Intelligent planning method and system for passenger plane article loading

Abstract

The invention provides a passenger plane article loading intelligent planning method and system, and the method comprises the steps: obtaining a three-dimensional model of a loading space in a passenger plane and the size and weight information of loaded articles, and building an intelligent distribution and loading information system; inputting the size information of the loaded article into a preset three-dimensional model, and outputting a three-dimensional model of the loaded article through the three-dimensional model; by taking the weight information of the loaded article as a constraint condition, matching the three-dimensional model of the loaded article with the three-dimensional model of the loading space through a pre-trained planning model, and planning and generating a placement scheme of the loaded article based on an intelligent distribution and loading and stowage information system; and sending a loading instruction to a worker and a freight station according to the placement scheme, and carrying out loading work. The problem that the loading space utilization rate of an existing passenger plane is low is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of aviation cargo loading, and in particular to an intelligent planning method and system for passenger aircraft article loading. Background Art

[0002] The current situation of cargo loading in the belly of passenger aircraft completely relies on the LDP stowage system. Although the visualization, graphics, intelligent and automated operation of a single aircraft has been realized, the use of AI technology to accurately collect luggage information, model and deep learning has not been realized, and the three-dimensional stacking guidance of luggage loading personnel has not been realized. There is no real-time information interaction with the air cargo system, which cannot maximize the use of the belly; there is no real-time information interaction with the air cargo system, and the belly loading information cannot be provided to the cargo station in real time, so a large amount of cargo cannot be loaded in time; and because the stowage information is closely related to the bookable cargo space, relying only on real-time data often causes the idle space resources after the passenger transport is cut off. Summary of the invention

[0003] The present invention provides a method and system for intelligent planning of article loading on a passenger aircraft, which are used to solve the problem of low utilization rate of loading space of existing passenger aircraft.

[0004] The present invention provides an intelligent planning method for loading items on a passenger aircraft, comprising: Obtain the three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establish an intelligent allocation and loading information system; Inputting the size information of the loaded object into a preset three-dimensional model, and outputting a three-dimensional model of the loaded object through the three-dimensional model; Taking the weight information of the loaded items as a constraint condition, the three-dimensional model of the loaded items is matched with the three-dimensional model of the loading space through a pre-trained planning model, and a placement plan for the loaded items is generated based on the establishment of an intelligent allocation and loading and stowage information system planning; According to the placement plan, loading instructions are sent to the staff and the freight station to carry out the loading work.

[0005] According to a method for intelligent planning of loading items on a passenger aircraft provided by the present invention, the step of obtaining a three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items specifically includes: Obtain the three-dimensional model of the loading space of the belly compartment and luggage compartment of the passenger aircraft; At the item consignment point, the size information of the loaded items is collected through the camera, and the weight information of the loaded items is obtained through the weighing equipment.

[0006] According to an intelligent planning method for loading items on a passenger aircraft provided by the present invention, the size information of the loaded items is input into a preset three-dimensional model, and a three-dimensional model of the loaded items is output through the three-dimensional model, which specifically includes: Input the collected size information of the loaded items into a preset three-dimensional model; The three-dimensional model is divided into blocks according to the size information of the loaded objects, and a three-dimensional model of the loaded objects is constructed by combining multiple blocks.

[0007] According to the present invention, a method for intelligent planning of loading items on a passenger aircraft is provided. The method takes the weight information of the loaded items as a constraint condition, matches the three-dimensional model of the loaded items with the three-dimensional model of the loading space through a pre-trained planning model, and generates a placement plan for the loaded items based on intelligent allocation and loading and stowage information system planning, which specifically includes: Combining multiple three-dimensional models of loading items into an overall size model through a planning model; Performing size matching between the overall size model and the three-dimensional model of the loading space to generate a matching result; According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

