An intelligent electric forklift control method and system based on a standardized API interface

Abstract

The present invention relates to the technical field of data processing, and in particular to an intelligent electric forklift control method and system based on a standardized API interface. The method includes defining a mandatory parameter set including the geometric features of the handling object of the electric forklift; establishing a standardized API interface and configuring at least modifiable dynamic parameters for the standardized API interface, where the dynamic parameters are established based on the mandatory parameter set; using the standardized API interface to implement request-response and obtaining the requests of users who request to use the electric forklift; obtaining the requests of a certain number of recent users, and updating and optimizing the dynamic parameters of the standardized API interface according to the requests of the certain number of recent users. By unifying the data specifications and communication protocols, the problems of inconsistent interfaces and poor compatibility of traditional handling equipment are solved, enabling it to formulate reasonable handling strategies according to specific situations, ensuring the safety and efficiency of the handling process, and dynamically quantifying the handling stability through the mathematical model of the tipping risk coefficient.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an intelligent electric forklift control method and system based on a standardized API interface. Background Art

[0002] In current industrial production and logistics transportation, heavy-load handling equipment is increasingly widely used. For heavy-load handling equipment with a load capacity of more than 20 tons, it plays a crucial role in scenarios such as mold manufacturing and port container transportation. However, there are many problems in the interaction between these devices and the logistics management system.

[0003] Because the items are relatively large, the quantity and variety of items to be handled are not too many, but there are some differences in the volume of each heavy object. For the handling of such large heavy objects in the prior art, when receiving the handling requirements sent by the demand side, it cannot receive the request and analyze the information of the items, and cannot handle the heavy objects specifically. The interface design of traditional heavy-load electric forklifts is relatively simple, mainly focusing on the weight information of the object, and unable to analyze the three-dimensional characteristic parameters of the object. In actual handling scenarios, the shapes and sizes of large heavy objects are different. For example, molds may have irregular shapes, and there are also various specifications for the length, width, and height of containers. Due to the lack of understanding of the three-dimensional characteristics of the object, problems such as unstable grasping and center-of-gravity deviation may occur during the handling process by the forklift, which not only affects the handling efficiency but also may lead to safety accidents.

[0004] In the current market environment, heavy-load electric forklift manufacturers of different brands often adopt their own private protocols to protect their own technologies and market advantages. This has led to difficulties in effective communication and collaborative work between devices of different brands. Summary of the Invention

[0005] In order to solve the problems mentioned in the above background art, the present invention provides an intelligent electric forklift control method based on a standardized API interface. At the same time, an intelligent electric forklift control system based on a standardized API interface is provided.

[0006] An intelligent electric forklift control method based on a standardized API interface provided by the present invention adopts the following technical solutions:

[0007] In a first aspect, an intelligent electric forklift control method based on a standardized API interface includes the steps of:

[0008] Defining a mandatory parameter set including the geometric characteristics of the handling object of the electric forklift;

[0009] Establish a standardized API interface, configure at least modifiable dynamic parameters for the standardized API interface, where the dynamic parameters are established based on a set of mandatory parameters, and the standardized API interface is at least applied to transmit stability evaluation data of the carried object;

[0010] Use the standardized API interface to implement request-response and obtain the requests of users who request to use an electric handling vehicle;

[0011] Conduct a stability evaluation of the carried object according to the user's request, and output a control command based on the stability evaluation;

[0012] Obtain the requests of a certain number of recent users, and update and optimize the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users.

[0013] In a second aspect, an intelligent electric handling vehicle control system based on a standardized API interface includes:

[0014] A parameter management module for defining a set of mandatory parameters including the geometric characteristics of the handling object of the electric handling vehicle;

[0015] An API interface module for establishing a standardized API interface and configuring at least modifiable dynamic parameters for the standardized API interface, where the dynamic parameters are established based on the set of mandatory parameters;

[0016] An interaction module for implementing request-response using the standardized API interface, where the standardized API interface is at least applied to transmit stability evaluation data of the carried object, and obtaining the requests of users who request to use an electric handling vehicle;

[0017] An evaluation and control module for conducting a stability evaluation of the carried object according to the user's request and outputting a control command based on the stability evaluation;

[0018] A parameter update module for obtaining the requests of a certain number of recent users and updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users.

