Mechanical dog inspection method, system and equipment and storage medium

Abstract

The invention provides a mechanical dog inspection method, system and device and a storage medium, and relates to the technical field of inspection, and the method comprises the steps: obtaining the first parking space information of a first parking space in an aircraft field, and the first position of the first parking space; acquiring second parking space information of a second parking space and a second position of the second parking space; in combination with the first position, the second position, the first aircraft position information and the second aircraft position information, determining an inspection sequence of each aircraft position in the aircraft field; acquiring the positions of a plurality of mechanical dogs in the airfield and the residual electric quantity of each mechanical dog; and in combination with the position of each mechanical dog, the residual electric quantity of each mechanical dog and the inspection sequence of each parking space in the aircraft field, generating an inspection route of each mechanical dog. The technical effects of the invention are that the routing inspection resources are reasonably distributed, and the routing inspection efficiency of each parking space in the airport is improved.

Description

Technical Field

[0001] The present application relates to the field of patrol inspection technology, and in particular to a mechanical dog patrol inspection method, system, equipment and storage medium. Background Art

[0002] With the rapid development of the civil aviation industry, the complexity of airport operation and management has continued to increase. Among them, how to efficiently inspect and manage parking spaces is a technical problem that needs to be solved urgently. The traditional manual inspection method is not only time-consuming and labor-intensive, but also easily affected by human factors, and it is difficult to ensure the comprehensiveness and timeliness of the inspection. This method is difficult to adapt to the fast-paced and high-density operation needs of modern airports, and it is impossible to detect and deal with potential safety hazards in a timely manner, thus affecting the operational efficiency and safety of the airport.

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

[0004] The present application provides a mechanical dog inspection method for rationally allocating inspection resources and improving the inspection efficiency of each parking space in an airport.

[0005] In a first aspect, the present application provides a robot dog inspection method, the method comprising: obtaining first parking stand information of a first parking stand in an airport, and a first position of the first parking stand; wherein the first parking stand is a parking stand where an aircraft is present, and the first parking stand information is the departure time of the aircraft at the first parking stand; obtaining second parking stand information of a second parking stand, and a second position of the second parking stand; wherein the second parking stand is a parking stand where no aircraft is present, and the second parking stand information is the occupied time of the second parking stand; determining the inspection order of each parking stand in the airport in combination with the first position, the second position, the first parking stand information and the second parking stand information; obtaining the positions of multiple robot dogs in the airport and the remaining power of each robot dog; generating the inspection route of each robot dog in combination with the position of each robot dog, the remaining power of each robot dog and the inspection order of each parking stand in the airport.

[0006] By adopting the above technical scheme, the intelligent allocation and optimization of inspection resources are realized by comprehensively considering the real-time status of the parking positions in the airport, the departure time of the aircraft, the occupancy of the parking positions, and the position and power of the robot dog. The method first obtains the relevant information of the first parking position where the aircraft exists and the second parking position where the aircraft does not exist, including the position and time data, and then determines the inspection order of the entire airport based on this information. Subsequently, the method further considers the real-time position and remaining power of multiple robot dogs, and generates the most optimized inspection route for each robot dog in combination with the determined inspection order. This dynamic adjustment method can effectively improve the inspection efficiency, avoid repeated inspections or omissions of important areas, and at the same time ensure the power management of the robot dog, reducing the inspection interruption 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, and improve the comprehensiveness and timeliness of the inspection, thereby enhancing the overall safety and operational efficiency of the airport.

[0007] Optionally, the combining of the first position, the second position, the first aircraft stand information and the second aircraft stand information to determine the inspection order of each parking stand in the airport includes: combining the first aircraft stand information and the second aircraft stand information to determine the initial inspection order of each parking stand in the airport; combining the first position and the second position to adjust the initial inspection order to determine the inspection order of each parking stand in the airport.

[0008] By adopting the above technical solution, the method determines the initial inspection order based on the first camera position information and the second camera position information, which ensures that the inspection gives priority to the parking positions with high time sensitivity. Subsequently, the method adjusts the initial order based on 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 robot dog between the 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 robot dog and improve the overall inspection efficiency.

[0009] Optionally, the combining of the first aircraft stand information and the second aircraft stand information to determine the initial inspection order of each parking stand in the airport includes: determining a first inspection priority of the first parking stand based on the first aircraft stand information, wherein the first inspection priority increases as the time difference between the departure time of the aircraft at the first parking stand and the current time decreases; determining a second inspection priority of the second parking stand based on the second aircraft stand information, wherein the second inspection priority increases as the time difference between the occupation time of the second parking stand and the current time decreases; determining the initial inspection order of each parking stand in the airport based on 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, where the first inspection priority increases as the aircraft departure time approaches, and the second inspection priority increases as the parking position is about to be occupied. This time-sensitive priority setting ensures timely inspections of parking positions that are about to change, effectively preventing potential safety hazards. By comprehensively considering these two priorities, the method can generate an initial inspection sequence that reflects real-time operational needs. This inspection strategy based on dynamic adjustment of time not only improves the timeliness and pertinence of inspections, but also optimizes resource allocation and avoids unnecessary frequent inspections of parking positions that will not change in the short term.

