Large-scale transportation and delivery unmanned aerial vehicle cargo hold stowage balancing method, equipment and medium

Abstract

The invention provides a cargo hold stowage balancing method for a large-scale transportation and delivery unmanned aerial vehicle, which comprises the following steps: receiving a transportation and delivery task instruction, and determining the total weight of cargoes and the quantity of packaging units; the total cargo weight and the number of the packaging units are both smaller than the limit value of the cargo hold of the unmanned aerial vehicle; traversing to generate a plurality of stowage schemes conforming to the load constraint, and screening to generate a stowage scheme set for loading the gravity center envelope; based on a predetermined optimization factor, establishing an efficiency evaluation equation, and determining N groups of candidate stowage schemes from the stowage scheme set; based on a group of fixed air-drop time sequences, determining a stowage scheme which conforms to an air-drop gravity center envelope and has a minimum gravity center dynamic change range from N groups of candidate stowage schemes; and generating stowage information of each packaging unit based on the determined stowage scheme. According to the method, the cargo hold balance control operation method is greatly simplified, the operation and maintenance cost of a user is remarkably reduced, the situation that balance weights are additionally increased due to cargo unbalance loading can be avoided, and the optimal stowage balance scheme can be efficiently and reasonably output.

Description

Technical Field

[0001] This invention relates to the field of large-scale delivery drones, and particularly to a method, equipment, and medium for loading and balancing the cargo hold of a large-scale delivery drone. Background Technology

[0002] With the rapid development of the low-altitude economy and the unmanned and intelligent upgrading of the logistics industry, large-scale delivery drones are increasingly widely used in fields such as air logistics, emergency relief material delivery, and military logistics support. The core mission of these drones is to efficiently and safely deliver cargo. The balance of the cargo hold directly affects flight stability, airdrop safety, structural safety, and mission reliability. If the cargo load within the hold is unbalanced, it may lead to a shift in the drone's center of gravity and abnormal aerodynamic characteristics, potentially causing loss of flight control or even a crash. Therefore, research on cargo hold balance control technology has significant and clear engineering application value.

[0003] For cargo hold balance control of large delivery drones, there are currently two methods: Mechanical leveling technology based on fixed counterweights: Traditional drones often use mechanical counterweights or pre-placed weights to adjust the center of gravity of the cargo hold. For example, an adjustable counterweight is placed at the nose of the drone to counteract the center of gravity shift caused by uneven cargo loading. This method is simple in structure and low in cost, but it has significant limitations: First, the counterweight can only handle typical loading scenarios preset in the design phase and cannot adapt to dynamic changes in cargo type, quantity, or loading position; second, mechanical leveling requires manual intervention, has a slow response speed, and cannot meet the needs of large drones for rapid loading and unloading; third, the additional counterweight increases the drone's weight and reduces the effective payload ratio.

[0004] Manual balancing based on weight balance manuals involves trained operators consulting the weight balance manual provided by the drone manufacturer, using an Excel spreadsheet to arrange and combine various load configurations, and manually selecting one that satisfies the center of gravity envelope. This method requires the user to employ a load balance designer with relevant business knowledge and suffers from drawbacks such as low efficiency, time-consuming and labor-intensive processes, and the inability to obtain optimal values. Summary of the Invention

[0005] This application provides a method, equipment, and medium for balancing the cargo hold of a large-scale delivery drone to solve the problems in the background art.

[0006] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0007] According to a first aspect of the embodiments of this application, a method for loading and balancing the cargo hold of a large-scale delivery drone is provided, comprising: Receive delivery mission instructions and determine the total weight of the cargo and the number of container units; both the total weight of the cargo and the number of container units are less than the limit value of the UAV cargo compartment; Based on the total weight of the cargo and the number of container units, several loading schemes that meet the load constraints are generated through a traversal process, and a set of loading schemes that meet the load center of gravity envelope is generated by filtering. Based on predetermined optimization factors, an efficiency evaluation equation is established to determine N candidate loading schemes from the set of loading schemes; Based on a set of fixed airdrop timing, determine the loading scheme that conforms to the airdrop center of gravity envelope and has the smallest dynamic change range of the center of gravity from N candidate loading schemes. Based on the determined loading scheme, loading information for each container unit is generated, which includes the weight of the container unit and the storage slot.