[0008] According to an intelligent planning method for loading items on a passenger aircraft provided by the present invention, the position of the three-dimensional model of the loaded items is adjusted based on the matching result and the weight information of the loaded items is used as a constraint condition to generate a new overall size model until the overall size model matches the three-dimensional model of the loading space, specifically comprising: The weight information of the loaded items includes the weight limit and weight distribution requirements of the loading space; Determine the number of items that can be loaded according to the weight limit of the loading space, and determine the position adjustment plan of the three-dimensional model of the loaded items according to the weight distribution requirements of the loading space; The position of the three-dimensional model of the loaded items is adjusted according to the position adjustment plan of the three-dimensional model of the loaded items, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

[0009] According to a method for intelligent planning of passenger aircraft item loading provided by the present invention, sending loading instructions to staff and cargo stations according to the placement plan to perform loading work specifically includes: The loading instructions include the location and order of the items to be stacked and the remaining amount of loading space; The staff loads the items according to their stacking location and order, and the freight station loads and replenishes new items according to the remaining loading space.

[0010] The present invention also provides an intelligent planning system for loading articles on a passenger aircraft, the system comprising: Data acquisition module, used to obtain the three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establish an intelligent allocation and loading information system; A three-dimensional model building module, used for inputting the size information of the loaded object into a preset three-dimensional model, and outputting a three-dimensional model of the loaded object through the three-dimensional model; A solution generation module is used to match the three-dimensional model of the loaded items with the three-dimensional model of the loading space by a pre-trained planning model, taking the weight information of the loaded items as a constraint condition, and to generate a placement solution for the loaded items based on the intelligent allocation and loading and stowage information system planning; The loading module is used to send loading instructions to the staff and the freight station according to the placement plan to carry out loading work.

[0011] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the intelligent planning method for loading items on an aircraft as described above is implemented.

[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned intelligent planning methods for loading items on a passenger aircraft.

[0013] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for intelligent planning of passenger aircraft cargo loading as described above is implemented.

[0014] The present invention provides an intelligent planning method and system for loading items on a passenger aircraft. The method obtains the size and weight information of the loaded items for three-dimensional modeling, matches the three-dimensional model with the three-dimensional model of the loading space of the belly compartment and luggage compartment of the passenger aircraft, and uses the weight information of the loaded items as a constraint to generate a placement plan for the loaded items, thereby helping to rationally utilize the loading space inside the aircraft and improve the loading capacity of aircraft cargo. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a flow chart of an intelligent planning method for passenger aircraft cargo loading provided by the present invention.

[0017] Figure 2It is a schematic diagram of obtaining loading item information for intelligent planning of passenger aircraft loading of items provided by the present invention.

[0018] Figure 3 The present invention provides a schematic diagram of the module connection of an intelligent planning system for passenger aircraft cargo loading.

[0019] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention.

[0020] Reference numerals: 110: data acquisition module; 120: three-dimensional model building module; 130: solution generation module; 140: loading module; 410: processor; 420: communication interface; 430: memory; 440: communication bus. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Combine the following Figure 1 and Figure 2 The invention describes an intelligent planning method for loading items on a passenger aircraft, comprising: step 100, obtaining a three-dimensional model of the loading space in the passenger aircraft and size and weight information of the loaded items, and establishing an intelligent allocation and loading information system.

[0023] In the present invention, the loading space in the passenger aircraft includes a belly compartment and a luggage compartment, and the volumes of different parts are different, and the types and sizes of items that can be placed are also different.

[0024] Specifically, a three-dimensional model of the loading space of the belly compartment and the luggage compartment of the passenger aircraft is obtained; At the item consignment point, the size information of the loaded items is collected through the camera, and the weight information of the loaded items is obtained through the weighing equipment.

[0025] In the present invention, the three-dimensional models of the belly compartment and luggage compartment inside the passenger aircraft can be constructed through the structural data obtained from the aircraft manufacturer, and the three-dimensional models of the belly compartment and luggage compartment can be accurately matched in the subsequent placement plan generation process.

[0026] The dimensions of passenger box luggage will be collected when passengers enter the terminal, check in (including counter check-in and self-service check-in), and board the plane at the boarding gate.