[0019] Advantageous technical effects of the present invention: This application solves the problems of inconsistent interfaces and poor compatibility of traditional handling equipment by unifying data specifications and communication protocols. The standardized API interface includes shape parameters, constraint parameters, etc., providing comprehensive task information, enabling it to formulate reasonable handling strategies according to specific situations, ensuring the safety and efficiency of the handling process. In the core application, through the mathematical model of the tipping risk coefficient K, parameters such as the center of gravity coordinates of the object, the width of the support surface, and the tilt angle are comprehensively considered to dynamically quantify the handling stability, distinguish risk levels, and trigger different control strategies. And by statistically analyzing recent user request data, the API interface is automatically updated. Description of the Drawings

[0020] Figure 1 This is a flowchart of a control method for an intelligent electric forklift based on a standardized API interface according to the present invention;

[0021] Figure 2 This is a flowchart of a method for updating and optimizing the dynamic parameters of a standardized API interface according to the present invention;

[0022] Figure 3 This is another flowchart of a method for updating and optimizing the dynamic parameters of a standardized API interface according to the present invention. Detailed implementation manners

[0023] An embodiment of the present invention discloses a control method for an intelligent electric forklift based on a standardized API interface. As Figure 1 shown, it specifically includes the steps: S1. Define a set of mandatory parameters including the geometric features of the handling object of the electric forklift, S2. Establish a standardized API interface, and configure at least modifiable dynamic parameters for the standardized API interface, S3. Use the standardized API interface to implement request response, and the standardized API interface is at least applied to transmit the stability evaluation data of the handling object and obtain the request of the user requesting to use the electric forklift, S4. Perform stability evaluation of the handling object according to the user's request and output a control command based on the stability evaluation, S5. Obtain the requests of a certain number of recent users, and update and optimize the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users.

[0024] In S1. Define a set of mandatory parameters including the geometric features of the handling object of the electric forklift:

[0025] First, in the control method for an intelligent electric forklift based on a standardized API interface, defining a set of mandatory parameters including the geometric features of the handling object of the electric forklift is the basis for the accurate and efficient operation of the entire system. It can provide accurate object information for the forklift to formulate appropriate handling strategies.

[0026] Specifically, the set of mandatory parameters includes but is not limited to basic parameters, shape parameters, and constraint parameters. Among them, the basic parameters include the weight, length, width, height dimensions, and center of gravity coordinates of the object. Among these basic parameters, the weight of the object directly determines the load capacity requirement of the forklift, and the power system, drive motor, etc. of the forklift need to provide appropriate power output according to the object weight.

[0027] It is understandable that obtaining the length, width, and height dimensions of the object helps the system plan an appropriate handling path and avoid collisions with the surrounding environment during handling.

[0028] It is understandable that the barycentric coordinates are crucial for ensuring stability during the handling process. During the handling process, the handling vehicle needs to adjust the position and attitude of the cargo-carrying device according to the barycentric position of the object to ensure the balance of the object.

[0029] Specifically, the shape parameter refers to the geometric type of the object, such as a cuboid, a cylinder, or an irregular object. The shape parameter is a key factor affecting the handling strategy. Different geometric types of objects require different grasping methods and supporting methods.

[0030] Specifically, the constraint parameters include the maximum tilt angle and the support surface width. The maximum tilt angle is an important constraint condition to ensure the stability of the object during the handling process. It limits the allowable tilt degree of the object during the handling process. Exceeding this angle may cause the object to fall.

[0031] It is understandable that the support surface width affects the support stability of the object. A wider support surface can provide better stability. During the handling process, the handling vehicle can adjust the spacing of the cargo-carrying device or select a suitable support method according to the requirement of the support surface width. For a wider object, the handling vehicle will adjust the spacing of the cargo-carrying device to a suitable position to provide a wide enough support surface to ensure the stability of the object during the handling process.

[0032] In S2. Establish a standardized API interface and configure at least modifiable dynamic parameters for the standardized API interface:

[0033] Specifically, establishing a standardized API interface is the key to realizing the efficient interaction between the intelligent electric handling vehicle and different logistics management systems. The API interface adopts a unified communication format and data structure. The protocol selects the HTTP / HTTPS protocol, and the data transmission format uses the JSON format to transmit data. There is a unified interface address naming rule for handling handling requests.

[0034] Specifically, define the core fields for the API interface. The definition of the core fields includes object characteristics, handling instructions, and safety parameters. Among them, the object characteristics include the mandatory parameter set defined in step S1, that is, the basic parameters, shape parameters, and constraint parameters. These parameters provide detailed information about the object for the handling vehicle.

[0035] Specifically, the handling instructions are used to clarify the starting position, target position, and handling sequence. The starting position and target position are accurate to specific coordinates or warehouse location numbers, and the handling sequence is sorted according to the priority of the task and the actual situation.

[0036] Exemplarily, the content of the handling instructions:

[0037] Define the starting point of the handling task, accurate to specific coordinates (such as three-dimensional coordinates (X, Y, Z), unit: meter) or the warehouse location number, such as the location code A-01-05 in a stereoscopic warehouse, indicating the 5th layer of the 1st column in Area A.

[0038] The coordinates X = 10.5, Y = 5.2, Z = 0.3 represent the ground plane coordinates of 10.5 meters × 5.2 meters, and the height of the cargo-carrying equipment is 0.3 meters.

