Cabin cargo stowage method, system, equipment and medium

Abstract

The invention belongs to the technical field of cargo stowage, and provides a cabin cargo stowage method, system, equipment and medium, and the method comprises the steps: constructing a data server for storing flight related data, inputting a flight number into MR equipment before stowage and sending the flight number to the server, and the server sequentially providing a cabin three-dimensional grid and anchor point data, the MR device renders a shipping space model; and the MR equipment obtains stowage order data during stowage, scans a cargo bar code, matches shipping space anchor point data in combination with the stowage order data, and performs navigation guidance auxiliary stowage based on the data. According to the method, through data centralized management, visual presentation and precise navigation, the accuracy and efficiency of cargo stowage are improved, and the problems that a traditional mode is low in stowage efficiency and prone to making mistakes are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of cargo stowage, and in particular to a method, system, equipment and medium for stowage of cargo in a cabin. Background Art

[0002] With the rapid development of global trade and the continuous growth of air cargo volume, aircraft cargo hold loading has become a key link in the field of air logistics.

[0003] Currently, the process of loading luggage, cargo, etc. on flights mainly includes printing paper cargo hold loading lists. Ground staff use the loading lists to find corresponding shelves, bulk luggage and other items, and load the items according to the loading positions of the goods specified in the configuration list, as well as confirming the loading after the loading is completed.

[0004] The existing loading work mainly relies on paper loading sheets, standard work procedures, and the work experience of ground staff to ensure that flight loading is completed according to requirements and standards. The work efficiency is relatively low, and there are loading errors caused by human factors, which brings many challenges to the daily operations of airlines. Summary of the invention

[0005] To solve the above problems, the present disclosure provides a method, system, device and medium for cargo loading in the cabin, which adopts a method of rendering a three-dimensional scene of an airport and loading navigation instructions, thereby effectively improving the efficiency of cargo loading in the cabin.

[0006] The following is the technology of the present invention:

[0007] A method for loading cargo in a cabin, characterized by comprising:

[0008] Constructing a data server, wherein the data server stores the flight number and the corresponding three-dimensional grid data, cabin anchor point data, and cargo loading list data;

[0009] Before cargo is loaded, obtain the flight number and enter it into the mixed reality MR device;

[0010] Use the MR device to send the flight number to the data server;

[0011] The data server finds the 3D mesh data of the cabin of the aircraft that matches the flight number and the cabin anchor point data and sends them to the MR device; the MR device uses the 3D mesh data to render the scene, so that the cabin model of the corresponding aircraft is displayed in the MR device;

[0012] When the cargo begins to be loaded, the MR device submits a request to the data server to obtain the cargo loading list data and obtains the cargo loading list data;

[0013] After the barcode data of the goods is obtained by using the MR device, the barcode data of the goods and the cargo loading list data are used to match the cargo space anchor point data to obtain the cargo space anchor point data for placing the goods;

[0014] The MR device displays navigation guidance based on the cargo space anchor point data for placing the cargo, and the navigation guidance is used to assist in completing the loading of the cargo.

[0015] Further,

[0016] Use voice input to obtain the flight number and enter it into the mixed reality MR device.

[0017] Further,

[0018] The method of obtaining the flight number by voice input and inputting it into the mixed reality MR device includes:

[0019] Set keywords and preset actions for entering flight numbers;

[0020] The KeywordRecognizer class in the Unity engine is used to monitor voice input information and match the voice input information with the keywords used to enter the flight number. If the match is successful, the DictationSubSystem class is used to monitor the voice input flight number to trigger the preset action of querying the 3D mesh and anchor point data.

[0021] Further,

[0022] The MR device uses three-dimensional grid data to perform scene rendering; including:

[0023] Create a new game object and add Mesh Filter and Mesh Renderer components;

[0024] Deserialize the binary file of the mapping data of the three-dimensional mesh data to obtain the Mesh object data;

[0025] Apply the Mesh object data to the Mesh Filter component of the game object to achieve scene rendering.

[0026] Further,

[0027] The method of obtaining the barcode data of the goods by using the MR device includes:

[0028] After obtaining the camera device of the MR device through the WebCamTexture class of the Unity engine, open the camera to scan the barcode data of the goods and capture the key frames of the camera video stream;

[0029] GetPixels32 is used to obtain the key pixel color array information of the video stream, and the Decode method of the BarcodeReader class of the ZXing library is used to identify the key pixel color array information of the video stream to obtain the barcode data recognition result of the goods.

