking positions and the subsequent inspection parking positions of the robotic dogs as the initial inspection routes for the robotic dogs.

[0016] By adopting the above technical solution, the method calculates the distances between each robotic dog and all parking positions, which provides an objective spatial information basis for task allocation. Then, based on these distance data, initial inspection parking positions are assigned to each robotic dog, ensuring the optimization of the starting points of the inspection tasks and reducing unnecessary long-distance movements. Next, according to the determined inspection sequence of the airport parking positions, the method determines the subsequent inspection parking positions for each robotic dog, which ensures the coherence and systematicness of the overall inspection sequence. Finally, the initial inspection parking positions and the subsequent inspection parking positions are combined to form the initial inspection routes of each robotic dog, forming a comprehensive and orderly inspection plan. This multi-step route generation method not only considers spatial efficiency but also maintains consistency with the overall inspection sequence, and can effectively balance the workload of a single robotic dog and the inspection requirements of the entire system.

[0017] Optionally, adjusting the initial inspection routes of each robotic dog according to the remaining power of each robotic dog to generate the inspection routes of each robotic dog includes: calculating the target power for each robotic dog to complete the initial inspection route; when the remaining power of a first robotic dog is less than the target power, calculating the power difference between the remaining power of a second robotic dog and the target power, where the second robotic dog is a robotic dog with remaining power greater than the target power; and according to the power difference, allocating some of the inspection routes in the initial inspection route of the first robotic dog to the second robotic dog to generate the inspection routes of each robotic dog.

[0018] By adopting the above technical solution, calculating the target power required for each robotic dog to complete the initial inspection route provides a quantitative basis for subsequent adjustment. When it is found that the remaining power of a certain robotic dog is insufficient to complete its initial inspection task, the method will identify the robotic dog with sufficient power and calculate the power difference available for additional tasks. Based on this difference, the system intelligently reallocates the part of the inspection tasks that the first robotic dog cannot complete to the second robotic dog. This task reallocation mechanism based on real-time power status not only avoids inspection interruptions or omissions caused by insufficient power of a single robotic dog but also makes full use of the remaining resources in the system, ensuring the continuity and integrity of the overall inspection task.

[0019] Second aspect, the present application provides a mechanical dog patrol inspection system, and the system includes: a first acquisition module, a second acquisition module, a first combination module, a third acquisition module, and a second combination module; wherein, the first acquisition module is used to acquire the first aircraft position information of the first parking position in the airport and the first position of the first parking position; wherein, the first parking position is a parking position where an aircraft exists, and the first aircraft position information is the departure time of the aircraft at the first parking position; the second acquisition module is used to acquire the second aircraft position information of the second parking position and the second position of the second parking position; wherein, the second parking position is a parking position where no aircraft exists, and the second aircraft position information is the occupied time of the second parking position; the first combination module is used to combine the first position, the second position, the first aircraft position information, and the second aircraft position information to determine the patrol inspection order of each parking position in the airport; the third acquisition module is used to acquire the positions of multiple mechanical dogs in the airport and the remaining power of each mechanical dog; the second combination module is used to combine the positions of each mechanical dog, the remaining power of each mechanical dog, and the patrol inspection order of each parking position in the airport to generate the patrol inspection routes of each mechanical dog.

[0020] Third aspect, the present application provides an electronic device, adopting the following technical solution: including a processor, a memory, a user interface, and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program of any one of the above mechanical dog patrol inspection methods.

[0021] Fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution: storing a computer program that can be loaded and executed by a processor for any one of the above mechanical dog patrol inspection methods.

[0022] In summary, the present application includes at least one of the following beneficial technical effects:

[0023] 1. Effectively improve the patrol inspection efficiency, avoid repeated patrol inspections or omission of important areas, and at the same time ensure the power management of mechanical dogs, reducing patrol inspection interruptions caused by insufficient power.

[0024] 2. Through this comprehensive and flexible patrol inspection strategy, the method can adapt to the complex and changeable operating environment of the airport, reasonably allocate patrol inspection resources, improve the patrol inspection efficiency of each parking position in the airport, improve the comprehensiveness and timeliness of patrol inspection, and thus enhance the overall safety and operating efficiency of the airport. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a schematic flowchart of a mechanical dog patrol inspection method provided by an embodiment of the present application;

[0026] Figure 2 It is a schematic structural diagram of a mechanical dog patrol inspection system provided by an embodiment of the present application;

[0027] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0028] Explanation of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. Specific embodiments

[0029] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "exemplary", "for example" or "for instance" are used to indicate as examples, illustrations or explanations. Any embodiment or design solution described as "exemplary", "for example" or "for instance" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of words such as "exemplary", "for example" or "for instance" is intended to present relevant concepts in a specific manner.

[0031] The mechanical dog patrol inspection method of the present invention is mainly applied to the daily operation and management of modern intelligent airports. In large international airports, especially those with numerous parking positions, the traditional manual patrol inspection method faces many challenges and limitations. Therefore, introducing mechanical dogs for automated patrol inspection has become an important measure to improve the safety, efficiency and economy of airports.

[0032] Mechanical dogs can work continuously for 24 hours, without being restricted by human working hours and physical strength, and can complete the parking position patrol inspection tasks more frequently and comprehensively.

[0033] At the same time, mechanical dogs are equipped with advanced sensors and camera devices, which can timely detect and report potential safety hazards, such as fuel leakage, abnormal objects, etc., greatly improving the overall safety level of the airport.