[0039] Location number: Warehouse Area 3 - Shelf 2 - Location 18.

[0040] When there are multiple handling tasks, define the priority and order of task execution, supporting sorting by task ID or sorting by time / weight priority.

[0041] Handling order: Task ID - 001 (high priority, execute first) → Task ID - 002 (low priority, execute later).

[0042] Path order: First, move from the starting position A to the intermediate temporary storage area B, and then move from B to the target position C.

[0043] Specifically, safety parameters are used to specify the maximum driving speed and maximum load weight limit. The maximum driving speed is set according to different working scenarios and load conditions, and the maximum load weight is determined based on the load-bearing capacity of the handling vehicle.

[0044] Exemplarily, the specific content of the safety parameters:

[0045] Specify the maximum driving speed allowed for electric handling vehicles under different loads or scenarios to avoid the center of gravity shifting or insufficient braking distance due to excessive speed.

[0046] The data format adopts numerical type (unit: km / h or m / s), for example, 20 km / h (when unloaded), 10 km / h (when fully loaded and the support surface is narrow).

[0047] Specify the maximum weight that the handling vehicle can safely carry, which is determined by the mechanical structure of the equipment and the performance of the power system.

[0048] For example, for a handling vehicle with a rated load of 25 tons, it is clearly prohibited to exceed this value in the safety parameters.

[0049] The data format adopts numerical type (unit: ton or kg), such as 25000 kg.

[0050] It can be understood that by establishing a standardized API interface, heavy-duty electric handling vehicles of different brands and various logistics management systems can be quickly and conveniently connected.

[0051] Specifically, modifiable dynamic parameters are configured for the standardized API interface. The dynamic parameters are established based on a set of mandatory parameters and can be flexibly adjusted according to the actual handling tasks and environmental changes to ensure the safety and efficiency of the handling process.

[0052] Specifically, the modifiable dynamic parameters include power output adjustment parameters, path planning optimization parameters, cargo equipment attitude adjustment parameters, cargo equipment adaptation parameters, support method adjustment parameters, speed and attitude adjustment parameters. Among them, the power output adjustment parameters dynamically adjust the power output of the handling vehicle according to the weight of the object. When the object is light, the power of the drive motor is reduced to save energy. When the weight of the object approaches the maximum load capacity of the handling vehicle, the power output is increased to ensure the stable operation of the handling vehicle.

[0053] Specifically, the path planning optimization parameters optimize the path planning of the handling vehicle based on the length, width, and height dimensions of the object. If the object size is large, the width and turning radius of the path are appropriately increased to avoid collisions with the surrounding environment during handling.

[0054] Specifically, the cargo equipment attitude adjustment parameters adjust the position and attitude of the cargo equipment in real time according to the center of gravity coordinates of the object. When the center of gravity deviates, the height and angle of the cargo equipment are automatically adjusted to ensure the balance of the object during handling. Specifically, the cargo equipment adaptation parameters automatically select the appropriate cargo equipment and adjust the grasping parameters according to the geometric type of the object. For cuboid objects, the spacing and depth of the parallel cargo equipment are adjusted to ensure uniform grasping; for cylindrical objects, the curvature and clamping force of the arc-shaped fixture are adjusted to prevent the object from rolling.

[0055] Specifically, the support method adjustment parameters configure different support methods according to objects of different geometric types. Specifically, the speed and attitude adjustment parameters dynamically adjust the driving speed and attitude of the handling vehicle according to the constraints of the maximum tilt angle and the support surface width. When the maximum tilt angle is small, the driving speed is reduced to avoid dropping the object due to excessive tilting; when the support surface width is narrow, the spacing of the cargo equipment is adjusted or a more stable support method is selected.

[0056] Exemplarily, the power output adjustment parameters dynamically adjust the power of the drive motor according to the weight of the handled object. It is stored in the form of key-value pairs, for example: {"weight_threshold": 20, "power_ratio": 0.9}, with the unit of ton (weight) and percentage (power ratio).

[0057] Exemplarily, for the path planning optimization parameters, the path width and turning radius are adjusted according to the length, width, and height of the object. It is stored as structured data, such as: {"length":3,"width":2,"path_width":4,"turn_radius":5}, with the unit being meters (m).

[0058] Exemplarily, for the attitude adjustment parameters of the cargo-carrying equipment, the height and tilt angle of the cargo-carrying equipment are adjusted according to the center-of-gravity coordinates of the object. The data storage uses a three-dimensional coordinate + angle combination. For example: {"offset_x":0.5,"height":1.2,"tilt_angle":2}, with the units being meters (m) and degrees (°).

[0059] Exemplarily, for the adaptation parameters of the cargo-carrying equipment, the cargo-carrying equipment is selected according to the geometric type of the object and the parameters are configured. The data storage uses an enumeration + numerical value combination. For example: {"tool_type":"parallel_fork","spacing":1.65,"clamping_force":500}, with the units being meters (m) and Newtons (N).