[0011] Optionally, the initial inspection sequence is adjusted in combination with the first position and the second position to determine the inspection sequence of each parking position in the airport, including: determining the distance between each parking position in the airport in combination with the first position and the second position; calculating the distance between adjacent parking positions in the initial inspection sequence based on the distance between each parking position in the airport; when the distance between adjacent parking positions in the initial inspection sequence is greater than a preset distance, adjusting the sequence of the adjacent parking positions in the initial inspection sequence until the distance between adjacent parking positions in the initial inspection sequence is no greater than the preset distance, thereby obtaining the inspection sequence of each parking position in the airport.

[0012] By adopting the above technical solution, the distance between each parking position is calculated using the first position and the second position information, and then the distance between adjacent parking positions in the initial inspection sequence is evaluated. When it is found that the distance between adjacent parking positions exceeds the preset threshold, the method will dynamically adjust the inspection sequence until the distance between all adjacent parking positions does not exceed the preset value. This distance-based optimization strategy can effectively reduce the ineffective movement of the mechanical dog between parking positions, thereby significantly improving the inspection efficiency. By combining time priority with space optimization, the scheme 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 energy consumption, extend the working time of the mechanical dog, and at the same time ensure the comprehensiveness of the inspection coverage.

[0013] Optionally, the inspection route of each robot dog is generated by combining the position of each robot dog, the remaining power of each robot dog and the inspection order of each parking space in the airport, including: generating an initial inspection route of each robot dog according to the position of each robot dog and the inspection order of each parking space in the airport; and adjusting the initial inspection route of each robot dog according to the remaining power of each robot dog to generate an inspection route for each robot dog.

[0014] By adopting the above technical solution, the initial inspection route is generated according to the current position of each robot dog and the determined parking inspection order, which ensures that the basic allocation of inspection tasks complies with the principle of space efficiency. Subsequently, the method further adjusts the initial inspection route considering the remaining power of each robot dog. This step effectively solves the power management problem and avoids inspection interruptions caused by insufficient power. By combining location information and power status, the scheme not only optimizes the inspection path and reduces the ineffective movement of robot dogs between parking positions, but also reasonably allocates tasks according to the actual energy status of each robot dog, ensuring that each robot dog can complete the specified inspection task within its power range. This method that comprehensively considers space efficiency and energy management significantly improves the reliability and sustainability of the entire inspection system, while maximizing the work efficiency of the robot dog group.

[0015] Optionally, the initial inspection route of each robot dog is generated according to the position of each robot dog and the inspection order of each parking position in the airport, including: determining the distance between each robot dog and each parking position in the airport; allocating an initial inspection parking position to each robot dog according to the distance between each robot dog and each parking position in the airport; determining a subsequent inspection parking position of the initial inspection parking position of each robot dog according to the inspection order of each parking position in the airport; and using the initial inspection parking position and the subsequent inspection parking position of each robot dog as the initial inspection route of each robot dog.

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

[0017] Optionally, the initial inspection route of each of the mechanical dogs is adjusted according to the remaining power of each of the mechanical dogs to generate the inspection route of each of the mechanical dogs, including: calculating the target power for each of the mechanical dogs to complete the initial inspection route; when the remaining power of the first mechanical dog is less than the target power, calculating the power difference between the remaining power of the second mechanical dog and the target power, the second mechanical dog being a mechanical dog with a remaining power greater than the target power; according to the power difference, allocating part of the initial inspection route of the first mechanical dog to the second mechanical dog to generate the inspection route of each of the mechanical dogs.

[0018] By adopting the above technical solution, the target power required for each robot dog to complete the initial inspection route is calculated, providing a quantitative basis for subsequent adjustments. When it is found that the remaining power of a robot dog is insufficient to complete its initial inspection task, the method will identify the robot dog with sufficient power and calculate the difference in power available for additional tasks. Based on this difference, the system intelligently reallocates part of the inspection task that the first robot dog cannot complete to the second robot 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 robot dog, but also makes full use of the remaining resources in the system to ensure the continuity and integrity of the overall inspection task.

[0019] In a second aspect, the present application provides a mechanical dog inspection system, the system comprising: 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 first parking position information of a first parking position in an airport, and a first position of the first parking position; wherein the first parking position is a parking position where an aircraft exists, and the first parking position information is the departure time of the aircraft at the first parking position; the second acquisition module is used to acquire second parking position information of a second parking position, and a second position of the second parking position; wherein the second The parking stand is a parking stand at which no aircraft exists, and the second stand information is the time the second parking stand is occupied; the first combining module is used to combine the first position, the second position, the first stand information and the second stand information to determine the inspection order of each parking stand in the airport; the third obtaining module is used to obtain the positions of multiple robot dogs in the airport and the remaining power of each robot dog; the second combining module is used to combine the position of each robot dog, the remaining power of each robot dog and the inspection order of each parking stand in the airport to generate an inspection route for each robot dog.

[0020] In the third aspect, the present application provides an electronic device, which adopts the following technical solution: 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, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the above-mentioned mechanical dog inspection methods.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: a computer program that can be loaded by a processor and execute any of the above-mentioned mechanical dog inspection methods is stored.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. Effectively improve inspection efficiency, avoid repeated inspections or omissions of important areas, and ensure the power management of the robot dog to reduce inspection interruptions caused by insufficient power; 2. 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 space in the airport, improve the comprehensiveness and timeliness of the inspection, and thus enhance the overall safety and operational efficiency of the airport. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of a mechanical dog inspection method provided in an embodiment of the present application; Figure 2It is a structural schematic diagram of a mechanical dog inspection system provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0024] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0025] 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 drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0027] The robot dog inspection method of the present invention is mainly used in the daily operation and management of modern intelligent airports. In large international airports, especially those with many parking spaces, traditional manual inspection methods face many challenges and limitations. Therefore, the introduction of robot dogs for automated inspection has become an important measure to improve the safety, efficiency and economy of airports.