[0034] In addition, mechanical dogs can conduct patrol inspections according to precise routes and schedules, and will not miss important areas due to fatigue or distraction, ensuring that each parking position is inspected as it should be. And mechanical dogs have good mobility and can move flexibly in narrow spaces and complex terrains to reach areas that are difficult for humans to reach for inspection.

[0035] Finally, the robotic dog can collect and transmit inspection data in real time. Combined with artificial intelligence technology, it can quickly analyze the data and provide decision-making support, helping airport managers to detect and solve problems in a timely manner. Under extreme weather conditions, the robotic dog can continue to perform inspection tasks, reducing the risk of personnel working in harsh environments.

[0036] Introducing the robotic dog inspection system is an important part of the airport's intelligent and digital transformation, which helps to improve the overall operation efficiency and international competitiveness of the airport. By setting up the robotic dog and applying the inspection method of the present invention, the airport can achieve safer, more efficient, and more economical operation management, provide better services for passengers, and lay a foundation for the sustainable development of the airport.

[0037] Figure 1 It is a schematic flow chart of a robotic dog inspection method provided by an embodiment of the present application. As Figure 1 shown, the method includes S101 - S105:

[0038] S101, obtain the first aircraft position information of the first parking bay within the airport and the first position of the first parking bay; wherein, the first parking bay is a parking bay with an aircraft present, and the first aircraft position information is the departure time of the aircraft at the first parking bay.

[0039] Specifically, in airport operation, obtaining the aircraft position information of the parking bay and inspecting the parking bay are key links to ensure the safe and efficient operation of the airport.

[0040] The main reasons for inspecting the parking bay are as follows: Through inspection, potential safety hazards around the parking bay, such as ground damage, foreign objects, water accumulation, etc., can be detected in a timely manner, thus preventing these problems from causing potential harm to the parked aircraft. Regular inspection helps to detect damage or abnormalities of parking bay-related facilities (such as fixed power supplies, refueling equipment, etc.) in a timely manner, ensuring that these facilities can operate normally and providing necessary ground services for the aircraft. By ensuring that the parking bay is in the best condition through inspection, flight delays or cancellations caused by parking bay problems can be reduced, and the overall operation efficiency of the airport can be improved, etc.

[0041] In one example, the first parking bay refers to the parking bay with an aircraft present currently, and the first aircraft position information specifically refers to the estimated departure time of the aircraft at this parking bay. The implementation of this step is crucial for subsequent inspection planning because it provides key information on the usage status and time arrangement of the parking bay.

[0042] The system can obtain the required information by interacting with the airport management system in real time. For example, it can utilize the API interface of the airport's flight management system to query the information of all currently occupied parking positions. For each occupied parking position, the system will record its unique identifier (as the representation of the first position) and the scheduled departure time of the aircraft parked at this position (as the first aircraft position information). These data can be stored in a structured dataset, such as a data table containing parking position ID, geographical coordinates, and departure time.

[0043] The purpose of obtaining this information is to be able to accurately evaluate the urgency of inspection for each parking position. The parking positions where the aircraft is about to depart usually require priority inspection to ensure the condition of the parking position can be checked in time after the aircraft leaves. In addition, knowing the specific location of the parking position helps to plan the optimal inspection route subsequently and improve the inspection efficiency.

[0044] S102. Obtain the second aircraft position information of the second parking position and the second position of the second parking position; wherein, the second parking position is a parking position without an aircraft, and the second aircraft position information is the occupied time of the second parking position.

[0045] In one example, the system can obtain the required information by interacting with the airport's parking position management system. For example, it can query the airport's resource allocation system to obtain the information of all currently idle but already reserved parking positions. For each such parking position, the system will record its unique identifier or geographical coordinates (as the representation of the second position) and the estimated arrival time of the next scheduled aircraft to dock (as the second aircraft position information). These data can also be integrated into a structured dataset, together with the information of the first parking position, to form a complete map of the usage status of airport parking positions.

[0046] The importance of obtaining the second parking position information is that it enables the inspection system to arrange inspection tasks predictably. Although there is no aircraft at the idle parking position currently, it also needs to be inspected regularly to ensure its availability. Especially before the arrival of the next aircraft, timely inspection can guarantee the safety and availability of the parking position. By knowing the time when the second parking position will be occupied, the system can reasonably arrange the inspection time, neither affecting the use of the parking position by the upcoming aircraft nor ensuring the necessary inspections and possible maintenance work can be completed before the aircraft arrives.

[0047] S103. Combine the first position, the second position, the first aircraft position information, and the second aircraft position information to determine the inspection order of each parking position within the airport.

[0048] In one example, the system will first determine an initial inspection priority based on the first aircraft position information (i.e., the departure time of the aircraft on the occupied parking position) and the second aircraft position information (i.e., the occupied time of the idle parking position).

[0049] For the first parking position, the system calculates the difference between the aircraft departure time and the current time. The smaller the difference, the higher the priority. Similarly, for the second parking position, the system calculates the difference between the occupied time and the current time. The smaller the difference, the higher the priority as well. This method ensures that the parking positions about to undergo state changes can be inspected in a timely manner.

[0050] Then, the system combines the first position and the second position information to optimize and adjust the initially determined inspection sequence. The purpose of this step is to minimize the ineffective movement of the robotic dog between parking positions while ensuring the timeliness of inspections. The system may adopt some path optimization algorithms, such as the nearest neighbor algorithm or genetic algorithm, to calculate an inspection path with the shortest total distance while meeting the time requirements.