[0027] When passengers enter the terminal, the number of passenger's box luggage pieces and size parameters including length, width and height are collected and transmitted to the intelligent allocation and loading information system in real time.

[0028] During the check-in process at the counter, the number of pieces of luggage checked in by passengers, the size parameters of length, width and height, and weight parameters are collected and transmitted to the intelligent allocation and loading information system in real time.

[0029] During the self-service check-in process, the number of unchecked box-type luggage pieces and the size parameters of length, width and height of the passengers are collected and transmitted to the intelligent allocation and loading information system in real time. The calculation results are pushed to the self-service check-in machine and a reminder is issued that there is too much cargo in the luggage compartment.

[0030] During the boarding process at the boarding gate, the number of unchecked box-type luggage pieces and the size parameters of length, width and height of the passengers are collected and transmitted to the intelligent allocation and loading information system in real time. Real-time reminders of excessive cargo in the baggage hold are issued to ground service staff and passengers, and ground service staff are guided to transfer the suitcase-type luggage into the belly hold.

[0031] During the receiving and security inspection process at the freight station, the length, width, height and weight information of the consigned items are collected and transmitted to the intelligent distribution and loading information system in real time to guide the freight station's collection, stacking, reweighing, departure time control and other processes.

[0032] The size and weight information of the loaded items, in the checked baggage delivery link, the checked baggage is spatially scanned by a precision camera, and through AI deep learning, the effective target segmentation of people, checked baggage, etc. is completed, and the important physical parameters such as the length, width, height, baggage barcode, surface feature data, weight, etc. of the baggage are obtained, and a spatial model of the checked baggage is established for use in intelligent cabin loading calculations. In the security inspection of suitcase-type luggage, the box-type hand luggage is spatially scanned by a precision camera, and through AI deep learning, the effective target segmentation of people, hand luggage, etc. is completed, and the important parameters such as the length, width, height, and geometric shape of the suitcase-type luggage are obtained, and a spatial model of the hand luggage is established for use in intelligent cabin loading calculations.

[0033] In the cargo delivery process at the freight station, precision cameras are used to perform spatial scanning of the cargo, and AI deep learning is used to complete the effective segmentation of cargo, personnel and other targets. Important parameters such as length, width, height, weight, surface feature data, waybills, etc. are obtained for the cargo, and a spatial model of the cargo is established for use in intelligent cabin loading calculations.

[0034] Acquiring the size signal and weight information of the loaded items through various means will help to subsequently establish a three-dimensional model of the loaded items.

[0035] Step 200: input the size information of the loaded object into a preset three-dimensional model, and output a three-dimensional model of the loaded object through the three-dimensional model.

[0036] Specifically, it includes: inputting the collected size information of the loaded objects into a preset three-dimensional model; The three-dimensional model is divided into blocks according to the size information of the loaded objects, and a three-dimensional model of the loaded objects is constructed by combining multiple blocks.

[0037] In the present invention, the size information of each object, including length, width and height, is received from the data acquisition module; an appropriate resolution is selected to determine the fineness of the model according to the size and complexity of the object. For example, for larger and simple-shaped objects, larger blocks can be used; while for smaller or complex-shaped objects, smaller blocks are needed to accurately capture details.

[0038] Define a three-dimensional coordinate system, with one corner of the object as the origin (0,0,0), and then determine the end point coordinates in the other three dimensions based on the size information; based on the selected resolution, create a unit cube, which will be the basic unit for building the object model; perform block filling, starting from the origin, along the X, Y, and Z axis directions, according to the actual size information of the object, use unit cubes to fill the entire object's space range. For example, if the size of an object is 50cm x30cm x 20cm, and the selected unit cube side length is 10cm, then 5 unit cubes are required along the X axis, 3 unit cubes are required along the Y axis, and 2 unit cubes are required along the Z axis.