[0028] The robot dog can work 24 hours a day without interruption, is not restricted by human working hours and physical strength, and can complete parking space inspection tasks more frequently and comprehensively.

[0029] At the same time, the robot dog is equipped with advanced sensors and camera equipment, which can promptly detect and report safety hazards such as fuel leaks, abnormal objects, etc., greatly improving the overall safety level of the airport.

[0030] In addition, the robot dog can inspect according to precise routes and schedules, and will not miss important areas due to fatigue or distraction, ensuring that each parking space is properly inspected. The robot dog also has good mobility and can move flexibly in small spaces and complex terrains, reaching areas that are difficult for humans to reach for inspection.

[0031] Finally, the robot dog can collect and transmit inspection data in real time. Combined with artificial intelligence technology, it can quickly analyze data and provide decision support, helping airport managers to find and solve problems in a timely manner. In extreme weather conditions, the robot dog can continue to perform inspection tasks, reducing the risk of personnel working in harsh environments.

[0032] The introduction of the robot dog inspection system is an important part of the intelligent and digital transformation of airports, which helps to improve the overall operational efficiency and international competitiveness of airports. By setting up robot dogs and applying the inspection method of the present invention, airports can achieve safer, more efficient and more economical operation management, provide passengers with better services, and also lay the foundation for the sustainable development of airports.

[0033] Figure 1 FIG. 1 is a flow chart of a mechanical dog inspection method provided in an embodiment of the present application. Figure 1 As shown, the method includes S101-S105: S101, obtaining first parking stand information of a first parking stand in an airport and a first position of the first parking stand; wherein the first parking stand is a parking stand where an aircraft is present, and the first parking stand information is a departure time of the aircraft at the first parking stand.

[0034] Specifically, in airport operations, obtaining parking space information and inspecting the parking spaces are key links in ensuring safe and efficient operations of the airport.

[0035] The main reasons for inspecting the parking stands are as follows: Through inspection, potential safety hazards around the parking stands can be discovered in time, such as ground damage, foreign objects, water accumulation, etc., so as to prevent these problems from causing potential harm to the parked aircraft. Regular inspections help to promptly discover damage or abnormalities in parking stand-related facilities (such as fixed power supplies, refueling equipment, etc.), ensure that these facilities can operate normally, and provide necessary ground services for aircraft. By ensuring that the parking stands are in the best condition through inspections, flight delays or cancellations caused by parking stand problems can be reduced, and the overall operational efficiency of the airport can be improved.

[0036] In one example, the first parking stand refers to the parking stand where an aircraft is currently located, and the first parking stand information specifically refers to the estimated departure time of the aircraft at the parking stand. The implementation of this step is crucial for subsequent inspection planning because it provides key information on the parking stand usage status and schedule.

[0037] The system can obtain the required information by interacting with the airport management system in real time. For example, the airport's flight management system API interface can be used to query all currently occupied parking positions. For each occupied parking position, the system records its unique identifier (as a representation of the first position) and the scheduled departure time of the aircraft parked at that position (as the first position information). This data can be stored in a structured data set, such as a data table containing parking position ID, geographic coordinates, and departure time.

[0038] The purpose of obtaining this information is to accurately assess the urgency of inspections at each parking stand. Parking stands where aircraft are about to depart usually require priority inspections to ensure that the parking stand status is checked in time after the aircraft leaves. In addition, knowing the specific location of the parking stand will help to plan the optimal inspection route and improve inspection efficiency.

[0039] S102, obtaining second parking stand information of a second parking stand and a second position of the second parking stand; wherein the second parking stand is a parking stand where no aircraft exists, and the second parking stand information is the time the second parking stand is occupied.

[0040] In one example, the system can obtain the required information by interacting with the airport's parking stand management system. For example, the airport's resource allocation system can be queried to obtain information about all currently idle but scheduled parking stands. For each such parking stand, the system records its unique identifier or geographic coordinates (as a representation of the second location) and the estimated arrival time of the next scheduled aircraft (as the second stand information). These data can also be integrated into a structured data set, together with the information of the first parking stand, to form a complete airport parking stand usage status map.

[0041] The importance of obtaining the second parking stand information is that it enables the inspection system to predictably schedule inspection tasks. Although there is no aircraft at the vacant parking stand, it also needs to be regularly inspected to ensure that it is in a usable state. Especially before the next aircraft arrives, timely inspections can ensure the safety and availability of the parking stand. By knowing the time when the second parking stand is about to be occupied, the system can reasonably arrange the inspection time, which will not affect the use of the parking stand by the upcoming aircraft, and ensure that the necessary inspections and possible maintenance work are completed before the aircraft arrives.

[0042] S103, determining an inspection sequence of each parking stand in the airport in combination with the first position, the second position, the first parking stand information and the second parking stand information.

[0043] In one example, the system first determines an initial inspection priority based on the first stand information (ie, the departure time of the aircraft at the parking stand where the aircraft is present) and the second stand information (ie, the occupied time of the vacant parking stand).

[0044] For the first parking stand, the system will calculate the difference between the aircraft departure time and the current time. The smaller the difference, the higher the priority. Similarly, for the second parking stand, the system will calculate the difference between the occupied time and the current time. The smaller the difference, the higher the priority. This method ensures that the parking stand that is about to change its status can be inspected in time.