[0051] During the optimization process, the system also considers some practical limiting factors. For example, the distance between adjacent inspection points should not be too large to prevent the robotic dog from running between parking positions for a long time without being able to conduct effective inspections. If it is found that the distance between adjacent parking positions in the initial sequence is too large, the system will make local adjustments and may insert another parking position with a shorter distance to optimize the path.

[0052] Based on the above embodiments, as an alternative implementation, in S103, combining the first position, the second position, the first aircraft position information, and the second aircraft position information to determine the inspection sequence of each parking position in the airport specifically includes S31 - S32:

[0053] S31, combining the first aircraft position information and the second aircraft position information to determine the initial inspection sequence of each parking position in the airport.

[0054] Specifically, the system first processes the first aircraft position information, that is, the aircraft departure time on the parking position where there is an aircraft. The system calculates the difference between the estimated departure time of the aircraft at each parking position with an aircraft and the current time. The smaller this difference, the closer the aircraft is to leaving, and the higher the inspection priority of this parking position. At the same time, the system also processes the second aircraft position information, that is, the occupied time of the idle parking position. The system calculates the difference between the estimated occupied time of each idle parking position and the current time. The smaller this difference, the faster this parking position will be occupied by a new aircraft, so its inspection priority is also higher.

[0055] After obtaining these time differences, the system sorts all the parking positions in ascending order of the time differences to form an initial inspection sequence.

[0056] Based on the above embodiments, as an alternative implementation, in S31, determining the initial inspection order of each parking bay in the airport by combining the first bay information and the second bay information specifically includes S311 - S313:

[0057] S311, determine the first inspection priority of the first parking bay according to the first bay information, where the first inspection priority increases as the time difference between the departure time of the aircraft at the first parking bay and the current time decreases.

[0058] S312, determine the second inspection priority of the second parking bay according to the second bay information, where the second inspection priority increases as the time difference between the occupied time of the second parking bay and the current time decreases.

[0059] S313, determine the initial inspection order of each parking bay in the airport according to the first inspection priority and the second inspection priority.

[0060] In one example, the system first processes the first bay information, that is, the parking bays with aircraft. For each first parking bay, the system calculates the time difference between the expected departure time of the aircraft on it and the current time. Based on this time difference, the system assigns a first inspection priority to the first parking bay. The smaller the time difference, the closer the aircraft is to departure, so the assigned first inspection priority is higher. This design ensures that the parking bays where the aircraft are about to take off can be inspected in a timely manner, which helps to ensure flight safety and on-time departure.

[0061] Next, the system processes the second bay information, that is, the currently idle but soon-to-be-occupied parking bays. For each second parking bay, the system calculates the time difference between its expected occupancy time and the current time. Based on this time difference, the system assigns a second inspection priority to the second parking bay. The smaller the time difference, the sooner the parking bay will be occupied by a new aircraft, so the assigned second inspection priority is higher. This design ensures that the parking bays about to receive new aircraft can be fully inspected before the aircraft arrives, and prepares for safe berthing.

[0062] After determining the inspection priorities of all parking bays, the system determines the initial inspection order of each parking bay in the airport according to these priorities. This process may involve trade-offs of various factors. First, the system will make a unified quantitative comparison of the first inspection priority and the second inspection priority. For example, a time threshold can be set. When the time difference is less than this threshold, both the first parking bay and the second parking bay will be given the highest inspection priority.

[0063] Then, the system will sort all the parking positions according to the quantified priorities to form a preliminary inspection order. This order may be further adjusted according to some additional rules. For example, considering the balance of inspections, the system may appropriately increase the priorities of those parking positions that have not been inspected for a long time. In addition, parking positions for certain special purposes or important locations may be given additional weights to ensure that they can be inspected more frequently.

[0064] S32. Combine the first position and the second position to adjust the initial inspection order and determine the inspection order of each parking position within the airport.

[0065] Specifically, the system will first obtain the first position information, that is, the current positions of each robotic dog, and the second position information, that is, the positions of each parking position. Then, based on these position information, the system will calculate the distance from each robotic dog to each parking position. This distance can be a straight-line distance or a path distance considering the actual terrain and obstacles of the airport.

[0066] Next, the system will combine the previously determined initial inspection order and the calculated distance information to optimize and adjust the inspection order. This process involves the trade-off and optimization of multiple factors. First, the system will try to maintain the inspection time sequence of high-priority parking positions in the initial inspection order to ensure that inspection tasks with tight time constraints can be completed in a timely manner. At the same time, the system will consider the positions of the robotic dogs and try to assign parking positions with relatively short distances to the same robotic dog to reduce the movement time of the robotic dogs between parking positions.

[0067] Based on the above embodiments, as an alternative embodiment, in S32, combining the first position and the second position to adjust the initial inspection order and determine the inspection order of each parking position within the airport specifically includes S321 - S323:

[0068] S321. Combine the first position and the second position to determine the distances between each parking position within the airport.

[0069] S322. Calculate the distances between adjacent parking positions in the initial inspection order according to the distances between each parking position within the airport.

[0070] S323. When there is a distance between adjacent parking positions in the initial inspection order that is greater than the preset distance, adjust the order of the adjacent parking positions in the initial inspection order until the distances between adjacent parking positions in the initial inspection order are all not greater than the preset distance, and obtain the inspection order of each parking position within the airport.

[0071] In one example, the system first combines the information of the first position (the current position of the robotic dog) and the second position (the positions of each parking bay) to calculate the distances between each parking bay within the airport. This distance can be the straight-line distance or the path distance considering the actual terrain and obstacles of the airport. Through this step, the system establishes a complete parking bay distance matrix, providing the basic data for subsequent path optimization.