[0008] In one embodiment of this application, the step of generating several loading schemes that meet the load constraints based on the total weight of the cargo and the number of container units specifically includes: The system retrieves all possible scenarios for allocating the total weight of the cargo to NUM container units according to the preset minimum weight division, and then filling the NUM container units into the slots of the drone's cargo compartment. Each scenario represents a loading scheme. NUM is a fixed number of container units, and NUM is less than or equal to the number of slots in the drone's cargo compartment.

[0009] In one embodiment of this application, the step of filtering and generating a set of loading schemes for the center of gravity envelope specifically includes: Calculate the overall center of gravity of the aircraft for each loading scheme. If the center of gravity conforms to the preset loading center of gravity envelope, output it to the set of matching loading schemes. If it does not conform, calculate the center of gravity of the next loading scheme.

[0010] In one embodiment of this application, the formula for calculating the overall center of gravity of the aircraft includes:

[0011] in, As the center of gravity of the entire aircraft, The weight of the i-th to NUMth container unit, plus the weight of the empty engine and fuel; This includes the center of gravity of the i-th to NUMth container units, as well as the center of gravity of the empty engine and fuel.

[0012] In one embodiment of this application, the step of establishing an efficiency evaluation equation based on a predetermined optimization factor to determine N candidate loading schemes from the loading scheme set specifically includes: Based on the selection of the economic cruise center of gravity and the pitch inertia of the entire aircraft, a comprehensive performance evaluation equation is established. Calculate the overall center of gravity and pitch inertia of the aircraft for each loading scheme in the set of loading schemes, input them into the comprehensive performance evaluation equation, and obtain the value of each scheme; The value of all loading schemes is sorted in descending order, and the top N loading schemes are selected as candidate loading schemes.

[0013] In one embodiment of this application, the comprehensive performance evaluation equation is:

[0014]

[0015]

[0016] in, For the value of the loading scheme, As a factor characterizing the merits of the centroid location, A factor characterizing the quality of the overall inertia; and These are the weights of the factors characterizing the quality of the center of gravity position and the factors characterizing the quality of the overall inertia, respectively. , These are the rear limit and the front limit of the center of gravity, respectively. As the center of gravity of the entire aircraft, As the focus of economic cruise, For the total inertia of the machine, Let be the inertia of the i-th container unit.

[0017] In one embodiment of this application, the step of determining the loading scheme that conforms to the airdrop center of gravity envelope and has the smallest dynamic change range of the center of gravity from N candidate loading schemes based on a set of fixed airdrop timings specifically includes: Each candidate loading scheme is stored in a linked list. The information of a single linked list node includes: slot number, container weight, container center of gravity, cargo unlocking time, and a pointer to the next node. Based on a fixed airdrop sequence, the linked list corresponding to each set of candidate loading schemes and the center of gravity of each node are updated through traversal, and the range of change of airdrop center of gravity during the traversal process is determined. The candidate loading schemes are sorted by the range of change of the airdrop center of gravity, and the candidate loading scheme with the smallest range of change of the airdrop center of gravity is selected as the optimal loading scheme.

[0018] In one embodiment of this application, the step of traversing and updating the linked list corresponding to each set of candidate loading schemes and the centroid of each node based on a fixed airdrop sequence, and determining the range of changes in the airdrop centroid during the traversal process, specifically includes: S1. Initialize the data required for calculation, including time T=0, initialize the container unit information in the linked list LoadList to the given input information, and calculate the acceleration a according to the fuselage angle of attack and cargo platform friction coefficient at the given airdrop time; S2. Traverse the linked list and update the linked list and the centroid STA of each node. This indicates that the cargo in slot i is unlocked at time T, and its center of gravity STA is updated.