[0060] Exemplarily, for the support method adjustment parameters, the support surface range is determined according to the geometric type of the object. The data storage uses structured dimension parameters. For example: {"shape":"irregular","min_support_width":1.2,"min_support_length":2.0}, with the unit being meters (m).

[0061] Exemplarily, for the speed and attitude adjustment parameters, the driving speed is restricted according to the tilt angle and the support surface width. The data storage uses a threshold + numerical value combination. For example: {"max_speed":5,"tilt_threshold":10,"compensation_factor":0.8}, with the units being kilometers per hour (km / h) and degrees (°).

[0062] In S3, a standardized API interface is used to implement request-response. The standardized API interface is at least applied to transmit the stability evaluation data of the handling object, and in the request of the user who requests to use the electric forklift:

[0063] Specifically, a standardized API interface is used to implement request-response. The request processing includes:

[0064] A POST request is sent to the endpoint through the HTTPS protocol. The request body includes the task identifier, object feature parameters, target location, priority identifier, and timestamp.

[0065] Exemplarily, a task identifier is a string that uniquely identifies a single handling task, used to distinguish different requests and track the task status. Format: {device ID}_{timestamp}_{random suffix} (e.g., TRUCK-001_202504071430_001). It contains the device identifier (such as the handling vehicle number), the request time (accurate to the second), and a uniqueness verification code to ensure global uniqueness.

[0066] Exemplarily, object feature parameters include the geometric features and constraint conditions of the handling object, corresponding to the "mandatory parameter set". It includes basic parameters, shape parameters, and constraint parameters.

[0067] Exemplarily, a target location contains the end coordinates or storage location number of the handling task, supporting multi-scenario positioning. The storage location number is structured and encoded in the format {warehouse area}-{shelf}-{layer / column / position} (e.g., Area A - Shelf 3 - 5th layer, 2nd column or standardized encoding A03-05-02).

[0068] Exemplarily, a priority identifier contains the priority marked for task execution to ensure that high-priority tasks are processed first. For example, use integers from 1 to 10, with 1 being the highest priority (e.g., an urgent mold handling task is set to 1, and ordinary goods are set to 5). Default rule: When the priority is not specified, the default is set to 5; tasks with the same priority are executed in the order of the timestamp.

[0069] Exemplarily, a timestamp records the specific time when the request is sent, used for task timing management and exception timeout judgment.

[0070] Exemplarily, for example, when the user requests to move a 20-ton cuboid cargo (dimensions 4m×2m×3m, center of gravity coordinates [2.0, 1.0, 1.5m]) to the storage location in Area B - Shelf 2 - 10th layer, the request body content is as follows: Task identifier: TRUCK-002_202504071500_003; Object features: weight 20.00t, dimensions [4.0, 2.0, 3.0], center of gravity [2.0, 1.0, 1.5]; Shape: cuboid, constraint parameters use the system default value (maximum tilt angle 15°); Target location: Area B - Shelf 2 - 10th layer; Priority: 5 (regular task); Timestamp: 2025-04-07T15:00:05+08:00.

[0071] Protocol parsing: includes version negotiation, automatic identification of the API version number, data cleaning, removal of redundant fields, unification of the timestamp format, and coordinate origin conversion;

[0072] Parameter verification: includes field integrity verification, numerical range verification, and unit conversion.

[0073] Exemplarily, version negotiation and automatic API version number recognition include declaring the supported API version (format: major version.minor version, such as 2.0) through the request header (such as the X-API-Version field) in the first request. The server defaults to supporting the latest version (such as the current 2.0), while being compatible with the core functions of historical versions (such as 1.0).

[0074] If the client does not declare the version, the server defaults to parsing according to the lowest compatible version (such as 1.0), only processes basic parameters (weight, size), and ignores the dynamic parameter extension functions (such as the correction logic of the safety margin coefficient λ).

[0075] If the client declares a version higher than the server's supported range, the server returns an error code and prompts the list of supported versions (such as [1.0, 2.0]) to ensure seamless docking of new and old devices.

[0076] Exemplarily, data cleaning and redundant field filtering include basic parameter verification. For example, the weight must be greater than 0; the center of gravity coordinates (xg, yg, zg) need to satisfy zg≥0 (the height of the bottom surface of the object is not lower than the ground), and be consistent with the length, width, and height dimensions logic (such as the x coordinate of the center of gravity needs to be within the range of [0, length]). Shape parameter verification, the geometric type only allows three enumerated values: cuboid, cylinder, and irregular body. Other inputs (such as cone) are automatically mapped to the irregular body and marked for manual confirmation. Constraint parameter verification, the maximum tilt angle θmax needs to be within the range of (0°, 90°), and if it exceeds, it is default set to the safety threshold of 15°; the support surface width must be greater than 0 and not exceed 80% of the maximum adjustable width of the handling vehicle's cargo equipment (to avoid exceeding the limit). Non-standard fields mis-transmitted by the client (such as irrelevant parameter = xxx) are automatically excluded during parsing.