[0072] Next, based on the calculated parking bay distance information, the system analyzes the distances between adjacent parking bays in the initial inspection sequence. The purpose of this step is to identify possible inefficient inspection paths. The initial inspection sequence is mainly determined based on time urgency, which may result in relatively long distances between adjacent inspection points, thus increasing the unnecessary movement of the robotic dog.

[0073] The system sets a preset distance threshold. When it is found that the distance between adjacent parking bays in the initial inspection sequence is greater than this preset distance, the adjustment mechanism is triggered. The adjustment process attempts to swap or insert other parking bays to shorten the distances between adjacent parking bays. This process is repeated until the distances between all adjacent parking bays in the initial inspection sequence are not greater than the preset distance, thereby obtaining the optimized inspection sequence of each parking bay within the airport.

[0074] During the adjustment process, the system uses intelligent algorithms to balance multiple factors. First, the system tries to maintain the inspection time sequence of high-priority parking bays to ensure that inspection tasks with tight time constraints can be completed in a timely manner. Second, the system considers the overall path optimization, attempting to find an optimal solution that can meet both the distance requirements and ensure inspection efficiency. In addition, the system may also consider the terrain features of the airport to avoid the robotic dog frequently crossing difficult terrains or obstacles.

[0075] Suppose there is a medium-sized airport with 10 parking bays to be inspected, numbered from A1 to A10. There are two robotic dogs (Dog1 and Dog2) in the airport for inspection tasks.

[0076] First, the initial inspection sequence: A3 > A7 > A1 > A9 > A4 > A2 > A6 > A10 > A5 > A8, where A3 is the most urgent parking bay to be inspected, and A8 is the least urgent one.

[0077] Calculate the distances between the parking bays (unit: meters). Some of the distance data are as follows: from A3 to A7: 500 meters, from A7 to A1: 800 meters, from A1 to A9: 300 meters, from A9 to A4: 700 meters...

[0078] Calculate the distances between adjacent parking bays: from A3 to A7: 500 meters, from A7 to A1: 800 meters, from A1 to A9: 300 meters, from A9 to A4: 700 meters...

[0079] The set preset distance is 600 meters. The distance from A7 to A1 (800 meters) and the distance from A9 to A4 (700 meters) exceed the preset distance. The system will attempt to adjust the order. For example, it may attempt to insert A1 between A3 and A7 because the distance from A3 to A1 may be less than 600 meters. At the same time, it may attempt to move A4 before A9.

[0080] After multiple iterations and adjustments, a new inspection order is obtained: A3 > A1 > A7 > A4 > A9 > A2 > A6 > A10 > A5 > A8. In this new order, the distance between all adjacent parking positions does not exceed 600 meters, and at the same time, the original priority order is maintained as much as possible.

[0081] Finally, the system will consider the positions of the two robotic dogs and may allocate tasks as follows: Dog1: A3 > A1 > A7 > A4 > A9, Dog2: A2 > A6 > A10 > A5 > A8.

[0082] Such an allocation ensures that high-priority parking positions (such as A3, A1, A7) can be inspected in a timely manner, optimizes the movement paths of each robotic dog, and reduces unnecessary long-distance movements.

[0083] S104, Obtain the positions of multiple robotic dogs within the airport and the remaining battery power of each robotic dog.

[0084] In one example, the system can obtain the position and power information of the robotic dogs through various technical means. For the position information, the GPS positioning system or indoor positioning technologies (such as UWB, RFID, etc.) can be used to track the specific positions of each robotic dog in real time. These position data usually include latitude and longitude coordinates or coordinates relative to specific reference points in the airport. For the power information, each robotic dog is equipped with a battery management system that can monitor the remaining capacity of the battery in real time and transmit this data to the central control system through a wireless communication network (such as Wi-Fi or 5G network).

[0085] The system will actively obtain this information regularly (for example, every few minutes) or when new tasks need to be allocated. The obtained data will be integrated into a real-time updated database, which contains information such as the unique identifier of each robotic dog, the current position coordinates, and the remaining battery percentage.

[0086] S105, Combine the positions of each robotic dog, the remaining battery power of each robotic dog, and the inspection order of each parking position within the airport to generate the inspection routes of each robotic dog.

[0087] In one example, a preliminary task list is established based on the previously determined inspection sequence of each parking position within the airport. Then, the system takes into account the current position and remaining battery power of each robotic dog, and allocates tasks and plans routes through a series of optimization steps.

[0088] During the optimization process, the system considers the following key factors:

[0089] Distance efficiency: The system tries to allocate parking positions that are relatively close to the same robotic dog to reduce the movement time of the robotic dog between parking positions.

[0090] Battery management: The system reasonably allocates the task volume according to the remaining battery power of each robotic dog. For robotic dogs with low battery power, fewer or closer tasks may be allocated, and charging is arranged at an appropriate time.

[0091] Time urgency: For parking positions with higher priorities in the inspection sequence, the system preferentially allocates them to robotic dogs that are closer in position or have sufficient battery power.

[0092] Load balancing: The system tries to balance the workload of each robotic dog to avoid overuse of some robotic dogs while others are idle.

[0093] Charging planning: When generating the inspection route, the system also considers the location of the charging station and arranges for the robotic dog to charge at the right time to ensure continuous operation.