[0039] The constructed model needs to be corrected in shape. An algorithm is used to detect the outer surface of each object to determine which unit cubes should be considered as part of the object and which should be removed. This is achieved by comparing the positional relationship of adjacent unit cubes or using more advanced surface reconstruction algorithms. If there are holes or non-solid parts inside the object, additional logic is required to identify these areas and avoid filling them. For objects with arcs or curves, more unit cubes may need to be added at the boundaries for approximation to make the model closer to the actual shape of the object. In order to reduce the demand for computing resources, model simplification technology can be used to merge multiple adjacent unit cubes into larger cubes or polyhedrons; and texture or color information can be added to the surface of the model to make the final model look more realistic. The constructed 3D model is converted into a commonly used 3D file format, such as STL, OBJ or FBX, for subsequent processing and visualization. Through the above steps, a 3D model composed of many small cubes can be obtained, which can accurately reflect the real shape and size of the object, and then used in the next step of solution generation and loading process.

[0040] Step 300: Using the weight information of the loaded items as a constraint condition, the three-dimensional model of the loaded items is matched with the three-dimensional model of the loading space through a pre-trained planning model, and a placement plan for the loaded items is generated based on intelligent allocation and loading and stowage information system planning.

[0041] Specifically, it includes: combining multiple three-dimensional models of loading items into an overall size model through a planning model; Performing size matching between the overall size model and the three-dimensional model of the loading space to generate a matching result; According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

[0042] In the present invention, based on the aircraft cabin pre-sale information and utilizing the AI ​​deep learning function, the luggage cabin space data and model are combined with the passenger seat information and the box-type carry-on luggage information to conduct a priority cabin loading simulation analysis. At the same time, historical events of on-board baggage check-in are analyzed. Real-time luggage cabin loading calculation, analysis, and spatial model analysis are performed during check-in, passenger boarding security checks, and boarding at the boarding gate. For box-type carry-on luggage that needs to be checked in on board, early warnings are given and the luggage is checked in, thus saving time for on-board baggage check-in and reducing delays caused by on-board baggage check-in.

[0043] Based on the aircraft belly compartment space information and using AI deep learning functions, the aircraft belly compartment space data and model are combined with the submitted checked baggage information and restricted box-type carry-on baggage information to conduct priority space loading simulation analysis. At the same time, the cargo already received and pre-collected at the cargo terminal is analyzed for integrated loading, and instructions such as pre-loaded cargo quantity, deadline for delivery, and cargo terminal departure time are issued to the cargo terminal in real time.

[0044] According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition to generate a new overall size model until the overall size model matches the three-dimensional model of the loading space, specifically including: The weight information of the loaded items includes the weight limit and weight distribution requirements of the loading space; Determine the number of items that can be loaded according to the weight limit of the loading space, and determine the position adjustment plan of the three-dimensional model of the loaded items according to the weight distribution requirements of the loading space; The position of the three-dimensional model of the loaded items is adjusted according to the position adjustment plan of the three-dimensional model of the loaded items, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

[0045] In the present invention, the overall size model is matched with the three-dimensional model of the loading space; a greedy algorithm or other heuristic algorithm is used to try different arrangements and combinations to find the optimal solution; the correlation between items is considered, such as placing heavy or large items first, and then arranging other items.

[0046] For items with irregular shapes or that require special placement, consider the possibility of rotating them to better fit the space. If possible, adjust the direction or position of the item to achieve the best space utilization.

[0047] Based on weight constraints, ensure that the total weight of a single loading unit or area does not exceed the specified upper limit, and distribute the weight to avoid structural problems caused by overloading a certain part. Ensure that the center of gravity after loading is within a safe range to prevent the risk of tilting or tipping; there must be sufficient friction or other fixing measures between items to prevent sliding or collision during movement. Leave enough buffer space around fragile or sensitive items, and use appropriate packaging materials to avoid direct contact with other hard items to reduce the risk of damage. If there is a requirement for the order of shipment, the location of the items needs to be arranged according to priority, ensuring that the items used first are easier to take out, and considering the convenience of unloading, design a reasonable stacking order.