[0019] S3. Determine whether the updated center of gravity STA is greater than the center of gravity STA at the exit position. leave If the value is greater than 0, then the node is removed from the linked list. S4. Traverse the updated linked list, calculate the center of gravity of the whole machine, and determine whether the center of gravity of the whole machine exceeds the limit. If it exceeds the limit, exit the loop directly and output a warning that the center of gravity exceeds the limit. If it does not exceed the limit, record the time T and the center of gravity of the whole machine. S5. Check if the linked list is empty. If not empty, update time T += 0.01 and return to S2. If empty, exit the loop and output time T and the center of gravity of the entire machine. Relationship diagram and range of airdrop center of gravity changes :

[0020] in, and These represent the maximum and minimum values ​​of the center of gravity change during the airdrop process.

[0021] According to a second aspect of this application, an electronic device is provided, comprising: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores instructions executable by the at least one processor, which executes the instructions stored in the memory to perform the method described in any of the first aspects.

[0022] According to a third aspect of this application, a computer-readable storage medium is provided for storing instructions that, when executed, cause the method described in the first aspect to be implemented.

[0023] Compared with existing technologies, the beneficial effects of adopting the above technical solution are as follows: 1. This method innovatively adopts cargo hold balance simulation to evaluate and select the best design scheme, which significantly reduces the user's operation and maintenance costs compared with manual balancing technology based on weight balance manual; 2. This method uses an automatic optimization screening approach, which avoids the disadvantages of low loading efficiency, time-consuming and labor-intensive processes, and failure to obtain the optimal value, thus significantly shortening the loading cycle. 3. This method introduces a cargo hold balance calculation method at the beginning of loading and unloading, which avoids the disadvantages of the traditional counterweight mechanical load balancing method, such as cargo imbalance and extra weight, and ensures the effective cargo weight. 4. This method not only ensures the balance of cargo transportation and loading, but also innovatively introduces a method for selecting the optimal loading scheme in the dynamic process of airdrop, which effectively ensures that the center of gravity shift of the UAV and the dynamic attitude change of airdrop are controllable. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0025] Figure 1 This is a flowchart of the large-scale delivery drone cargo hold loading and balancing method proposed in the embodiments of this application.

[0026] Figure 2 This is a schematic diagram of the cargo hold loading and balancing system of the large-scale delivery UAV cargo hold loading and balancing method based on this application.

[0027] Figure 3 This is a flowchart illustrating the selection process for the load configuration scheme set in this application.

[0028] Figure 4 This is a schematic diagram of the loading center of gravity envelope of an embodiment of this application.

[0029] Figure 5 This is a flowchart illustrating the candidate loading scheme selection process in an embodiment of this application.

[0030] Figure 6 This is a flowchart illustrating the airdrop center of gravity loading scheme selection strategy in an embodiment of this application.

[0031] Figure 7 This is a schematic diagram illustrating the range of changes in the center of gravity of an airdrop according to an embodiment of this application.

[0032] Figure 8 This is a cargo loading identifier for a container unit in this application embodiment.

[0033] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0034] The embodiments of this application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar modules or modules having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application. Rather, the embodiments of this application include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0035] To address the shortcomings of existing technologies, this application proposes a cargo hold loading and balancing method for large-scale delivery drones. Based on constraints related to cargo load weight, the loading and transport center of gravity envelope, and the airdrop center of gravity envelope, the method minimizes the dynamic variation range of the economic cruise center of gravity, overall aircraft inertia, and airdrop center of gravity. A loading software calculation method is used to quantitatively evaluate and select the optimal loading scheme, achieving the best cargo hold loading scheme while satisfying the aforementioned constraints. This method significantly simplifies cargo hold balancing control operations, substantially reduces user maintenance costs, avoids the need for additional counterweights due to cargo imbalance, and efficiently and rationally outputs the optimal loading and balancing scheme. Please refer to [reference needed]. Figure 1 The specific steps are as follows: S101. Receive the delivery task instruction and determine the total weight of the cargo and the number of container units; the total weight of the cargo and the number of container units are both less than the limit value of the UAV cargo compartment.