[0094] Based on the above embodiments, as an alternative implementation, in S105, generating the inspection routes of each robotic dog by combining the positions of each robotic dog, the remaining battery power of each robotic dog, and the inspection sequence of each parking position within the airport specifically includes S51 - S52:

[0095] S51, generate the initial inspection routes of each robotic dog according to the positions of each robotic dog and the inspection sequence of each parking position within the airport.

[0096] In S51, generating the initial inspection routes of each robotic dog according to the positions of each robotic dog and the inspection sequence of each parking position within the airport specifically includes S511 - S514:

[0097] S511, determine the distances between each robotic dog and each parking position within the airport.

[0098] S512, allocate the initial inspection parking positions for each robotic dog according to the distances between each robotic dog and each parking position within the airport.

[0099] In one example, the system first obtains the current location information of each robotic dog and the location data of all the parking positions that need to be inspected. This data may come from the airport's real-time positioning system, such as GPS or specialized indoor positioning technologies. The system uses this location data to calculate the distance matrix from each robotic dog to each parking position. This distance can be a straight-line distance or a path distance considering the actual terrain and possible obstacles of the airport, depending on the system design and the actual situation of the airport.

[0100] Next, the system uses an intelligent allocation algorithm to assign initial inspection parking positions to each robotic dog. The core of this algorithm is to minimize the overall moving distance while considering the priority of the parking positions and the balance of tasks. The algorithm first tries to assign the nearest parking position to the corresponding robotic dog, but this is not the only consideration. If a parking position that is farther away but has a high priority needs to be inspected urgently, the system may choose to assign it to a certain robotic dog even if there are closer parking positions. This trade-off ensures that important inspection tasks are not delayed due to distance factors.

[0101] To achieve this goal, the system may find a globally optimal or near-optimal allocation scheme considering multiple constraints. In actual operation, the system may assign a comprehensive score to each parking position, which takes into account not only the distance factor but also multiple dimensions such as priority and urgency. The algorithm will perform the allocation based on this comprehensive score.

[0102] In addition, the algorithm also considers the balance of tasks. It tries to avoid assigning all the close or high-priority parking positions to the same robotic dog, but instead attempts to achieve a relatively balanced allocation of tasks while ensuring efficiency. The purpose of doing this is to avoid overusing some robotic dogs while others are in a relatively idle state, thereby improving the efficiency and reliability of the entire system.

[0103] During the allocation process, the algorithm also considers the terrain features and possible obstacles of the airport. For example, if there are difficult-to-cross obstacles between two parking positions, even if their straight-line distance is very close, the system may assign them to different robotic dogs. This consideration ensures that the generated initial inspection route is practical and avoids potential problems during actual execution.

[0104] Finally, the system assigns an initial inspection parking position to each robotic dog and reserves room for subsequent dynamic adjustment. This approach enables the system to better handle real-time changes, such as sudden high-priority inspection requirements or temporary failures of robotic dogs. The system may periodically or based on specific trigger conditions re-evaluate and adjust the allocation scheme to ensure the continuous optimization of the inspection work.

[0105] S513. Determine the subsequent inspection parking positions of each robotic dog based on the inspection sequence of each parking position within the airport.

[0106] In one example, the system first reads the inspection sequence of each parking position within the airport that has been optimized in the previous step. This inspection sequence is obtained through comprehensive consideration of various factors, which may include the importance, urgency, geographical location, etc. of the parking positions. At the same time, the system also acquires the information of the initial inspection parking positions assigned to each robotic dog in step S512.

[0107] Next, the system uses an intelligent algorithm to determine the sequence of subsequent inspection parking positions for each robotic dog after its initial inspection parking position. The core of this algorithm is to assign the most suitable subsequent inspection tasks to each robotic dog while ensuring the overall inspection sequence. The algorithm takes into account the following key factors:

[0108] First of all, the algorithm follows the previously determined overall inspection sequence. This ensures that parking positions with high priority or urgent inspection needs can be processed in a timely manner. However, the algorithm does not simply assign tasks in a fixed order but makes optimization adjustments according to the actual situation.

[0109] Secondly, the algorithm considers the task balance among the robotic dogs. It tries to avoid the situation where some robotic dogs are overburdened while others are relatively idle. This may mean making fine-tuning to the inspection sequence of individual parking positions on the premise of ensuring the overall inspection sequence to achieve better task allocation.

[0110] Furthermore, the algorithm also considers geographical location and movement efficiency. When determining the subsequent inspection parking positions, it tries to select parking positions that are relatively close to the current location or on the movement path to reduce unnecessary long-distance movements and improve the overall inspection efficiency.

[0111] In addition, the algorithm considers the performance parameters of the robotic dogs, such as battery life, movement speed, etc. It adjusts the assigned task volume and inspection route according to these parameters to ensure that each robotic dog can efficiently complete tasks within its capabilities.

[0112] In actual operation, the system may use heuristic algorithms or dynamic programming algorithms to implement this complex task allocation process. The algorithm may first generate an initial sequence of subsequent inspection parking positions and then continuously improve this sequence through multiple iterations of optimization until a balance point is reached, that is, while ensuring the overall inspection sequence, the task balance and movement efficiency are optimized.

[0113] It should be noted that the determination of the subsequent inspection parking positions is not a static process completed at one time. The system retains a certain degree of flexibility, allowing for dynamic adjustment according to on-site conditions during the actual inspection process. For example, if a certain robotic dog discovers a problem that requires urgent handling during the inspection, the system may adjust the subsequent inspection sequence in real time to prioritize this emergency situation.

[0114] S514. Use the initial inspection parking positions and subsequent inspection parking positions of each robotic dog as the initial inspection routes of each robotic dog.