[0045] Then, the system will optimize and adjust the inspection order initially determined by combining the first and second position information. The purpose of this step is to minimize the ineffective movement of the robot dog between parking positions while ensuring the timeliness of the inspection. The system may use 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.

[0046] During the optimization process, the system will also consider some practical constraints. For example, the distance between adjacent inspection points should not be too large to prevent the robot dog from running between parking positions for a long time and being unable 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 that is closer to optimize the path.

[0047] Based on the above embodiment, as an optional implementation, in S103, combining the first position, the second position, the first aircraft stand information and the second aircraft stand information, determining the inspection order of each parking stand in the airport specifically includes S31-S32: S31, combining the first parking position information and the second parking position information, determining an initial inspection sequence of each parking position in the airport.

[0048] Specifically, the system will first process the first stand information, that is, the departure time of the aircraft at the parking stand with the aircraft. The system will calculate the difference between the estimated departure time of the aircraft and the current time for each parking stand with an aircraft. The smaller the difference, the sooner the aircraft will leave, and the higher the inspection priority of the parking stand. At the same time, the system will also process the second stand information, that is, the occupied time of the idle parking stand. The system will calculate the difference between the estimated occupied time and the current time for each idle parking stand. The smaller the difference, the sooner the parking stand will be occupied by a new aircraft, and therefore the higher its inspection priority.

[0049] After obtaining these time differences, the system will sort all parking spaces from small to large according to the time differences to form an initial inspection order.

[0050] Based on the above embodiment, as an optional implementation, in S31, combining the first parking position information and the second parking position information, determining the initial inspection sequence of each parking position in the airport specifically includes S311-S313: S311, determining a first inspection priority of the first parking position according to the first parking position information, wherein 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.

[0051] S312: Determine a second inspection priority of the second parking position according to the second parking position information, wherein the second inspection priority increases as the time difference between the occupied time of the second parking position and the current time decreases.

[0052] S313, determining an initial inspection sequence of each parking space in the airport according to the first inspection priority and the second inspection priority.

[0053] In one example, the system first processes the first parking stand information, that is, the parking stand where the aircraft is located. For each first parking stand, the system calculates the time difference between the estimated departure time of the aircraft on it and the current time. Based on this time difference, the system assigns the first inspection priority to the first parking stand. The smaller the time difference, the sooner the aircraft will leave, so the higher the first inspection priority assigned. This design ensures that the parking stand where the aircraft is about to take off can be inspected in time, which helps to ensure flight safety and on-time take-off.

[0054] Next, the system processes the second parking stand information, that is, the parking stands that are currently vacant but are about to be occupied. For each second parking stand, the system calculates the time difference between its expected occupation time and the current time. Based on this time difference, the system assigns the second inspection priority to the second parking stand. The smaller the time difference, the faster the parking stand will be occupied by a new aircraft, so the higher the second inspection priority assigned. This design ensures that the parking stands that are about to receive new aircraft can be fully inspected before the aircraft arrives and prepared for safe parking.

[0055] After determining the inspection priorities of all parking stands, the system determines the initial inspection order of each parking stand in the airport based on these priorities. This process may involve weighing multiple factors. First, the system will make a unified quantitative comparison between 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 stand and the second parking stand will be given the highest inspection priority.

[0056] The system will then sort all parking spaces 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 priority of parking spaces that have not been inspected for a long time. In addition, some parking spaces for special purposes or important locations may be given additional weights to ensure that they can be inspected more frequently.

[0057] S32, adjusting the initial inspection sequence in combination with the first position and the second position to determine the inspection sequence of each parking position in the airport.

[0058] Specifically, the system will first obtain the first location information, that is, the current location of each robot dog, and the second location information, that is, the location of each parking position. Then, based on this location information, the system will calculate the distance from each robot dog to each parking position. This distance can be a straight-line distance or a path distance that takes into account the actual terrain and obstacles of the airport.

[0059] Next, the system will optimize the inspection order based on the previously determined initial inspection order and the calculated distance information. This process involves weighing and optimizing multiple factors. First, the system will try to maintain the inspection timing of high-priority parking positions in the initial inspection order to ensure that time-critical inspection tasks can be completed in a timely manner. At the same time, the system will consider the location of the robot dog and try to assign parking positions that are close to each other to the same robot dog to reduce the time it takes for the robot dog to move between parking positions.

[0060] Based on the above embodiment, as an optional implementation, in S32, the initial inspection sequence is adjusted in combination with the first position and the second position, and the inspection sequence of each parking position in the airport is determined, which specifically includes S321-S323: S321, determining the distance between each parking position in the airport by combining the first position and the second position.

[0061] S322, calculating the distances between adjacent parking stands in the initial inspection sequence according to the distances between the parking stands in the airport.

[0062] S323, when the distance between adjacent parking positions in the initial inspection sequence is greater than the preset distance, adjust the order of the adjacent parking positions in the initial inspection sequence until the distance between adjacent parking positions in the initial inspection sequence is no greater than the preset distance, thereby obtaining the inspection order of each parking position in the airport.

[0063] In one example, the system first combines the first position (the current position of the robot dog) and the second position (the position of each parking position) information to calculate the distance between each parking position in the airport. This distance can be a straight-line distance or a path distance that takes into account the actual terrain and obstacles of the airport. Through this step, the system establishes a complete parking position distance matrix, providing basic data for subsequent path optimization.