[0030] Further,

[0031] The method of matching the cargo space anchor point data with the cargo stowage list data to obtain the cargo space anchor point data for placing the cargo includes:

[0032] After obtaining the cargo barcode data, the serial value of the cargo barcode data in the cargo loading list data is cyclically matched to find the corresponding cargo information;

[0033] After finding the corresponding cargo information, get the content of the position field corresponding to the cargo;

[0034] The cabin ID is obtained from the content of the position field, and the cabin ID is used to match the anchor point data in the cabin anchor point data. After the match is successful, the anchor point data of the corresponding cabin is returned to obtain the anchor point coordinates.

[0035] Further,

[0036] The MR device displays navigation guidance based on the cargo space anchor point data; including:

[0037] Add a new child node Chevron to the cabin anchor and rename it to Indicator. Add DirectionalIndicator and SolverHandler components to the new child node Chevron.

[0038] DirectionalIndicator and SolverHandler components are used for configuration so that a sign Chevron pointing to the cabin coordinates appears in the rendered scene for displaying navigation guidance.

[0039] A cabin cargo stowage system, characterized by comprising:

[0040] A database construction module is used to construct a data server, in which the flight number and the corresponding three-dimensional grid data, cabin anchor point data, and cargo stowage list data are stored;

[0041] The rendering module is used to obtain the flight number and input it into the mixed reality MR device before cargo loading; send the flight number to the data server using the MR device; the data server finds the three-dimensional mesh data of the cabin of the aircraft matching the flight number and the cabin anchor point data based on the flight number and sends them to the MR device; the MR device uses the three-dimensional mesh data to perform scene rendering, so that the cabin model of the corresponding aircraft is displayed in the MR device;

[0042] The navigation module is used for, when the cargo starts to be loaded, the MR device submits a request for obtaining cargo loading list data to the data server to obtain the cargo loading list data; after obtaining the barcode data of the cargo by using the MR device, the barcode data of the cargo and the cargo loading list data are used to match the cabin anchor point data to obtain the cabin anchor point data for placing the cargo; the MR device displays navigation guidance based on the cabin anchor point data for placing the cargo, and the navigation guidance is used to assist in completing the loading of the cargo.

[0043] A cabin cargo stowage device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a cabin cargo stowage method.

[0044] A computer storage medium stores executable instructions, which, when executed by a processor, enable the processor to implement the method.

[0045] Compared with the prior art, the present invention has the following advantages:

[0046] The present invention constructs a data server to centrally store flight-related data, uses flight numbers for accurate association and rapid acquisition, avoids the tediousness of traditional manual data search, and improves data acquisition efficiency;

[0047] MR equipment uses the acquired 3D grid data to render the aircraft cabin model, which helps ground staff to clearly understand the cabin layout with intuitive visualization effects and reduce human judgment errors;

[0048] Scan the cargo barcode to obtain data and match it with the loading list data to obtain the cabin anchor point data, based on which navigation instructions are displayed, thereby accurately guiding the loading of cargo. This effectively solves the problems of low work efficiency and loading errors caused by human factors in the existing technology, and improves the accuracy and efficiency of cabin cargo loading.

[0049] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or be understood by implementing the present disclosure. The purpose and other advantages of the present disclosure can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0051] Figure 1 A schematic diagram of the method of the present invention is shown;

[0052] Figure 2 A schematic diagram of a technical implementation path of the present invention is shown;

[0053] Figure 3 A schematic diagram of the device of the present invention is shown;

[0054] Figure 4 The functional architecture diagram of the present invention is shown;

[0055] Figure 5 The technical architecture diagram of the present invention is shown. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0057] The present invention proposes a full-process, intelligent cargo hold loading solution based on wearable devices by means of mixed reality MR technology. Through this solution, the cargo hold loading list of the flight can be automatically obtained and presented in the field of vision of the ground staff through augmented reality. At the same time, by identifying and confirming the cargo to be loaded and its loading position, the staff is guided to accurately perform cargo loading operations and automatically perform loading confirmation work. Figure 1 A schematic diagram of the method according to the present invention is shown, Figure 2 The technical implementation path of the present invention includes the following specific implementation details:

[0058] Step 1: construct a data server, in which the flight number and the corresponding three-dimensional grid data, cabin anchor point data, and cargo loading list data are stored;

[0059] Step 2: Before loading the cargo, obtain the flight number and enter it into the mixed reality MR device; use the MR device to send the flight number to the data server;

[0060] The data server finds the 3D mesh data of the cabin of the aircraft that matches the flight number and the cabin anchor point data and sends them to the MR device. The MR device uses the 3D mesh data to render the scene, so that the cabin model of the corresponding aircraft is displayed in the MR device.

[0061] Specifically, the flight cabin three-dimensional grid data information in the storage medium is obtained through the flight number and date. The voice format is such as "enter the flight number";

[0062] Anchor point data format: [position:”1P”,location:{x:1.22,y:3.00,z:1.11}].

[0063] Step 3: When the cargo starts to be loaded, the MR device submits a request to obtain the cargo loading list data to the data server and obtains the cargo loading list data;

[0064] Specific:

[0065] Enter the specific flight number through voice and call the background service to query the flight loading list information.

[0066] Step 4: Scan the cargo through the MR device, identify the cargo and obtain the unique identification of the cargo, that is, the barcode data, and calculate the specific cabin information where the cargo needs to be loaded through the identification information.

[0067] Step 5: Obtain navigation guidance for loading process planning through the cabin 3D grid and anchor point information.

[0068] Specific:

[0069] According to the cargo loading space information, by querying the anchor point information of the corresponding space, the cargo loading path navigation planning is carried out to point to the specific coordinates of the space.

[0070] Step 6: Complete the loading according to the navigation path and store the completed data in the storage medium. According to the space and anchor point data information, push the cargo to the designated space in the cabin and align it for reinforcement. Complete the loading operation confirmation through voice interaction and store the assembly results in the storage medium.

[0071] The specific implementation technical details of the present invention are as follows:

[0072] This device is mainly developed using computer vision technology, MRTK toolkit, Unity 3D engine and Hololens device through C# language. The functional architecture diagram and technical architecture diagram of this case are as follows Figure 4 , Figure 5 As shown: The device of the present invention is as follows Figure 3 shown.

[0073] 1. According to the flight number, obtain the flight loading list, cabin 3D grid and anchor point data information.

[0074] 1) Voice input of flight number

[0075] The client application of Mr device uses voice control of non-UI interface, and uses custom scripts to realize voice interactive control. According to the functional requirements, design corresponding keywords and preset actions, bind keywords and preset actions through Dictionary class through the KeywordRecognizer class that comes with UnityEngine, register <keyword> to initialize the KeywordRecognizer class instance, and register voice command events for subsequent processing. When the user speaks a keyword, the KeywordRecognizer class monitors the voice input and tries to match the monitored phrase with the registered keyword list. If the match is successful, the preset action will be called, thereby achieving the purpose of voice control.

[0076] The user interacts with the client through voice and issues a voice command "Enter the flight number". The KeywordRecognizer class listens to the voice input and matches it with the keyword list. After a successful match, it responds to the user "Please speak". The user needs to speak the specific flight number. The DictationSubSystem class listens to the dictation content, which triggers the preset action of querying the 3D grid and anchor data. If the voice input fails to match the keyword, the user will be prompted to "Please enter the correct command."

[0077] 2) Acquisition of 3D mesh and anchor point data

[0078] After the user inputs the flight number by voice, the client encapsulates an Http request to the backend API (the interface provided by the data server to the client application), and the request data format is: {fltno:”CA001X”, fltdate:”2024-06-23”}. After receiving the request parameters, the data server queries the aircraft registration number information according to the flight number information and date requested by the front end, and then obtains the cabin three-dimensional grid data file on the disk according to the aircraft registration number; at the same time, the aircraft registration number is used to query the cabin anchor data, return it to the client program, and cache it. Anchor data format: [position:”1P”, location:{x:1.22,y:3.00,z:1.11}]

[0079] 3) Scene Rendering

[0080] The MR client will receive the 3D mesh data for scene rendering. Create a new game object, then add Mesh Filter and Mesh Renderer components to display the mesh in the scene. Deserialize the binary file of the mapping data stored locally into Mesh object data, and then apply the Mesh data to the Mesh Filter component of the game object, so that the mesh data can be rendered into the scene. After rendering is completed, the system will voice prompt "Scene rendering completed".