[0115] Suppose we have a medium-sized airport with a total of 20 parking positions to be inspected, numbered from A1 to A20. The airport is equipped with 3 robotic dogs, numbered Dog1, Dog2, and Dog3. In step S512, the system has already assigned the initial inspection parking positions for these robotic dogs: Dog1 is assigned to A3, Dog2 is assigned to A12, and Dog3 is assigned to A18.

[0116] In step S513, the system determines the subsequent inspection parking positions for each robotic dog. Suppose that after previous optimization, the system has determined an overall inspection sequence: A3 > A4 > A12 > A13 > A5 > A18 > A19 > A6 > A1 > A2 > A14 > A15 > A7 > A8 > A9 > A16 > A17 > A10 > A11 > A20.

[0117] The intelligent algorithm of the system will consider this overall sequence and also take into account factors such as task balance, geographical location, and movement efficiency. After calculation, the system may obtain the following subsequent inspection parking position assignments:

[0118] Dog1 (initial position A3): A4 > A5 > A6 > A1 > A2 > A7 > A8 > A9 > A10;

[0119] Dog2 (initial position A12): A13 > A14 > A15 > A16 > A17 > A11;

[0120] Dog3 (initial position A18): A19 > A20;

[0121] This assignment scheme reflects several key considerations:

[0122] Follow the overall sequence: For example, A4 is assigned to Dog1 immediately after A3, and A13 is assigned to Dog2 immediately after A12.

[0123] Task balance: Although the initial position of Dog3 is relatively backward, the system does not assign all the remaining tasks to it, but tries to balance the workload of the three robotic dogs as much as possible.

[0124] Geographical location and movement efficiency: The system tries to make each robotic dog move between adjacent or nearby parking positions. For example, the parking positions that Dog1 is responsible for are mostly concentrated in the range from A1 to A10.

[0125] Flexibility: The system does not allocate all parking positions at once, but assigns a certain number of subsequent tasks to each robotic dog. This allows for adjustment according to the situation during actual execution.

[0126] S52. Adjust the initial inspection route of each robotic dog according to the remaining power of each robotic dog, and generate the inspection route of each robotic dog.

[0127] In S52, adjusting the initial inspection route of each robotic dog according to the remaining power of each robotic dog and generating the inspection route of each robotic dog specifically includes S521 - S523:

[0128] S521. Calculate the target power of each robotic dog to complete the initial inspection route.

[0129] S522. When the remaining power of the first robotic dog is less than the target power, calculate the power difference between the remaining power of the second robotic dog and the target power, where the second robotic dog is a robotic dog with remaining power greater than the target power.

[0130] In an example, the system first continuously monitors the remaining power of all robotic dogs. When the system detects that there is one or more robotic dogs (referred to as the first robotic dog) with remaining power lower than the preset target power, this step will be triggered. The target power is a threshold preset by the system, which represents the minimum power required for the robotic dog to safely complete the current task and return to the charging station. The setting of this target power needs to consider multiple factors, such as the energy consumption rate of the robotic dog, the distance from the current position to the nearest charging station, the reserved safety margin, etc.

[0131] Once the system detects that the remaining power of the first robotic dog is lower than the target power, it will immediately start looking for a robotic dog with remaining power higher than the target power, which is the second robotic dog. The system will calculate the difference between the remaining power of each second robotic dog and the target power, that is, the power difference. This power difference represents the power that the second robotic dog can safely transfer to other robotic dogs without affecting its normal operation.

[0132] The process of calculating the power difference may involve the following steps:

[0133] The system first determines all robotic dogs with remaining power higher than the target power and marks them as potential second robotic dogs.

[0134] For each potential second robotic dog, the system calculates the difference between its remaining power and the target power.

[0135] The system may consider the current task status and location of each second robotic dog. For example, if a second robotic dog is performing an important task or is far from the charging station, the system may appropriately reduce the transferable power to ensure its safety.

[0136] The system may also consider the distance between the robotic dogs. If two robotic dogs are far apart, transferring power may consume too much energy, so the system may adjust the calculated power difference accordingly.

[0137] Finally, the system generates a final power difference for each second robotic dog, which represents the maximum amount of power that the robotic dog can safely transfer.

[0138] S523. According to the power difference, allocate part of the initial inspection route of the first robotic dog to the second robotic dog to generate the inspection routes of each robotic dog.

[0139] In one example, the system first uses the power difference calculated in step S522 as the basis for reallocating the inspection route. This power difference represents the additional workload that the second robotic dog (i.e., the robotic dog with remaining power higher than the target power) can undertake. The system selects an appropriate part from the initial inspection route of the first robotic dog (i.e., the robotic dog with remaining power lower than the target power) and allocates it to the second robotic dog according to this difference.

[0140] When reallocating the route, the system considers multiple factors to ensure that the new allocation plan can not only solve the problem of insufficient power but also ensure the overall inspection efficiency. These factors include but are not limited to:

[0141] Power consumption estimation: The system estimates the power consumption required for each section of the inspection route. This estimation is based on multiple parameters such as route length, terrain complexity, and estimated inspection time. The system preferentially selects route segments whose power consumption matches the power difference of the second robotic dog for transfer.

[0142] Geographical location: The system considers the current positions of the first and second robotic dogs and the position of the route segment to be transferred. It tries to select a plan that minimizes the moving distance of the two robotic dogs to reduce unnecessary energy consumption.

[0143] Task urgency: If there are some high-priority or urgent inspection points in the initial inspection route, the system will give priority to allocating these points to the second robotic dog with sufficient power to ensure that these important tasks can be completed in a timely manner.