[0064] Next, the system analyzes the distances between adjacent parking spots in the initial inspection sequence based on the calculated parking spot distance information. 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 long distances between adjacent inspection points, thereby increasing unnecessary movement of the robot dog.

[0065] The system sets a preset distance threshold. When it is found that the distance between adjacent parking stands in the initial inspection sequence is greater than the preset distance, the adjustment mechanism will be triggered. The adjustment process will try to swap or insert other parking stands to shorten the distance between adjacent parking stands. This process will be repeated until the distance between all adjacent parking stands in the initial inspection sequence is no greater than the preset distance, thus obtaining the optimized inspection sequence of each parking stand in the airport.

[0066] During the adjustment process, the system uses intelligent algorithms to balance multiple factors. First, the system will try to maintain the inspection sequence of high-priority parking spaces to ensure that time-sensitive inspection tasks can be completed in a timely manner. Second, the system will consider the optimization of the overall path and try to find an optimal solution that can meet the distance requirements and ensure inspection efficiency. In addition, the system may also consider the terrain characteristics of the airport to prevent the robot dog from frequently crossing difficult terrain or obstacles.

[0067] Assume there is a medium-sized airport with 10 parking stands that need to be inspected, numbered A1 to A10. The airport has two robot dogs (Dog1 and Dog2) for inspection tasks.

[0068] First, the initial inspection order is: A3>A7>A1>A9>A4>A2>A6>A10>A5>A8, among which A3 is the parking position that most urgently needs inspection, and A8 is the least urgent parking position.

[0069] Calculate the distance between parking stands (unit: meters). Some distance data are as follows: A3 to A7: 500 meters, A7 to A1: 800 meters, A1 to A9: 300 meters, A9 to A4: 700 meters...

[0070] Calculate the distance between adjacent parking positions: A3 to A7: 500 meters, A7 to A1: 800 meters, A1 to A9: 300 meters, A9 to A4: 700 meters...

[0071] The preset distance is set to 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 try to adjust the order. For example, it may try 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 try to move A4 before A9.

[0072] After multiple iterations and adjustments, a new inspection order was obtained: A3>A1>A7>A4>A9>A2>A6>A10>A5>A8. In this new order, the distance between all adjacent parking stands is no more than 600 meters, while also maintaining the original priority order as much as possible.

[0073] Finally, the system will consider the positions of the two robot dogs and may distribute the tasks as follows: Dog1: A3>A1>A7>A4>A9, Dog2: A2>A6>A10>A5>A8.

[0074] This allocation not only ensures that high-priority parking positions (such as A3, A1, and A7) can be inspected in a timely manner, but also optimizes the movement path of each robot dog and reduces unnecessary long-distance movement.

[0075] S104, obtaining the positions of multiple robot dogs in the airport and the remaining power of each robot dog.

[0076] In one example, the system can obtain the location and power information of the robot dog through a variety of technical means. For location information, the GPS positioning system or indoor positioning technology (such as UWB, RFID, etc.) can be used to track the specific location of each robot dog in real time. These location data usually include longitude and latitude coordinates or coordinates relative to specific reference points at the airport. For power information, each robot 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).

[0077] The system will actively obtain this information periodically (for example, every few minutes) or when a new task needs to be assigned. The acquired data will be integrated into a real-time updated database containing information such as the unique identifier of each robot dog, current location coordinates, remaining battery percentage, etc.

[0078] S105, generating an inspection route for each robot dog based on the position of each robot dog, the remaining power of each robot dog, and the inspection sequence of each parking space in the airport.

[0079] In one example, a preliminary task list is established based on the previously determined inspection order of each parking space in the airport. The system then assigns tasks and plans routes through a series of optimization steps, taking into account the current position and remaining power of each robot dog.

[0080] During the optimization process, the system considers the following key factors: Distance efficiency: The system will try to assign parking spaces that are close to each other to the same robot dog to reduce the time it takes the robot dog to move between parking spaces.

[0081] Power management: The system will reasonably allocate tasks according to the remaining power of each robot dog. For robot dogs with lower power, fewer or closer tasks may be assigned, and charging will be arranged at an appropriate time.

[0082] Time urgency: For parking spaces with higher priority in the inspection sequence, the system will give priority to the robot dogs that are closer or have sufficient power.

[0083] Load balancing: The system will try to balance the workload of each robot dog to avoid overuse of some robot dogs while others are idle.

[0084] Charging planning: When generating inspection routes, the system will also consider the location of charging stations and arrange for the robot dog to charge in a timely manner to ensure continuous operation.

[0085] Based on the above embodiment, as an optional implementation, in S105, the inspection route of each robot dog is generated by combining the position of each robot dog, the remaining power of each robot dog and the inspection order of each parking space in the airport, which specifically includes S51-S52: S51, generating an initial inspection route for each robot dog according to the position of each robot dog and the inspection order of each parking space in the airport.

[0086] In S51, according to the position of each robot dog and the inspection order of each parking space in the airport, the initial inspection route of each robot dog is generated, which specifically includes S511-S514: S511, determining the distance between each robot dog and each parking position in the airport.

[0087] S512, allocating an initial inspection parking position for each robot dog according to the distance between each robot dog and each parking position in the airport.

[0088] In one example, the system first obtains the current location information of each robot dog and the location data of all parking spaces that need to be inspected. This data may come from the airport's real-time positioning system, such as GPS or specialized indoor positioning technology. The system uses this location data to calculate the distance matrix from each robot dog to each parking space. This distance may be a straight-line distance or a path distance that takes into account the actual terrain and possible obstacles of the airport, depending on the design of the system and the actual situation of the airport.