[0077] Exemplarily, the standardization of timestamp formats includes supporting the client to send timestamps in multiple formats (such as 2025-04-07 15:00:05, 20250407T150005+0800, Unix timestamp 1680855605). During parsing, it is uniformly converted to the ISO8601 standard format (including the time zone, such as 2025-04-07T15:00:05+08:00).

[0078] If the client does not declare the time zone, the server time zone (such as UTC+8) is default adopted, and the original timestamp and the converted timestamp are recorded in the log to ensure the accuracy of task time sequence management (such as timeout judgment: if there is no response for more than 30 seconds, it is marked as abnormal).

[0079] Exemplarily, the coordinate origin conversion means defining the origin of the globally unified coordinate system (such as the entrance of the logistics warehouse being (0, 0, 0)), the Z-axis is vertically upward (unit: meter), the X-axis points in the direction of the warehouse length, and the Y-axis points in the width direction. If the coordinates sent by the client are in the local coordinate system (such as the origin of a certain storage area being (100, 50, 0)), the coordinate system offset parameters are attached in the request body (such as offset_x = 100, offset_y = 50, offset_z = 0), and the server converts according to the formula global coordinates = local coordinates + offset; if the offset is not declared, it is processed by default according to the global coordinate system, and the coordinate values need to satisfy X ≥ 0, Y ≥ 0, Z ≥ 0, otherwise it is regarded as an invalid coordinate and an error prompt is returned (such as "The coordinates of the target position cannot be negative").

[0080] In S4. Perform the stability evaluation of the handling object according to the user's request, and output the control command based on the stability evaluation:

[0081] Specifically, after obtaining the request of the user who requests to use the electric handling vehicle, perform the stability evaluation of the handling object according to the user's request. The stability evaluation of the handling object includes calculating the tipping risk coefficient. The tipping risk coefficient is based on the geometric characteristic parameters of the object (center of gravity coordinates, support surface width, geometric type), the real-time state of the handling vehicle (spacing between the cargo-carrying equipment, traveling speed), and the constraint parameters (maximum tilting angle), and realizes the dynamic evaluation of the tipping risk through the coupling calculation of multi-dimensional parameters.

[0082] Specifically, the calculation of the tipping risk coefficient includes the steps:

[0083] Define the actual center of gravity coordinates of the object as (x g , y g , z g ), the geometric center coordinates of the support surface of the cargo-carrying equipment are (x c , y c , z c ), the center of gravity offset along the horizontal x-axis direction of the object is: ;

[0084] The center of gravity offset along the horizontal y-axis direction of the object is: ;

[0085] The offset distance d offset of the object is: ;

[0086] Define the width of the adjusted support surface of the handling vehicle's cargo-carrying equipment along the x-axis as W, and the length of the adjusted support surface of the handling vehicle's cargo-carrying equipment along the y-axis as L. Then the half-width and half-length of the adjusted support surface of the handling vehicle's cargo-carrying equipment are W / 2 and L / 2 respectively.

[0087] When the geometric type of the object is a cuboid or a cylinder, the range of the support surface is jointly determined by the spacing of the loading equipment and the bottom size of the object; for an irregular object, the range of the support surface is determined by the minimum stable support surface width W min and length L min determined by the user.

[0088] Define the real-time tilt angle of the forklift as θ (the inclination angle around the x-axis or y-axis), and the center of gravity height h of the object g , where h g =z g -z c Then, the increment d of the horizontal offset of the center of gravity caused by the tilt θ The calculation formula is: d θ =h g ×sinθ;

[0089] Define the tipping risk coefficient as K. The tipping risk coefficient K comprehensively reflects the degree to which the center of gravity offset exceeds the support surface. The calculation formula of the tipping risk coefficient K is: ;

[0090] The physical meaning of the tipping risk coefficient K:

[0091] When K < 1, the center of gravity projection is within the support surface, and the handling state is stable; when K ≥ 1, the center of gravity projection exceeds the edge of the support surface, there is a tipping risk, and the greater the value of K, the higher the risk.

[0092] Modify the constraint parameters. The constraint parameter modification is based on the maximum tilt angle θ max defined for the object and the support surface width W req and the support surface length L req for modification. Introduce a safety margin coefficient λ (0 < λ < 1), with λ preset. Then the actual allowable maximum offset distance d max is: d max =λ×min(W req / 2, L req / 2), and then modify the risk coefficient to:

[0093] ;

[0094] Obtain the object characteristic parameters (center of gravity coordinates, geometric type, constraint parameters) and the real-time state of the forklift (spacing of the loading equipment, tilt angle, speed) from the API interface, and calculate the tipping risk coefficient K to determine the tipping risk. Preferably, preset two levels of risk thresholds:

[0095] Warning threshold K1 (e.g., K1 = 0.8), emergency threshold K2 (e.g., K2 = 0.95).