[0048] In actual operation, the application of size matching and constraint conditions often requires comprehensive consideration, and the scheme is adjusted continuously through algorithm iterative optimization until all conditions are met. In addition, the effectiveness and feasibility of the design scheme need to be verified through simulation or prototype testing. Finally, once the best solution is determined, it needs to be converted into a specific implementation plan to guide the actual operation process.

[0049] Step 400: Send loading instructions to staff and freight stations according to the placement plan to carry out loading work.

[0050] Specifically, the loading instructions include the location and order of the items to be stacked and the remaining amount of loading space; The staff loads the items according to their stacking location and order, and the freight station loads and replenishes new items according to the remaining loading space.

[0051] In the present invention, the effective loading rate of the belly compartment can be maximized through AI loading analysis of checked baggage, box-type hand luggage, and consigned cargo in the belly compartment. By issuing a real-time instruction on the loading capacity of consigned cargo to the cargo terminal, the airline can sell belly compartment space to the freight forwarder in advance, thereby reducing costs and increasing efficiency.

[0052] In the present invention, a pre-trained artificial intelligence prediction model is used for analysis, and the current flight baggage loading situation is predicted based on the changes in different local seasons, local specialties and local activities, and a preliminary prediction result is generated. According to the prediction result, if there is surplus belly cargo space, the remaining loading space information is sent to the freight station 12 hours in advance. The freight station matches the required acquisition according to the remaining loading space information, comprehensively considers the volume, weight and nature of the cargo, and transports the cargo to the terminal to wait for loading.

[0053] In the specific implementation process, belly loading space and luggage compartment loading space are provided for hand luggage and box luggage on a priority basis. The remaining belly loading space is compared with the remaining belly loading space predicted by the artificial intelligence prediction model according to the actual situation. If the comparison result is within the set error range, the loading operation of the goods is performed. When the actual situation determines that the remaining belly loading space is less than the remaining belly loading space predicted by the artificial intelligence prediction model, the loading and transportation service cannot be provided for the acquisition, and the goods are kept in the terminal, and the closest flights are matched for loading and transportation of the goods. In the transportation of special goods, such as pets, fish, etc., which have special needs, they are stored in the terminal all the time, so they will not cause damage or death to the special goods, thereby improving the transportation quality of special goods. Based on the intelligent planning method for loading passenger aircraft items provided by the present invention, three-dimensional modeling is performed by obtaining the size and weight information of the loaded items, and the three-dimensional model is matched with the three-dimensional model of the loading space of the belly compartment and luggage compartment of the passenger aircraft, and the weight information of the loaded items is used as a constraint to generate a placement plan for the loaded items, which helps to reasonably utilize the loading space inside the aircraft and improve the loading capacity of aircraft cargo.

[0054] refer to Figure 3 The present invention also discloses an intelligent planning system for loading items on passenger aircraft, the system comprising: The data acquisition module 110 is used to obtain the three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establish an intelligent allocation and loading information system; A three-dimensional model building module 120, used for inputting the size information of the loaded object into a preset three-dimensional model, and outputting a three-dimensional model of the loaded object through the three-dimensional model; A solution generation module 130 is used to match the three-dimensional model of the loaded objects with the three-dimensional model of the loading space by a pre-trained planning model, taking the weight information of the loaded objects as a constraint condition, and generating a placement solution for the loaded objects based on intelligent allocation and loading and stowage information system planning; The loading module 140 is used to send loading instructions to the staff and the freight station according to the placement plan to perform loading work.

[0055] The three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items are obtained, including: Obtain the three-dimensional model of the loading space of the belly compartment and luggage compartment of the passenger aircraft; At the item consignment point, the size information of the loaded items is collected through the camera, and the weight information of the loaded items is obtained through the weighing equipment.