[0089] Next, the system uses an intelligent allocation algorithm to assign an initial inspection parking position to each robot dog. The core of this algorithm is to minimize the overall moving distance while considering the priority of the parking position and the balance of tasks. The algorithm will first try to assign the closest parking position to the corresponding robot dog, but this is not the only consideration. If a parking position that is far away but has a high priority requires urgent inspection, the system may choose to assign it to a robot dog, even if there is a parking position that is closer. This trade-off ensures that important inspection tasks will not be delayed due to distance factors.

[0090] To achieve this goal, the system may find a globally optimal or near-optimal allocation solution while considering multiple constraints. In actual operation, the system may assign a comprehensive score to each parking space, which not only considers distance factors, but also includes multiple dimensions such as priority and urgency. The algorithm will make allocations based on this comprehensive score.

[0091] In addition, the algorithm also considers the balance of tasks. It will try to avoid assigning all close or high-priority parking spaces to the same robot dog, but try to achieve a relatively balanced distribution of tasks while ensuring efficiency. The purpose of this is to avoid overuse of some robot dogs while others are relatively idle, thereby improving the efficiency and reliability of the entire system.

[0092] During the allocation process, the algorithm also takes into account the airport's terrain features and possible obstacles. For example, if there is an insurmountable obstacle between two parking stands, the system may assign them to different robot dogs even if they are close in a straight line. This consideration ensures that the generated initial inspection route is feasible and avoids problems that may be encountered during actual execution.

[0093] Finally, the system assigns an initial inspection parking position to each robot dog and reserves space for subsequent dynamic adjustments. This approach enables the system to better respond to real-time changes, such as sudden high-priority inspection needs or temporary failures of robot dogs. The system may re-evaluate and adjust the allocation plan regularly or based on specific trigger conditions to ensure continuous optimization of inspection work.

[0094] S513, according to the inspection sequence of each parking position in the airport, determine the subsequent inspection parking position of the initial inspection parking position of each robot dog.

[0095] In one example, the system first reads the inspection order of each parking space in the airport that has been optimized in the previous step. This inspection order is based on a variety of factors, including the importance, urgency, and geographical location of the parking space. At the same time, the system also obtains the initial inspection parking space information assigned to each robot dog in step S512.

[0096] Next, the system uses an intelligent algorithm to determine the sequence of subsequent inspection stops for each robot dog after its initial inspection stop. The core of this algorithm is to assign the most appropriate subsequent inspection task to each robot dog while ensuring the overall inspection sequence. The algorithm considers the following key factors: First, the algorithm follows the previously determined overall inspection order. This ensures that high-priority or urgent parking spaces that require inspection can be processed in a timely manner. However, the algorithm does not simply assign tasks in a fixed order, but makes optimization adjustments based on actual conditions.

[0097] Second, the algorithm considers the task balance between the robot dogs. It tries to avoid situations where some robot dogs are overloaded while others are relatively idle. This may mean fine-tuning the inspection order of individual parking spaces to achieve better task distribution while maintaining the overall inspection order.

[0098] Furthermore, the algorithm also takes into account geographic location and mobility efficiency. When determining the parking positions for subsequent inspections, it will try to choose parking positions that are close to the current position or on the moving path to reduce unnecessary long-distance movements and improve overall inspection efficiency.

[0099] In addition, the algorithm will take into account the performance parameters of the robot dog, such as battery life, movement speed, etc. It will adjust the assigned tasks and inspection routes based on these parameters to ensure that each robot dog can complete the task efficiently within its capabilities.

[0100] 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 iterative optimizations until a balance point is reached, that is, while ensuring the overall inspection order, the task balance and movement efficiency are optimized.

[0101] It is worth noting that the determination of the subsequent inspection parking position is not a static process that is completed once. The system will retain a certain degree of flexibility and allow dynamic adjustments according to the actual on-site conditions during the actual inspection process. For example, if a robot dog finds a problem that needs urgent treatment during the inspection, the system may adjust the subsequent inspection order in real time to give priority to this emergency.

[0102] S514, taking the initial inspection parking position and subsequent inspection parking position of each robot dog as the initial inspection route of each robot dog.

[0103] Assume that we have a medium-sized airport with 20 parking stands that need to be inspected, numbered from A1 to A20. The airport is equipped with 3 robot dogs, numbered Dog1, Dog2, and Dog3. In step S512, the system has assigned initial inspection parking stands to these robot dogs: Dog1 is assigned to A3, Dog2 is assigned to A12, and Dog3 is assigned to A18.

[0104] In step S513, the system determines the subsequent inspection parking position for each robot dog. Assume that after the 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.

[0105] The system's intelligent algorithm takes this overall order into account, as well as factors such as task balance, geographic location, and mobility efficiency. After calculation, the system may come up with the following subsequent inspection parking lot allocation: Dog1 (initial position A3): A4>A5>A6>A1>A2>A7>A8>A9>A10; Dog2 (initial position A12): A13>A14>A15>A16>A17>A11; Dog3 (initial position A18): A19>A20; This allocation scheme reflects several key considerations: The overall order is followed: for example, A4 is assigned to Dog1 immediately after A3, and A13 is assigned to Dog2 immediately after A12.

[0106] Task balance: Although Dog3's initial position is at the back, the system does not assign all the remaining tasks to it, but tries to balance the workload of the three mechanical dogs.