[0096] Judge the risk coefficient before outputting the command:

[0097] If K ≥ K1, the spacing of the cargo-loading equipment is extended according to the geometric type of the object. The formula for adjusting the spacing of the cargo-loading equipment is as follows:

[0098] , .

[0099] Among them, △w is a constant, W max is the maximum adjustable width of the cargo-loading equipment, W old is the width of the cargo-loading equipment before extension, W new is the width of the cargo-loading equipment after extension. By increasing W new the support surface is enlarged and the value of K is reduced.

[0100] When K ≥ K2, the traveling speed is also adjusted. The formula for speed adjustment is as follows:

[0101] ;

[0102] In the formula, v new is the adjusted speed, v old is the speed before adjustment; the speed decreases linearly with the increase of the risk coefficient, reducing the influence of inertia force on the center-of-gravity offset.

[0103] If it is detected that the tilt angle is greater than half of the maximum tilt angle, an adjustment command for the tilt angle of the cargo-loading equipment is output to compensate for the tilt angle in the reverse direction.

[0104] This application generates adjustment commands for the spacing, speed, and attitude of the cargo-loading equipment according to the tipping risk coefficient K and outputs the adjustment commands.

[0105] In S5. Obtaining requests from a certain number of recent users and updating and optimizing the dynamic parameters of the standardized API interface according to the requests from a certain number of recent users:

[0106] In the "cargo-loading equipment adaptation parameters", for the geometric type of "cuboid", an "optional list" is correspondingly set, and at least the option of "parallel cargo-loading equipment" is included in the "optional list".

[0107] Specifically, count the proportion of users who choose to grab with parallel cargo-loading equipment when handling cuboids in recent requests. If more than 80% of the users choose to grab with parallel cargo-loading equipment when handling cuboids, the default tool for cuboids in the "cargo-loading equipment adaptation parameters" is forcibly set to parallel cargo-loading equipment to reduce invalid parameter verification.

[0108] Exemplarily, such as Figure 2, The statistical period selects valid handling requests within the last 30 days (or when the cumulative number of similar requests reaches 1000, whichever comes first), ensuring that the data covers high-frequency scenarios and has real-time characteristics. Only include requests with the shape parameter labeled as "cuboid" and the user actively specifying the loading equipment, ensuring that the statistical results reflect the true preferences of the users. During the statistical period, when the proportion of cuboid handling requests where the user selects "parallel loading equipment" in the total number of requests of this type is ≥ 80% for three consecutive statistics (with a 24-hour interval between each), it triggers the forced update of the default tool to avoid short-term accidental data interfering with the stability of the strategy. In the "loading equipment adaptation parameters", adjust the default loading equipment corresponding to the "cuboid" geometric type from the "optional list" to "parallel loading equipment", so that the system preferentially calls the adaptation parameters of this tool. For all subsequent requests with the shape parameter of "cuboid", it automatically skips the loading equipment type verification link and directly matches the standard parameters of the parallel loading equipment, reducing the invalid verification steps during interface data parsing and improving the request response efficiency.

[0109] The "loading equipment adaptation parameters" configure a "wrapping angle - weight" mapping table for the cylinder geometric type, which is used to generate control instructions for the arc-shaped fixture according to the weight of the cylinder, and the control instructions include the wrapping angle.

[0110] Specifically, in the recent requests, count the distribution of the wrapping angles of the arc-shaped fixtures in the recent cylinder handling requests, stratify by load weight (for example, the average wrapping angle is 135° when ≤ 25 tons, and 160° when > 25 tons), generate a "wrapping angle - weight" mapping table, and update the "loading equipment adaptation parameters" of the API interface.

[0111] Exemplarily, such as Figure 3 , Wrapping angle collection: Each request records the wrapping angle actually configured by the user (unit: degree), and this angle needs to meet the physical constraints of the arc-shaped fixture (such as a minimum of 120° and a maximum of 180°), and outliers outside the range (such as 110° or 190°) are automatically marked as invalid and excluded. Take the median of the valid wrapping angles within each weight range (for example: 135° in the light load range, 150° in the medium load range, 165° in the heavy load range) to avoid the interference of extreme values on the statistical results. Mapping table structure: Adopt the corresponding relationship of "weight range - recommended wrapping angle", and the example is as follows: weight ≤ 20 tons → 135°; 20 tons < weight ≤ 25 tons → 150°; weight > 25 tons → 170°; when receiving a cylinder handling request, automatically read the object weight, match the "wrapping angle - weight" mapping table, and generate control instructions for the arc-shaped fixture.