[0056] Inputting the size information of the loaded object into a preset three-dimensional model, and outputting a three-dimensional model of the loaded object through the three-dimensional model, specifically includes: Input the collected size information of the loaded items into a preset three-dimensional model; The three-dimensional model is divided into blocks according to the size information of the loaded objects, and a three-dimensional model of the loaded objects is constructed by combining multiple blocks.

[0057] Taking the weight information of the loaded items as a constraint condition, the three-dimensional model of the loaded items is matched with the three-dimensional model of the loading space through a pre-trained planning model, and a placement plan for the loaded items is generated based on the intelligent allocation and loading and stowage information system planning, which specifically includes: Combining multiple three-dimensional models of loading items into an overall size model through a planning model; Performing size matching between the overall size model and the three-dimensional model of the loading space to generate a matching result; According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

[0058] According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition to generate a new overall size model until the overall size model matches the three-dimensional model of the loading space, specifically including: The weight information of the loaded items includes the weight limit and weight distribution requirements of the loading space; Determine the number of items that can be loaded according to the weight limit of the loading space, and determine the position adjustment plan of the three-dimensional model of the loaded items according to the weight distribution requirements of the loading space; The position of the three-dimensional model of the loaded items is adjusted according to the position adjustment plan of the three-dimensional model of the loaded items, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

[0059] According to the placement plan, loading instructions are sent to the staff and the freight station to carry out loading work, specifically including: The loading instructions include the location and order of the items to be stacked and the remaining amount of loading space; The staff loads the items according to their stacking location and order, and the freight station loads and replenishes new items according to the remaining loading space.

[0060] An intelligent planning system for loading items on a passenger aircraft provided by the present invention performs three-dimensional modeling by acquiring the size and weight information of the loaded items, matches the three-dimensional model with the three-dimensional model of the loading space of the belly compartment and the luggage compartment of the passenger aircraft, and generates a placement plan for the loaded items based on the weight information of the loaded items, which helps to rationally utilize the loading space inside the aircraft and improve the loading capacity of aircraft cargo.

[0061] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute an intelligent planning method for loading passenger aircraft items, the method comprising: obtaining a three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, establishing an intelligent allocation and loading stowage information system; inputting the size information of the loaded items into a preset three-dimensional model, and outputting a three-dimensional model of the loaded items through the three-dimensional model; taking the weight information of the loaded items as a constraint condition, matching the three-dimensional model of the loaded items with the three-dimensional model of the loading space through a pre-trained planning model, and generating a placement plan for the loaded items based on the intelligent allocation and loading stowage information system planning; sending a loading instruction to the staff and the freight station according to the placement plan to perform loading work.

[0062] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0063] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a passenger aircraft item loading intelligent planning method provided by the above-mentioned methods, the method including: obtaining a three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establishing an intelligent allocation and loading and stowage information system; inputting the size information of the loaded items into a preset three-dimensional model, and outputting a three-dimensional model of the loaded items through the three-dimensional model; using the weight information of the loaded items as a constraint condition, matching the three-dimensional model of the loaded items with the three-dimensional model of the loading space through a pre-trained planning model, and generating a placement plan for the loaded items based on the intelligent allocation and loading and stowage information system planning; sending loading instructions to staff and freight stations according to the placement plan to perform loading work.

[0064] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute a method for intelligent planning of passenger aircraft loading provided by the above methods, the method comprising: obtaining a three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establishing an intelligent allocation and loading and stowage information system; inputting the size information of the loaded items into a preset three-dimensional model, and outputting a three-dimensional model of the loaded items through the three-dimensional model; using the weight information of the loaded items as a constraint condition, matching the three-dimensional model of the loaded items with the three-dimensional model of the loading space through a pre-trained planning model, and generating a placement plan for the loaded items based on the planning of the intelligent allocation and loading and stowage information system; sending loading instructions to staff and freight stations according to the placement plan to perform loading work.