[0144] Robotic dog performance parameters: The system considers the performance characteristics of different robotic dogs, such as moving speed, climbing ability, etc., to ensure that the allocated tasks match the capabilities of the robotic dogs.

[0145] Charging station location: When reallocating routes, the system takes into account the location of charging stations to ensure that each robotic dog can reach the nearest charging station before its battery runs out.

[0146] Based on these considerations, the system uses intelligent algorithms to calculate the optimal route allocation plan. This process may involve the following steps:

[0147] First, the system decomposes the initial inspection route of the first robotic dog into several small segments. Then, it evaluates the characteristics of each segment, including the estimated power consumption, importance, location, etc. Next, based on the power difference of the second robotic dog, the system selects the most suitable route segment for transfer. In this process, the system may use dynamic programming or greedy algorithms to find the optimal solution.

[0148] Once the route segment to be transferred is determined, the system regenerates the inspection routes of each robotic dog. For the first robotic dog, the new inspection route will exclude the transferred part and may also add a path to the nearest charging station. For the second robotic dog, the new inspection route will include its original route plus the new tasks received from the first robotic dog.

[0149] Based on the above method, this application also discloses a robotic dog inspection system, as Figure 2 shown Figure 2 is a schematic structural diagram of a robotic dog inspection system provided by an embodiment of this application. The system includes: a first acquisition module, a second acquisition module, a first combination module, a third acquisition module, and a second combination module; wherein,

[0150] The first acquisition module is used to acquire the first aircraft position information of the first parking bay in the airport and the first position of the first parking bay; wherein, the first parking bay is a parking bay where an aircraft exists, and the first aircraft position information is the departure time of the aircraft in the first parking bay; the second acquisition module is used to acquire the second aircraft position information of the second parking bay and the second position of the second parking bay; wherein, the second parking bay is a parking bay where no aircraft exists, and the second aircraft position information is the occupied time of the second parking bay; the first combination module is used to combine the first position, the second position, the first aircraft position information, and the second aircraft position information to determine the inspection order of each parking bay in the airport; the third acquisition module is used to acquire the positions of multiple robotic dogs in the airport and the remaining power of each robotic dog; the second combination module is used to combine the positions of each robotic dog, the remaining power of each robotic dog, and the inspection order of each parking bay in the airport to generate the inspection routes of each robotic dog.

[0151] It should be noted that when the device provided in the above embodiments realizes its functions, only the division of the above function modules is used for illustration. In actual applications, the above functions can be allocated to different function modules according to needs, that is, the internal structure of the device is divided into different function modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments belong to the same concept. For the specific implementation process, please refer to the method embodiments and will not be elaborated here.

[0152] Please refer to Figure 3 , which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 3 shown, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, and at least one communication bus 1002.

[0153] Among them, the communication bus 1002 is used to realize the connection and communication between these components.

[0154] Among them, the user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface.

[0155] Among them, the network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0156] Among them, the processor 1001 may include one or more processing cores. The processor 1001 connects various parts within the entire server through various interfaces and lines, and executes various functions of the server and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and by calling the data stored in the memory 1005. Optionally, the processor 1001 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 1001 may integrate one or a combination of several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 1001 and may be implemented separately by a single chip.

[0157] Among them, the memory 1005 may include random access memory (RAM), and may also include read-only memory. Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1005 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store the data involved in the above-mentioned various method embodiments. Optionally, the memory 1005 may further be at least one storage device located far from the aforementioned processor 1001. As Figure 3 shown, the memory 1005, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a mechanical dog patrol method.

[0158] In Figure 3In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an interface for the user to input and obtain the data input by the user; and the processor 1001 can be used to call the application program storing a mechanical dog patrol method in the memory 1005. When executed by one or more processors, the electronic device executes one or more of the methods as described in the above embodiments.

[0159] An electronic device-readable storage medium stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods as described in the above embodiments.

[0160] It should be noted that, for the foregoing method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be in other sequences or performed simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0161] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0162] In several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0163] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In addition, in each embodiment of this application, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0165] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned memory includes: various media such as USB flash drives, external hard drives, magnetic disks, or optical discs that can store program codes.

[0166] The foregoing are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will readily think of other embodiments of the present disclosure after considering the specification and practicing the present disclosure herein. The present application aims to cover any variations, uses, or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include the common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A mechanical dog patrol inspection method, characterized in that, The method includes: Obtaining the first aircraft position information of the first parking bay in the airport and the first position of the first parking bay; wherein, the first parking bay is the parking bay with an aircraft, and the first aircraft position information is the departure time of the aircraft at the first parking bay; Obtaining the second aircraft position information of the second parking bay and the second position of the second parking bay; wherein, the second parking bay is the parking bay without an aircraft, and the second aircraft position information is the occupied time of the second parking bay; Combining the first position, the second position, the first aircraft position information and the second aircraft position information to determine the inspection sequence of each parking bay in the airport, including: combining the first aircraft position information and the second aircraft position information to determine the initial inspection sequence of each parking bay in the airport; combining the first position and the second position to adjust the initial inspection sequence to determine the inspection sequence of each parking bay in the airport; The combining the first aircraft position information and the second aircraft position information to determine the initial inspection sequence of each parking bay in the airport includes: determining the first inspection priority of the first parking bay according to the first aircraft position information, wherein the first inspection priority increases as the time difference between the departure time of the aircraft at the first parking bay and the current time decreases; Determining the second inspection priority of the second parking bay according to the second aircraft position information, wherein the second inspection priority increases as the time difference between the occupied time of the second parking bay and the current time decreases; determining the initial inspection sequence of each parking bay in the airport according to the first inspection priority and the second inspection priority; The combining the first position and the second position to adjust the initial inspection sequence to determine the inspection sequence of each parking bay in the airport includes: combining the first position and the second position to determine the distances between the parking bays in the airport; calculating the distances between adjacent parking bays in the initial inspection sequence according to the distances between the parking bays in the airport; when there are distances between adjacent parking bays in the initial inspection sequence that are greater than the preset distance, adjusting the order of the adjacent parking bays in the initial inspection sequence until the distances between adjacent parking bays in the initial inspection sequence are all not greater than the preset distance to obtain the inspection sequence of each parking bay in the airport; Obtaining the positions of multiple robotic dogs in the airport and the remaining power of each robotic dog; Generating the inspection routes of each robotic dog by combining the positions of each robotic dog, the remaining power of each robotic dog and the inspection sequence of each parking bay in the airport.