[0081] 2. Identify the cargo and obtain the corresponding cargo space location information according to the loading list

[0082] 1) Obtaining electronic loading list

[0083] The user issues a voice command "start loading", and the client prompts "load loading list". The Keyword RecognitionSubsystem matches the monitored voice input with the keyword list, triggers the preset action of electronic loading list query, and the electronic loading list query API passes the received {fltno:"CA001X", fltdate:"2024-06-23"} to the external loading system (part of the data server). The external loading system returns the corresponding electronic loading list, which is processed by the electronic loading list query API and returns the loading list information to the MR client. The client caches the electronic loading list locally. Loading list data format: {"id":16586456,"status":"Completed","positionList":[{"dataList":[{"type":"LD3","serial":"AKE00003MU"},{"type":"LD3","serial":"AKE00005MU"}],"position":"11H"},{"dataList":[{"type":"LD 3","serial":"AKE01234CA"}],"position":"1P"}]}

[0084] 2) Cargo identification

[0085] After the loading list is loaded, a prompt "Please scan the goods" is displayed. The user uses the client program to scan the goods, obtains the camera device through the WebCamTexture class of the Unity engine, opens the camera to run recognition, captures the key frames of the MR device camera video stream, obtains the pixel color array information of the camera screen through GetPixels32, and uses the Decode method of the BarcodeReader class of the ZXing library for recognition. The recognition result data structure is: {Text:"AKE00005MU", ResultPoints:[{x:1.22,y:34}]}, where the text field is the recognized text information, that is, the value of the goods barcode data serial.

[0086] 3) Acquisition of space anchor information

[0087] After obtaining the cargo barcode content, use this value to cyclically match the serial value of the electronic stowage order. If the match is successful, the position field content corresponding to the cargo is returned. After obtaining the cabin ID, use this cabin ID to match the anchor point data. If the match is successful, the anchor point data of the corresponding cabin is returned. At this point, the anchor point coordinates have been obtained.

[0088] 3. Obtain navigation guidance for loading process planning through cabin 3D grid and anchor point information.

[0089] 1) Navigation process.

[0090] After obtaining the anchor point information of the corresponding space, the client prompts "Scanning is successful, navigation is available", the user issues a voice command "Start navigation", the voice prompt "Navigation is in progress", and then a blue arrow indicator is displayed on the screen, pointing to the navigation destination space coordinates. The user pushes the goods to the designated space according to the direction of the target indicator. After completing the relevant actions, the voice command "Complete navigation" is issued, and then the name of the goods on the screen is displayed in green.

[0091] 2) Navigation function implementation.

[0092] The keywords such as "start navigation" and "complete navigation" are mapped to the corresponding functions through the dictionary and registered in the KeywordRecognizer class object. When the word recognizer class monitors the input voice keywords, the corresponding function code will be triggered to execute.

[0093] After obtaining the coordinate data of the cabin anchor point, add a new child node Chevron to the cabin anchor point through code and rename it to Indicator, then add "DirectionalIndicator" and "SolverHandler" components to this Indicator, and make appropriate configurations according to the actual situation. At this time, a Chevron will appear in the scene, pointing to the coordinates of the cabin. The user navigates according to the Indicator, and when the system receives the "complete navigation" keyword, the system displays the cargo name in green, indicating that the assembly is completed.

[0094] 4. Complete the loading according to the navigation path and store the data on the storage medium.

[0095] 1) Cargo assembly.

[0096] After starting navigation, the system voice prompts "Please push the goods to the cabin according to the navigation", and a blue direction indicator will appear on the screen. The user pushes the goods to the cabin coordinates according to the indicator and assembles and reinforces them. After the assembly is completed, the user issues a voice command "Complete navigation", and the corresponding goods name on the screen is displayed in green, which means that the goods have been assembled. The user repeats the above operation process and continues to assemble other goods until all goods are assembled and all goods names on the screen are displayed in green.

[0097] 2) Data persistence.