[0112] The "speed and attitude adjustment parameters" set scenario-specific configuration items to at least adjust the tilt angle threshold in different scenarios.

[0113] Specifically, in the scenario of port container transportation, the inclination angle threshold adjustment data when users face slope sections are statistically analyzed (for example, the default 15° is averaged down to 12°), association rules are generated, and the speed and attitude adjustment parameters of the API interface are updated.

[0114] Exemplarily, for the slope section in port container transportation, this scenario is sensitive to the inclination angle due to the high center of gravity of the container and the fixed support surface (the bottom size is determined by the container specifications). Incorporate the handling requests in which users have actively adjusted the inclination angle threshold (for example, users manually modify the default 15° to 12° in the port system to avoid the system automatically ignoring the invalid default value); use a sliding window to select the valid requests within the past 30 days (accumulative ≥ 200 requests of the same type of scenario) to ensure that the data covers the high-frequency operation period and reflects seasonal variations (for example, when the port slope is slippery during the rainy season, users tend to prefer a lower threshold). Record the original default threshold θ_default (system preset 15°), the threshold θ_user after user adjustment (such as 12°, 10°), and the slope gradient α (real-time collected by the on-vehicle slope sensor, unit: °) for each request; the association rule generation adopts a triple of "scenario label - slope grade - recommended threshold", and the example is as follows:

[0115] Scenario label: Port container slope handling; Slope grade: gentle slope (5° ≤ α < 10°), steep slope (α ≥ 10°); Recommended threshold: 12° for gentle slope and 10° for steep slope. Write the association rules into the scenario-specific configuration item in the "speed and attitude adjustment parameters" to update the speed and attitude adjustment parameters of the API interface.

[0116] The "speed and attitude adjustment parameters" are at least configured with an initial speed upper limit to clarify the safe speed upper limit of the handling vehicle.

[0117] Specifically, in the scenario of factory mold handling, the relationship between the load weight and the speed set by the user is analyzed (for example, the average speed is 4 km / h when the load is 30 tons and 6 km / h when it is 20 tons), a dynamic mapping of "weight - speed" is established, and the initial speed upper limit in the "speed and attitude adjustment parameters" is automatically adjusted.

[0118] Exemplarily, based on the valid requests in the past 30 days, the request data with a speed setting exceeding the safety speed limit of the forklift (such as 10 km / h for no-load) or a tipping risk coefficient K≥0.8 is excluded to avoid interference of extreme operations on the model. It is divided into 3 core intervals according to the mold weight, and different speed limit rules are matched. For example, in the light-load interval (≤20 tons): the default initial speed is 6 km / h, and users are allowed to adjust it within the range of 4 - 8 km / h to meet the efficient handling requirements of smaller molds. In the medium-load interval (20 tons - 30 tons): based on historical data (such as the average speed of 5 km / h at 25 tons), the initial speed is set to 5 km / h, and the speed adjustment step is 0.5 km / h to avoid the center of gravity shift caused by frequent acceleration and deceleration. In the heavy-load interval (>30 tons): the forced initial speed ≤4 km / h (such as the average speed of 3.5 km / h at 35 tons). The "weight - speed" dynamic mapping uses a linear decreasing model to determine the speed limit.

[0119] It can be understood that the relationship between "evaluating the stability of the object to be carried according to the user's request and outputting a control command based on the stability evaluation" and "managing the standardized API interface" in the present application is as follows:

[0120] The core data required for stability evaluation (such as object geometric features, center of gravity coordinates, constraint parameters, etc.) are all obtained from the user request through the standardized API interface. The API interface provides a standardized input and output channel for stability evaluation. Stability evaluation is the core application scenario of API interface management. The standardized data is converted into specific handling strategies through the tipping risk model. The update of dynamic parameters also depends on the user data accumulated in the evaluation process, forming a closed loop of "data collection, strategy optimization, and improvement", and finally achieving the dual goals of "interface unification" and "handling intelligence", and giving full play to the real value of the management interface.

[0121] The embodiment of the present invention also provides an intelligent electric forklift control system based on a standardized API interface, including:

[0122] A parameter management module for defining a set of mandatory parameters including the geometric features of the object to be carried by the electric forklift;

[0123] An API interface module for establishing a standardized API interface and configuring at least modifiable dynamic parameters for the standardized API interface. The dynamic parameters are established based on the set of mandatory parameters;

[0124] An interaction module for implementing request response using the standardized API interface. The standardized API interface is at least applied to transmit the stability evaluation data of the object to be carried and obtain the request of the user who requests to use the electric forklift;

[0125] An evaluation control module, configured to perform a stability evaluation of an object to be carried according to a user's request, and output a control command based on the stability evaluation;

[0126] A parameter update module, configured to obtain requests of a certain number of users in the recent period, and update and optimize the dynamic parameters of the standardized API interface according to the requests of the certain number of users in the recent period.