2. The mechanical dog patrol inspection method according to claim 1, wherein The generating the inspection routes of each robotic dog by combining the positions of each robotic dog, the remaining power of each robotic dog and the inspection sequence of each parking bay in the airport includes: Generating the initial inspection routes of each robotic dog according to the positions of each robotic dog and the inspection sequence of each parking bay in the airport; Adjusting the initial inspection routes of each robotic dog according to the remaining power of each robotic dog to generate the inspection routes of each robotic dog.

3. The mechanical dog patrol inspection method according to claim 2, wherein, Generating an initial inspection route for each of the mechanical dogs according to the positions of the mechanical dogs and the inspection sequence of each parking bay in the airport, includes: Determining the distances between each of the mechanical dogs and each parking bay in the airport; Allocating initial inspection parking bays for each of the mechanical dogs according to the distances between each of the mechanical dogs and each parking bay in the airport; Determining subsequent inspection parking bays of the initial inspection parking bays of each of the mechanical dogs according to the inspection sequence of each parking bay in the airport; Taking the initial inspection parking bays and the subsequent inspection parking bays of each of the mechanical dogs as the initial inspection route of each of the mechanical dogs.

4. The mechanical dog patrol inspection method according to claim 2, characterized in that, Adjusting the initial inspection route of each of the mechanical dogs according to the remaining power of each of the mechanical dogs to generate an inspection route for each of the mechanical dogs, includes: Calculating the target power of each of the mechanical dogs to complete the initial inspection route; When the remaining power of a first mechanical dog is less than the target power, calculating the power difference between the remaining power of a second mechanical dog and the target power, where the second mechanical dog is a mechanical dog with a remaining power greater than the target power; Allocating a part of the inspection route in the initial inspection route of the first mechanical dog to the second mechanical dog according to the power difference to generate an inspection route for each of the mechanical dogs.

5. A mechanical dog patrol inspection system, characterized in that, The system includes: a first acquisition module, a second acquisition module, a first combination module, a third acquisition module and a second combination module; where The first acquisition module is used to acquire first aircraft position information of a first parking bay in the airport and a first position of the first parking bay; where the first parking bay is a parking bay with an aircraft, and the first aircraft position information is the departure time of the aircraft in the first parking bay; The second acquisition module is used to acquire second aircraft position information of a second parking bay and a second position of the second parking bay; where the second parking bay is a parking bay without an aircraft, and the second aircraft position information is the occupied time of the second parking bay; The first combination module is used to combine the first position, the second position, the first aircraft position information and the second aircraft position information to determine the inspection sequence of each parking bay in the airport, includes: combining the first aircraft position information and the second aircraft position information to determine the initial inspection sequence of each parking bay in the airport; combining the first position and the second position to adjust the initial inspection sequence to determine the inspection sequence of each parking bay in the airport; Combining the first aircraft position information and the second aircraft position information to determine the initial inspection sequence of each parking bay in the airport, includes: determining a first inspection priority of the first parking bay according to the first aircraft position information, where the first inspection priority increases as the time difference between the departure time of the aircraft in the first parking bay and the current time decreases; Determine the second patrol priority of the second parking bay according to the second bay information, wherein the second patrol priority increases as the time difference between the occupied time of the second parking bay and the current time decreases; determine the initial patrol sequence of each parking bay in the airport according to the first patrol priority and the second patrol priority; The adjusting the initial patrol sequence in combination with the first position and the second position to determine the patrol sequence of each parking bay in the airport includes: determining the distances between the parking bays in the airport in combination with the first position and the second position; calculating the distances between adjacent parking bays in the initial patrol sequence according to the distances between the parking bays in the airport; when there is a distance between adjacent parking bays in the initial patrol sequence that is greater than a preset distance, adjusting the order of the adjacent parking bays in the initial patrol sequence until the distances between adjacent parking bays in the initial patrol sequence are not greater than the preset distance, to obtain the patrol sequence of each parking bay in the airport; The third obtaining module is configured to obtain the positions of a plurality of robotic dogs in the airport and the remaining power of each robotic dog; The second combining module is configured to generate a patrol route for each robotic dog by combining the positions of the robotic dogs, the remaining power of each robotic dog, and the patrol sequence of each parking bay in the airport.

6. An electronic device, characterized in that, It includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions. The user interface and the network interface are used to communicate with other devices. The processor is configured to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, A computer program is stored that can be loaded and executed by a processor to execute the method according to any one of claims 1-4.

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