[0098] 5. All goods are assembled. At this time, the names of the goods are all displayed in green, and the status of the electronic loading list is pending confirmation. The user uses the voice command "end assembly". The system encapsulates an Http request to the backend to confirm the loading API, with parameters: {id:16586456, status:"confirmed"}; the backend will encapsulate the received parameters into an http request to the third-party loading system, complete the loading list confirmation operation, and persist it in the database. At the same time, it pushes the electronic loading list message to ActiveMQ for use by other services.

[0099] The present invention combines barcode recognition technology, MR technology and Unity engine technology to realize a device based on the equipment confirmation function of the Hololens wearable device. The patent of the present invention has the following advantages: (1) Improving the user experience of the cargo hold loading process. The existing cargo hold loading process is mainly assembled according to the loading list information. The present device is completed through MR equipment and voice control throughout the process, which greatly improves the user experience. (2) Improving the convenience of system operation. Full voice command control is a feature of the present device. There is no need for manual operation of the terminal equipment, which greatly simplifies the operation difficulty. The MR terminal can be operated only according to voice commands. (3) Avoiding errors in manual proofreading. The present device uses equipment to identify goods throughout the process, does not require manual proofreading, and almost avoids all shortcomings of manual operation, and will not have human weaknesses and errors. (4) Wide application field. The present device is suitable for most business scenarios of assembly confirmation, not limited to business fields.

[0100] The implementation of the present invention is not limited to the programming language and tools used, and any language can be selected. The MR device is not limited to Hololens, and other MR devices can be selected; the virtual engine is not limited to Unity, and other engines such as Unreal can be selected for implementation; in terms of barcode recognition, other recognition technologies such as Scan Kit can be selected, not limited to ZXing; cargo recognition can be implemented using target detection, not limited to barcode recognition technology. The content of the present invention is to illustrate the principle and process of implementing the device, and the choice of implementation method is only one of them.

[0101] Based on the method of the present invention, the embodiment of the present disclosure also provides a system corresponding to the above method, which includes:

[0102] A database construction module is used to construct a data server, in which the flight number and the corresponding three-dimensional grid data, cabin anchor point data, and cargo stowage list data are stored;

[0103] The rendering module is used to obtain the flight number and input it into the mixed reality MR device before cargo loading; send the flight number to the data server using the MR device; the data server finds the three-dimensional mesh data of the cabin of the aircraft matching the flight number and the cabin anchor point data based on the flight number and sends them to the MR device; the MR device uses the three-dimensional mesh data to perform scene rendering, so that the cabin model of the corresponding aircraft is displayed in the MR device;

[0104] The navigation module is used for, when the cargo starts to be loaded, the MR device submits a request for obtaining cargo loading list data to the data server to obtain the cargo loading list data; after obtaining the barcode data of the cargo by using the MR device, the barcode data of the cargo and the cargo loading list data are used to match the cabin anchor point data to obtain the cabin anchor point data for placing the cargo; the MR device displays navigation guidance based on the cabin anchor point data for placing the cargo, and the navigation guidance is used to assist in completing the loading of the cargo.

[0105] Based on the same inventive concept as the above disclosed content, an embodiment of the present disclosure also provides a device corresponding to the above method, which includes at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the above method.

[0106] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean the connection between lines. An indirect connection method can be applied to the embodiments of the present disclosure as long as the purpose of the present disclosure is achieved.

[0107] Based on the same inventive concept, the present disclosure also provides a computer storage medium on which executable instructions are stored, and the instructions are executed by a processor to execute the above method.

[0108] Although the present disclosure 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; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A method for loading cargo in a cabin, characterized in that: include: Constructing a data server, wherein the data server stores the flight number and the corresponding three-dimensional grid data, cabin anchor point data, and cargo loading list data; Before cargo loading, obtain the flight number and enter it into the mixed reality MR device; use the MR device to send the flight number to the data server; The data server finds the 3D mesh data of the cabin of the aircraft that matches the flight number and the cabin anchor point data and sends them to the MR device; the MR device uses the 3D mesh data to render the scene, so that the cabin model of the corresponding aircraft is displayed in the MR device; When the cargo begins to be loaded, the MR device submits a request to the data server to obtain the cargo loading list data, and obtains the cargo loading list data; after the MR device obtains the barcode data of the cargo, the cargo barcode data and the cargo loading list data are used to match the cabin anchor point data, and obtain the cabin anchor point data for placing the cargo; The MR device displays navigation guidance based on the cargo space anchor point data for placing the cargo, and the navigation guidance is used to assist in completing the loading of the cargo.