[0107] Geographic location and movement efficiency: The system tries to make each robot dog move between adjacent or nearby parking positions. For example, the parking positions that Dog1 is responsible for are mostly concentrated in the range of A1 to A10.

[0108] Flexibility: The system does not allocate all parking spaces at once, but assigns a certain number of follow-up tasks to each robot dog, so that adjustments can be made according to the actual situation during the actual execution.

[0109] S52, adjusting the initial inspection route of each robot dog according to the remaining power of each robot dog, and generating the inspection route of each robot dog.

[0110] In S52, the initial inspection route of each robot dog is adjusted according to the remaining power of each robot dog, and the inspection route of each robot dog is generated, which specifically includes S521-S523: S521, calculating the target power consumption of each robot dog to complete the initial inspection route.

[0111] S522, when the remaining power of the first robot dog is less than the target power, the power difference between the remaining power of the second robot dog and the target power is calculated, and the second robot dog is a robot dog whose remaining power is greater than the target power.

[0112] In one example, the system first continuously monitors the remaining power of all robot dogs. This step is triggered when the system detects that the remaining power of one or more robot dogs (called the first robot dog) is lower than the preset target power. The target power is a threshold value pre-set by the system, which represents the minimum power required for the robot 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 robot dog, the distance from the current location to the nearest charging station, and the reserved safety margin.

[0113] Once the system detects that the remaining power of the first robot dog is lower than the target power, it will immediately start looking for a robot dog with a remaining power higher than the target power, which is the second robot dog. The system will calculate the difference between the remaining power of each second robot dog and the target power, i.e. the power difference. This power difference represents the power that the second robot dog can safely transfer to other robot dogs without affecting its normal operation.

[0114] The process of calculating the power difference may involve the following steps: The system first identifies all robot dogs whose remaining power is higher than the target power and marks them as potential second robot dogs.

[0115] For each potential second robot dog, the system calculates the difference between its remaining power and the target power.

[0116] The system may take into account the current mission status and location of each second robot dog. For example, if a second robot dog is performing an important mission or is far away from a charging station, the system may appropriately reduce the amount of power it can transfer to ensure its safety.

[0117] The system may also take into account the distance between the two robot dogs. If the two robot dogs are far apart, transferring power may consume too much energy, so the system may adjust the calculated power difference accordingly.

[0118] Finally, the system generates a final power difference value for each second robot dog, which represents the maximum amount of power that the robot dog can safely transfer.

[0119] S523, according to the power difference, part of the initial inspection route of the first robot dog is allocated to the second robot dog, and the inspection routes of each robot dog are generated.

[0120] 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 robot dog (i.e., the robot dog with a remaining power higher than the target power) can undertake. Based on this difference, the system selects an appropriate portion of the initial inspection route of the first robot dog (i.e., the robot dog with a remaining power lower than the target power) and allocates it to the second robot dog.

[0121] When redistributing routes, the system will consider multiple factors to ensure that the new allocation plan can not only solve the problem of insufficient power but also ensure overall inspection efficiency. These factors include but are not limited to: Power consumption estimation: The system estimates the power consumption required for each inspection route. This estimation is based on multiple parameters, such as route length, terrain complexity, expected inspection time, etc. The system will prioritize the route segment whose power consumption matches the difference between the power consumption of the second robot dog.

[0122] Geographic location: The system considers the current location of the first and second robot dogs, as well as the location of the route segment to be transferred. It will try to choose a solution that minimizes the moving distance of the two robot dogs to reduce unnecessary energy consumption.

[0123] Task urgency: If the initial inspection route contains some high-priority or urgent inspection points, the system will give priority to assigning these points to the second robot dog with sufficient power to ensure that these important tasks can be completed in time.

[0124] Robot dog performance parameters: The system will take into account the performance characteristics of different robot dogs, such as moving speed, climbing ability, etc., to ensure that the assigned tasks match the capabilities of the robot dogs.

[0125] Charging station location: When reallocating routes, the system takes the location of charging stations into account to ensure that each robot dog can reach the nearest charging station before the battery runs out.

[0126] Based on these considerations, the system uses intelligent algorithms to calculate the optimal route allocation. This process may involve the following steps: First, the system breaks down the initial inspection route of the first robot dog into several small segments. Then, it evaluates the characteristics of each segment, including the expected power consumption, importance, location, etc. Then, the system selects the most suitable route segment for transfer based on the power difference of the second robot dog. In this process, the system may use dynamic programming or greedy algorithms to find the optimal solution.

[0127] Once the route segment to be transferred is determined, the system will regenerate the inspection route for each robot dog. For the first robot dog, the new inspection route will exclude the transferred segment and may also add a path to the nearest charging station. For the second robot dog, the new inspection route will include its original route plus the new tasks received from the first robot dog.

[0128] Based on the above method, the present application also discloses a mechanical dog inspection system, such as Figure 2 As shown, Figure 2 is a structural diagram of a mechanical dog inspection system provided in an embodiment of the present application, the system comprises: 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 parking 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 is present, and the first parking position information is the departure time of the aircraft at the first parking position; the second acquisition module is used to acquire the second parking 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 is present, and the second parking 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 parking position information and the second parking position information to determine the inspection order of each parking position in the airport; the third acquisition module is used to acquire the positions of multiple robot dogs in the airport and the remaining power of each robot dog; the second combination module is used to generate the inspection route of each robot dog by combining the position of each robot dog, the remaining power of each robot dog and the inspection order of each parking position in the airport.