[0036] In this embodiment, the overall center of gravity balance calculation of the delivery drone mainly consists of three parts: empty aircraft, fuel, and cargo. Before performing the load balance calculation, information initialization is required. In one embodiment, an implementation method for the cargo hold load balance method of the large delivery drone proposed in this application is given, which is implemented through cargo hold load balance system software, such as... Figure 2 As shown, in the system information input window, you need to enter the empty aircraft weight, empty aircraft center of gravity, takeoff fuel weight, fuel center of gravity, and total cargo weight W in sequence. load The optimal loading scheme can be output by calculating the number of container units (NUM) using software. Generally, the center of gravity of the empty aircraft weight is obtained by maintenance personnel through on-site weighing, the center of gravity of the takeoff fuel weight is calculated based on the required flight distance for the delivery mission, and the total weight of the cargo and the number of container units are determined by the specific delivery mission.

[0037] It should be noted that, according to the definition of drone cargo compartments, there are maximum limits on the weight and quantity of cargo in the container unit. These limits can be built into the program, and the total weight of the received cargo (Wload) and the number of container units (NUM) must be less than the limits. Figure 2 The cargo hold of the delivery drone shown includes four slots, limiting the maximum number of container units (NUM) to four and the maximum payload to 1500 kg. This embodiment will use this delivery drone cargo hold as an example for subsequent explanations. In practical applications, the configuration can be tailored to specific needs.

[0038] S102. Based on the total weight of the cargo and the number of container units, generate several loading schemes that meet the load constraints, and filter to generate a set of loading schemes that meet the load center of gravity envelope.

[0039] After determining the total cargo weight and the number of container units, all possible loading schemes that meet the load constraints can be obtained by iterating through the data. Specifically, all possible scenarios are obtained where the total cargo weight is allocated to NUM container units according to a preset minimum weight division, and then NUM container units are filled into the slots of the drone's cargo compartment. Each scenario represents a loading scheme; where NUM is the determined number of container units, and NUM is less than or equal to the number of slots in the drone's cargo compartment.

[0040] The following explanation uses a maximum of 4 slots as an example: (1) NUM=1 Loading schemes include indivual.

[0041] (2) NUM=2 Assuming there are two containers, A and B, the initial state is that container A is filled to the maximum weight W of a single loading dock. limit The weight of container unit B can be determined as W. load -W limit Assuming the smallest divisible unit of goods weighs w (kg), the iterative approach is to continuously move goods of weight w from A to B until the total weight of A is reduced to w. The following steps conclude the process. Then, place these two containers into the four slots, totaling [number missing]. One option.

[0042] (3) NUM=3 When MUM=3, after determining the weight of a container unit, the problem degenerates into the case of NUM=2. Analogous to NUM=2, when the weight of container unit A is from W... limit Reduced to 1 / 3 W load The procedure then repeats. When the weight of container unit A is determined to be W... A Then, the problem degenerates to the case where NUM=2, and these 3 container units are then placed on 4 cargo bays, totaling... One option.

[0043] (4) NUM=4 Analogous to NUM=3, after determining the weights of the two container units, the problem degenerates into the case of NUM=2. When the weights of container unit A and container unit B change from W... limit Reduced to 1 / 4 W load The following procedure is repeated. When the weights of containers A and B are respectively determined to be W...A和 W B Then, the problem degenerates to the case where NUM=2, and these 4 container units are then placed on 4 cargo bays, totaling... One option.

[0044] After determining all loading schemes corresponding to NUM container units, it is necessary to further filter out the set of loading schemes based on the loading center of gravity envelope. Specifically, such as... Figure 3 As shown, the overall center of gravity of the aircraft is calculated for each loading scheme. If the center of gravity conforms to the preset loading center of gravity envelope, it is output to the set of suitable loading schemes; otherwise, the center of gravity of the next loading scheme is calculated. In this embodiment, the loading center of gravity envelope used is as follows: Figure 4 As shown.

[0045] Furthermore, this embodiment also provides a specific method for calculating the overall center of gravity of the aircraft:

[0046] in, As the center of gravity of the entire aircraft, The weight of the i-th to NUMth container unit, plus the weight of the empty engine and fuel; This includes the center of gravity of the i-th to NUMth container units, as well as the center of gravity of the empty engine and fuel.

[0047] S103. Based on the predetermined optimization factors, establish an efficiency evaluation equation to determine N candidate loading schemes from the set of loading schemes.