[0065] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0066] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent planning method for loading items on a passenger aircraft, characterized in that: include: Obtain the three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establish an intelligent allocation and loading information system; Inputting the size information of the loaded object into a preset three-dimensional model, and outputting a three-dimensional model of the loaded object through the three-dimensional model; Taking the weight information of the loaded items as a constraint condition, the three-dimensional model of the loaded items is matched with the three-dimensional model of the loading space through a pre-trained planning model, and a placement plan for the loaded items is generated based on the intelligent allocation and loading and stowage information system planning; According to the placement plan, loading instructions are sent to the staff and the freight station to carry out the loading work.

2. The intelligent planning method for passenger aircraft cargo loading according to claim 1, characterized in that: The obtaining of the three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items specifically includes: Obtain the three-dimensional model of the loading space of the belly compartment and luggage compartment of the passenger aircraft; At the item consignment point, the size information of the loaded items is collected through the camera, and the weight information of the loaded items is obtained through the weighing equipment.

3. The intelligent planning method for passenger aircraft cargo loading according to claim 1, characterized in that: The step of inputting the size information of the loaded object into a preset three-dimensional model and outputting a three-dimensional model of the loaded object through the three-dimensional model specifically includes: Input the collected size information of the loaded items into a preset three-dimensional model; The three-dimensional model is divided into blocks according to the size information of the loaded objects, and a three-dimensional model of the loaded objects is constructed by combining multiple blocks.

4. The intelligent planning method for passenger aircraft cargo loading according to claim 1, characterized in that: The method uses the weight information of the loaded items as a constraint condition, matches the loaded item three-dimensional model with the loading space three-dimensional model through a pre-trained planning model, and generates a placement plan for the loaded items based on intelligent allocation and loading and stowage information system planning, specifically including: Combining multiple three-dimensional models of loading items into an overall size model through a planning model; Performing size matching between the overall size model and the three-dimensional model of the loading space to generate a matching result; According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

5. The intelligent planning method for passenger aircraft cargo loading according to claim 4, characterized in that: According to the matching result, the position of the three-dimensional model of the loaded object is adjusted with the weight information of the loaded object as a constraint condition to generate a new overall size model until the overall size model matches the three-dimensional model of the loading space, specifically including: The weight information of the loaded items includes the weight limit and weight distribution requirements of the loading space; Determine the number of items that can be loaded according to the weight limit of the loading space, and determine the position adjustment plan of the three-dimensional model of the loaded items according to the weight distribution requirements of the loading space; The position of the three-dimensional model of the loaded items is adjusted according to the position adjustment plan of the three-dimensional model of the loaded items, and a new overall size model is generated until the overall size model matches the three-dimensional model of the loading space.

6. The method for intelligent planning of passenger aircraft cargo loading according to claim 1, characterized in that: The step of sending loading instructions to the staff and the freight station according to the placement plan to perform loading work specifically includes: The loading instructions include the location and order of the items to be stacked and the remaining amount of loading space; The staff loads the items according to their stacking location and order, and the freight station loads and replenishes new items according to the remaining loading space.

7. An intelligent planning system for loading cargo on passenger aircraft, characterized in that: The system comprises: Data acquisition module, used to obtain the three-dimensional model of the loading space in the passenger aircraft and the size and weight information of the loaded items, and establish an intelligent allocation and loading information system; A three-dimensional model building module, used for inputting the size information of the loaded object into a preset three-dimensional model, and outputting a three-dimensional model of the loaded object through the three-dimensional model; A solution generation module is used to match the three-dimensional model of the loaded items with the three-dimensional model of the loading space by a pre-trained planning model, taking the weight information of the loaded items as a constraint condition, and generating a placement solution for the loaded items based on the intelligent allocation and loading and stowage information system planning; The loading module is used to send loading instructions to the staff and the freight station according to the placement plan to carry out loading work.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for intelligent planning of passenger aircraft loading of items as claimed in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for intelligent planning of passenger aircraft loading of items as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for intelligent planning of passenger aircraft loading of items as claimed in any one of claims 1 to 6 is implemented.

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