2. A method for loading cargo in a cabin according to claim 1, characterized in that: Use voice input to obtain the flight number and enter it into the mixed reality MR device.

3. A method for loading cargo in a cabin according to claim 2, characterized in that: The method of obtaining the flight number by voice input and inputting it into the mixed reality MR device includes: Set keywords and preset actions for entering flight numbers; The KeywordRecognizer class in the Unity engine is used to monitor voice input information and match the voice input information with the keywords used to enter the flight number. If the match is successful, the DictationSubSystem class is used to monitor the voice input flight number to trigger the preset action of querying the 3D mesh and anchor point data.

4. A method for loading cargo in a cabin according to claim 1, characterized in that: The MR device uses three-dimensional grid data to perform scene rendering; including: Create a new game object and add Mesh Filter and Mesh Renderer components; Deserialize the binary file of the mapping data of the three-dimensional mesh data to obtain the Mesh object data; Apply the Mesh object data to the Mesh Filter component of the game object to achieve scene rendering.

5. A method for loading cargo in an aircraft cabin according to claim 1, characterized in that: The method of obtaining the barcode data of the goods by using the MR device includes: After obtaining the camera device of the MR device through the WebCamTexture class of the Unity engine, open the camera to scan the barcode data of the goods and capture the key frames of the camera video stream; GetPixels32 is used to obtain the key pixel color array information of the video stream, and the Decode method of the BarcodeReader class of the ZXing library is used to identify the key pixel color array information of the video stream to obtain the barcode data recognition result of the goods.

6. A method for loading cargo in an aircraft cabin according to claim 1, characterized in that: The method of matching the cargo space anchor point data with the cargo stowage list data to obtain the cargo space anchor point data for placing the cargo includes: After obtaining the cargo barcode data, the serial value of the cargo barcode data in the cargo loading list data is cyclically matched to find the corresponding cargo information; After finding the corresponding cargo information, get the content of the position field corresponding to the cargo; The cabin ID is obtained from the content of the position field, and the cabin ID is used to match the anchor point data in the cabin anchor point data. After the match is successful, the anchor point data of the corresponding cabin is returned to obtain the anchor point coordinates.

7. A method for loading cargo in an aircraft cabin according to claim 1, characterized in that: The MR device displays navigation guidance based on the cargo space anchor point data; including: Add a new child node Chevron to the cabin anchor and rename it to Indicator. Add DirectionalIndicator and SolverHandler components to the new child node Chevron. DirectionalIndicator and SolverHandler components are used for configuration so that a sign Chevron pointing to the cabin coordinates appears in the rendered scene for displaying navigation guidance.

8. A cabin cargo stowage system, characterized in that: include: A database construction module is used to construct a data server, in which the flight number and the corresponding three-dimensional grid data, cabin anchor point data, and cargo stowage list data are stored; The rendering module is used to obtain the flight number and input it into the mixed reality MR device before cargo loading; send the flight number to the data server using the MR device; the data server finds the three-dimensional mesh data of the cabin of the aircraft matching the flight number and the cabin anchor point data based on the flight number and sends them to the MR device; the MR device uses the three-dimensional mesh data to perform scene rendering, so that the cabin model of the corresponding aircraft is displayed in the MR device; The navigation module is used for, when the cargo starts to be loaded, the MR device submits a request for obtaining cargo loading list data to the data server to obtain the cargo loading list data; after obtaining the barcode data of the cargo by using the MR device, the barcode data of the cargo and the cargo loading list data are used to match the cabin anchor point data to obtain the cabin anchor point data for placing the cargo; the MR device displays navigation guidance based on the cabin anchor point data for placing the cargo, and the navigation guidance is used to assist in completing the loading of the cargo.

9. A cabin cargo loading device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor so that the at least one processor can execute the cabin cargo loading method described in any one of claims 1 to 7.

10. A computer storage medium having executable instructions stored thereon, wherein when the instructions are executed by a processor, the processor is enabled to implement the method according to any one of claims 1 to 7.

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