[0048] Considering the impact of the center of gravity position on elevator trim drag, which in turn affects the mission radius of the delivery UAV, and the influence of the overall pitch inertia after loading on structural load and the ease of dynamic pitch control during airdrop, this embodiment considers the economic cruise center of gravity and overall pitch inertia as optimization factors to establish a comprehensive performance evaluation equation. The closer to the economic cruise center of gravity and the smaller the overall pitch inertia, the higher the value. This allows for the ranking and selection of the top N candidate loading schemes, such as... Figure 5 As shown.

[0049] In this embodiment, the performance evaluation equation is established as follows:

[0050]

[0051]

[0052] in, For the value of the loading scheme, The smaller the factor representing the quality of the center of gravity position, the better; The smaller the factor that characterizes the overall inertia of the machine, the better; and These are the weights of the factors characterizing the quality of the center of gravity position and the factors characterizing the quality of the overall inertia, respectively. , These are the rear limit and the front limit of the center of gravity, respectively. As the center of gravity of the entire aircraft, As the focus of economic cruise, For the total inertia of the machine, Let be the inertia of the i-th unit. Total machine inertia. The calculation process is as follows: The inertia of an empty aircraft is generally a given value. The inertia of fuel itself needs to be obtained by interpolation from the fuel center of gravity inertia database built into the program. The inertia of a container unit is considered as a cuboid (the weight of a single container unit is m, the heading length is a, the lateral width is b, and the height is h). The length a and lateral width b of the container unit are fixed dimensions, and the height h can be calculated based on its own weight and the statistical average density of the cargo. Therefore, the inertia of the container unit itself is:

[0053] Based on the individual inertia of the airframe, fuel, and container units, the inertia of the entire aircraft needs to be calculated using the axis-shifting formula:

[0054] in, It includes not only the inertia of the i-th to NUMth cargoes, but also the inertia of using empty aircraft and fuel.

[0055] S104. Based on a set of fixed airdrop timings, determine the loading scheme that conforms to the airdrop center of gravity envelope and has the smallest dynamic change range of the center of gravity from N candidate loading schemes.

[0056] After determining N candidate loading schemes, the feasibility of the airdrop mission needs to be verified under the given cargo hold loading scheme and airdrop sequence. This involves iterative verification of the center of gravity conformity throughout the entire airdrop mission timeframe, using a time step approach. Specifically, this includes: First, each candidate loading scheme is stored in a linked list. The information of a single linked list node includes: slot number i, container unit weight W. i Center of gravity of container unit, unlocking time of container unit T unlock A pointer to the next node; Then, based on a fixed airdrop sequence, the linked list corresponding to each set of candidate loading schemes and the center of gravity of each node are updated through traversal, and the range of change of airdrop center of gravity during the traversal process is determined. Finally, the range of change of the airdrop center of gravity for each group of candidate loading schemes is sorted, and the candidate loading scheme with the smallest range of change of the airdrop center of gravity is selected as the optimal loading scheme.

[0057] Please refer to Figure 6 , Figure 7 This embodiment provides a detailed process for determining the range of changes in the airdrop center of gravity during the traversal process: S1041. Initialize the data required for calculation, including time T=0, initialize the container unit information in the linked list LoadList to the given input information, and calculate the acceleration according to the fuselage angle of attack and cargo platform friction coefficient at the given airdrop time; S1042, Traverse the linked list and update the linked list and the centroid STA of each node: If This indicates that the cargo in slot i is unlocked at time T, and its center of gravity STA is updated.

[0058] S1043. Determine whether the updated center of gravity STA is greater than the center of gravity STA at the exit point. leave If the value is greater than 0, then the node is removed from the linked list. S1044. Traverse the updated linked list, calculate the center of gravity of the whole machine, and determine whether the center of gravity of the whole machine exceeds the limit. If it exceeds the limit, exit the loop directly and output a warning that the center of gravity exceeds the limit. If it does not exceed the limit, record the time T and the center of gravity of the whole machine. S1045. Check if the linked list is empty. If not empty, update time T += 0.01 and return to S1042. If empty, exit the loop and output time T and the center of gravity of the entire machine. Relationship diagram and range of airdrop center of gravity changes ;

[0059] in, and These represent the maximum and minimum values ​​of the center of gravity change during the airdrop process.