[0127] Obviously, the method of the present invention can be implemented by a computer program. The computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, so that when the computer program is executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer program can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0128] Therefore, it can be understood that the present invention discloses an electronic device, including:

[0129] At least one processor; and

[0130] A memory communicatively connected to the at least one processor; wherein,

[0131] 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 the above-mentioned forestry survey planning design and analysis method based on three-dimensional laser modeling.

[0132] The above are all preferred embodiments of the present invention and do not limit the protection scope of the present invention accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A control method for an intelligent electric forklift based on a standardized API interface, characterized in that, Including the steps: Defining a set of mandatory parameters that include the geometric characteristics of the object to be carried by the electric forklift; Establishing a standardized API interface, configuring at least modifiable dynamic parameters for the standardized API interface, where the dynamic parameters are established based on the set of mandatory parameters, and the standardized API interface is at least applied to transmit the stability evaluation data of the carried object; Implementing request-response using the standardized API interface to obtain the requests of users who request to use the electric forklift; Conducting a stability evaluation of the carried object according to the user's request, and outputting a control command based on the stability evaluation; Obtaining the requests of a certain number of recent users, and updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users.

2. The intelligent electric forklift control method based on a standardized API interface according to claim 1, wherein The set of mandatory parameters includes basic parameters, shape parameters, and constraint parameters. Among them, the basic parameters include the weight, length, width, height dimensions, and center of gravity coordinates of the object. The shape parameter is the geometric type of the object, and the shape parameters include cuboid, cylinder, and irregular body. The constraint parameters include the maximum tilt angle and the support surface width.

3. The control method of an intelligent electric forklift based on a standardized API interface according to claim 2, characterized in that, Establishing a standardized API interface includes defining core fields for the API interface. The definition of the core fields includes object characteristics, handling instructions, and safety parameters. Among them, the object characteristics include the set of mandatory parameters. The handling instructions are used to clarify the starting position, target position, and handling sequence; the safety parameters are used to specify the maximum driving speed and the maximum load weight limit.

4. The control method of an intelligent electric forklift based on a standardized API interface according to claim 3, characterized in that, The modifiable dynamic parameters include power output adjustment parameters, path planning optimization parameters, cargo equipment attitude adjustment parameters, cargo equipment adaptation parameters, support method adjustment parameters, and speed and attitude adjustment parameters.

5. The control method of an intelligent electric forklift based on a standardized API interface according to claim 4, characterized in that Conducting a stability evaluation of the carried object according to the user's request specifically includes calculating the tipping risk coefficient K, and then determining the stability based on the tipping risk coefficient K, and judging whether the value of the tipping risk coefficient K is higher than the risk threshold.

6. The control method of an intelligent electric forklift based on a standardized API interface according to claim 5, characterized in that, Updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users includes: if the proportion of users who choose to grab parallel to the cargo equipment when handling a cuboid is greater than the threshold, then forcibly set the default tool for the cuboid in the cargo equipment adaptation parameters to the parallel cargo equipment.

7. A control method for an intelligent electric forklift based on a standardized API interface according to claim 6, characterized in that, Updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users includes: stratifying the load weight according to the wrapping angle distribution of the arc-shaped fixture in the recent cylinder handling requests, generating a "wrapping angle - weight" mapping table, and updating the cargo equipment adaptation parameters of the API interface.

8. A control method for an intelligent electric forklift based on a standardized API interface according to claim 7, characterized in that, Updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users includes: statistically analyzing the tilt angle threshold adjustment data when users face a slope section, generating an association rule, and updating the speed and attitude adjustment parameters of the API interface.

9. A control method for an intelligent electric forklift based on a standardized API interface according to claim 8, characterized in that, Updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of recent users includes: statistically analyzing the relationship between the load weight and the user-set speed, establishing a "weight - speed" dynamic mapping, and automatically adjusting the initial speed upper limit in the speed and attitude adjustment parameters.

10. An intelligent electric forklift control system based on a standardized API interface, characterized in that, Including: A parameter management module for defining a set of mandatory parameters that include the geometric characteristics of the object to be carried by the electric forklift; An API interface module for establishing a standardized API interface and configuring at least modifiable dynamic parameters for the standardized API interface, where the dynamic parameters are established based on a set of mandatory parameters; An interaction module for implementing request-response using the standardized API interface. The standardized API interface is at least applied to transmit stability evaluation data of the carried object and obtain the requests of users who request to use an electric forklift; An evaluation and control module for performing stability evaluation of the carried object according to the user's request and outputting control commands based on the stability evaluation; A parameter update module for obtaining the requests of a certain number of recent users and updating and optimizing the dynamic parameters of the standardized API interface according to the requests of the certain number of recent users.

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