[0129] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0130] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As 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 .

[0131] The communication bus 1002 is used to realize the connection and communication between these components.

[0132] The user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0133] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0134] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, 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 calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0135] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (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, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally also be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As 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 of a mechanical dog inspection method.

[0136] exist Figure 3 In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program storing a mechanical dog inspection method in the memory 1005. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0137] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0138] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0139] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0140] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0141] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0142] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0143] 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, 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, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0144] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A mechanical dog inspection method, characterized in that: The method comprises: Acquire first parking stand information of a first parking stand in an airport and a first position of the first parking stand; wherein the first parking stand is a parking stand where an aircraft is present, and the first parking stand information is a departure time of the aircraft at the first parking stand; Acquire second parking stand information of a second parking stand and a second position of the second parking stand; wherein the second parking stand is a parking stand where no aircraft exists, and the second parking stand information is the time the second parking stand is occupied; Determine an inspection order of each parking stand in the airport by combining the first position, the second position, the first parking stand information, and the second parking stand information; Obtaining the positions of multiple robot dogs in the airport and the remaining power of each robot dog; The inspection routes of the robot dogs are generated by combining the positions of the robot dogs, the remaining power of the robot dogs and the inspection order of the parking spaces in the airport.

2. The mechanical dog inspection method according to claim 1, characterized in that: The step of determining the inspection sequence of each parking stand in the airport by combining the first position, the second position, the first parking stand information, and the second parking stand information includes: Determine an initial inspection sequence of each parking stand in the airport by combining the first parking stand information and the second parking stand information; The initial inspection sequence is adjusted in combination with the first position and the second position to determine the inspection sequence of each parking position in the airport.

3. The mechanical dog inspection method according to claim 2, characterized in that: The step of combining the first parking position information and the second parking position information to determine an initial inspection sequence of each parking position in the airport includes: Determine, according to the first parking position information, a first inspection priority of the first parking position, wherein 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; Determine a second inspection priority of the second parking position according to the second parking position information, wherein the second inspection priority increases as the time difference between the occupied time of the second parking position and the current time decreases; An initial inspection sequence of each parking space in the airport is determined according to the first inspection priority and the second inspection priority.

4. The mechanical dog inspection method according to claim 2, characterized in that: The step of adjusting the initial inspection sequence in combination with the first position and the second position to determine the inspection sequence of each parking space in the airport includes: Determine the distance between parking spaces in the airport based on the first position and the second position; Calculating the distances between adjacent parking stands in the initial inspection sequence according to the distances between the parking stands in the airport; When the distance between adjacent parking positions in the initial inspection sequence is greater than the preset distance, the order of the adjacent parking positions in the initial inspection sequence is adjusted until the distance between adjacent parking positions in the initial inspection sequence is no greater than the preset distance, thereby obtaining the inspection order of each parking position in the airport.

5. The mechanical dog inspection method according to claim 1, characterized in that: The generating of the inspection route of each robot dog by combining the position of each robot dog, the remaining power of each robot dog and the inspection order of each parking space in the airport includes: Generating an initial inspection route for each of the robot dogs according to the position of each of the robot dogs and the inspection order of each parking space in the airport; According to the remaining power of each of the mechanical dogs, the initial inspection route of each of the mechanical dogs is adjusted to generate the inspection route of each of the mechanical dogs.

6. The mechanical dog inspection method according to claim 5, characterized in that: The method of generating an initial inspection route for each of the robot dogs according to the position of each of the robot dogs and the inspection order of each parking space in the airport comprises: Determining the distance between each of the mechanical dogs and each parking space in the airport; Allocating an initial inspection parking position for each of the robot dogs according to the distance between each of the robot dogs and each of the parking positions in the airport; Determining the subsequent inspection parking positions of the initial inspection parking positions of each of the robot dogs according to the inspection order of each parking position in the airport; The initial inspection parking position and the subsequent inspection parking position of each robot dog are used as the initial inspection route of each robot dog.

7. The mechanical dog inspection method according to claim 5, characterized in that: The method of adjusting the initial inspection route of each of the mechanical dogs according to the remaining power of each of the mechanical dogs to generate the inspection route of each of the mechanical dogs includes: Calculate the target power of each of the mechanical dogs to complete the initial inspection route; When the remaining power of the first robot dog is less than the target power, the power difference between the remaining power of the second robot dog and the target power is calculated, and the second robot dog is a robot dog whose remaining power is greater than the target power; According to the power difference, part of the initial inspection route of the first robot dog is allocated to the second robot dog to generate the inspection route of each robot dog.

8. A mechanical dog inspection system, characterized in that: The system comprises: 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 first parking stand information of a first parking stand in the airport and a first position of the first parking stand; wherein the first parking stand is a parking stand where an aircraft is present, and the first parking stand information is a departure time of the aircraft at the first parking stand; The second acquisition module is used to acquire second parking stand information of a second parking stand and a second position of the second parking stand; wherein the second parking stand is a parking stand where no aircraft exists, and the second parking stand information is the time the second parking stand is occupied; The first combining module is used to combine the first position, the second position, the first parking position information and the second parking position information to determine the inspection order of each parking position in the airport; The third acquisition module is used to acquire the positions of multiple robot dogs in the airport and the remaining power of each robot dog; The second combining module is used to combine the position of each of the robot dogs, the remaining power of each of the robot dogs and the inspection sequence of each parking space in the airport to generate an inspection route for each of the robot dogs.

9. 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, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-7.

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

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