[0060] S105. Generate loading information for each container unit based on the determined loading scheme. The loading information includes the weight of the container unit and the storage slot.

[0061] Finally, the output loading scheme can be printed out, such as... Figure 8 As shown, after each container unit is packed according to the loading plan, a label can be affixed to indicate the weight of the container unit and the planned storage slot. The maintenance personnel can then complete the loading and unloading process based on the label.

[0062] Based on the same technical concept, this application also provides an electronic device that can implement the cargo hold loading and balancing method for large-scale delivery drones provided in the above embodiments of the present invention. In one embodiment, the electronic device can be a server, a terminal device, or other electronic equipment. Figure 9 As shown, the electronic device may include: At least one processor and a memory connected to the at least one processor. In this embodiment of the invention, the specific connection medium between the processor and the memory is not limited. Figure 9 The example used is the connection between the processor and memory via a bus. The bus... Figure 9 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. Buses can be divided into address buses, data buses, control buses, etc., but for ease of representation, [the specific bus type is not shown here]. Figure 9 The processor is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, a processor can also be called a controller; there are no restrictions on the name.

[0063] In this embodiment of the invention, the memory stores instructions executable by at least one processor. By executing the instructions stored in the memory, the at least one processor can perform the cargo hold loading and balancing method for a large-scale delivery drone discussed above. The processor can implement... Figure 9 The functions of each module in the device shown.

[0064] The processor is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory and calling data stored in memory, it can monitor the device's various functions and process data, thereby enabling overall monitoring of the device.

[0065] In an alternative design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. In some embodiments, the processor and memory may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0066] The processor can be a general-purpose processor, such as a CPU, digital signal processor, application-specific integrated circuit, field-programmable array, or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the large-scale delivery drone cargo hold loading and balancing method disclosed in the embodiments of this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0067] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures, and accessible by a computer, but is not limited thereto. In embodiments of the present invention, memory can also be a circuit or any other device capable of implementing storage functions, used to store program instructions and / or data.

[0068] By designing and programming the processor, the code corresponding to the cargo hold loading and balancing method for a large delivery drone described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the steps of the method described in the foregoing embodiments during operation. How to design and program the processor is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0069] Based on the same inventive concept, embodiments of the present invention also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a large-scale delivery drone cargo hold loading and balancing method described above.

[0070] In some alternative embodiments, the present invention also provides a method for balancing the cargo hold of a large delivery drone, which can also be implemented as a program product including program code. When the program product is run on a device, the program code is used to cause the control device to perform the steps in a method for balancing the cargo hold of a large delivery drone according to various exemplary embodiments of the present invention as described in this specification.

[0071] It should be noted that although several units or sub-units of the apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the invention, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units. Furthermore, although the operation of the method of the invention is described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0072] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0074] Program code for performing the operations of this invention can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0075] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0076] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0077] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0078] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for balancing the cargo hold of a large-scale delivery drone, characterized in that, include: Receive delivery mission instructions and determine the total weight of the cargo and the number of container units; both the total weight of the cargo and the number of container units are less than the limit value of the UAV cargo compartment; Based on the total weight of the cargo and the number of container units, several loading schemes that meet the load constraints are generated through a traversal process, and then a set of loading schemes that meet the load center of gravity envelope is generated through a selection process. Based on predetermined optimization factors, an efficiency evaluation equation is established to determine N candidate loading schemes from the set of loading schemes; Based on a set of fixed airdrop timing, determine the loading scheme that conforms to the airdrop center of gravity envelope and has the smallest dynamic change range of the center of gravity from N candidate loading schemes. Based on the determined loading scheme, loading information for each container unit is generated, which includes the weight of the container unit and the storage slot.

2. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 1, characterized in that, The process of generating several loading schemes that meet the load constraints based on the total weight of the cargo and the number of container units specifically includes: The system retrieves all possible scenarios for allocating the total weight of the cargo to NUM container units according to the preset minimum weight division, and then filling the NUM container units into the slots of the drone's cargo compartment. Each scenario represents a loading scheme. NUM is a fixed number of container units, and NUM is less than or equal to the number of slots in the drone's cargo compartment.

3. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 1, characterized in that, The set of loading schemes generated by filtering the loading center of gravity envelope specifically includes: Calculate the overall center of gravity of the aircraft for each loading scheme. If the center of gravity conforms to the preset loading center of gravity envelope, output it to the set of matching loading schemes. If it does not conform, calculate the center of gravity of the next loading scheme.

4. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 3, characterized in that, The formula for calculating the overall center of gravity of the aircraft includes: in, As the center of gravity of the entire aircraft, The weight of the i-th to NUMth container unit, plus the weight of the empty engine and fuel; This includes the center of gravity of the first to NUM container units, as well as the center of gravity of the empty engine and fuel.

5. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 1, characterized in that, The step of establishing an efficiency evaluation equation based on predetermined optimization factors to determine N candidate loading schemes from the set of loading schemes specifically includes: Based on the selection of the economic cruise center of gravity and the pitch inertia of the entire aircraft, a comprehensive performance evaluation equation is established. Calculate the overall center of gravity and pitch inertia of the aircraft for each loading scheme in the set of loading schemes, input them into the comprehensive performance evaluation equation, and obtain the value of each scheme; The value of all loading schemes is sorted in descending order, and the top N loading schemes are selected as candidate loading schemes.

6. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 5, characterized in that, The comprehensive performance evaluation equation is as follows: in, For the value of the loading scheme, As a factor characterizing the merits of the centroid location, A factor characterizing the quality of the overall inertia; and These are the weights of the factors characterizing the quality of the center of gravity position and the factors characterizing the quality of the overall inertia, respectively. , These are the rear limit and the front limit of the center of gravity, respectively. As the center of gravity of the entire aircraft, As the focus of economic cruise, For the total inertia of the machine, Let be the inertia of the i-th container unit.

7. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 1, characterized in that, The process of determining the loading scheme that conforms to the airdrop center of gravity envelope and has the smallest dynamic change range of the center of gravity from N candidate loading schemes based on a set of fixed airdrop timings specifically includes: Each candidate loading scheme is stored in a linked list. The information of a single linked list node includes: slot number, container weight, container center of gravity, cargo unlocking time, and a pointer to the next node. Based on a fixed airdrop sequence, the linked list corresponding to each set of candidate loading schemes and the center of gravity of each node are updated through traversal, and the range of change of airdrop center of gravity during the traversal process is determined. The candidate loading schemes are sorted by the range of change of the airdrop center of gravity, and the candidate loading scheme with the smallest range of change of the airdrop center of gravity is selected as the optimal loading scheme.

8. The method for loading and balancing the cargo hold of a large-scale delivery drone according to claim 7, characterized in that, The process involves traversing and updating the linked list corresponding to each set of candidate loading schemes and the centroid of each node based on a fixed airdrop sequence, and determining the range of changes in the airdrop centroid during the traversal process. Specifically, this includes: S1. Initialize the data required for calculation, including time T=0, initialize the container unit information in the linked list LoadList to the given input information, and calculate the acceleration a according to the fuselage angle of attack and cargo platform friction coefficient at the given airdrop time; S2. Traverse the linked list and update the linked list and the centroid STA of each node: If This indicates that the cargo in slot i is unlocked at time T, and its center of gravity STA is updated. S3. Determine whether the updated center of gravity STA is greater than the center of gravity STA at the exit position. leave If the value is greater than 0, then the node is removed from the linked list. S4. Traverse the updated linked list, calculate the center of gravity of the whole machine, and determine whether the center of gravity of the whole machine exceeds the limit. If it exceeds the limit, exit the loop directly and output a warning that the center of gravity exceeds the limit. If it does not exceed the limit, record the time T and the center of gravity of the whole machine. S5. Check if the linked list is empty. If not empty, update time T += 0.01 and return to S2. If empty, exit the loop and output time T and the center of gravity of the entire machine. Relationship diagram and range of airdrop center of gravity changes : in, and These represent the maximum and minimum values ​​of the center of gravity change during the airdrop process.

9. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, which executes the instructions stored in the memory to perform the method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store instructions that, when executed, cause the method as described in any one of claims 1-8 to be implemented.

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