Intelligent electric carrier control method and system based on standardized API interface

Abstract

The invention relates to the technical field of data processing, in particular to an intelligent electric carrier control method and system based on a standardized API (Application Program Interface), and the method comprises the steps: defining a forced parameter set containing the geometric characteristics of a carried object of an electric carrier; establishing a standardized API interface for at least configuring modifiable dynamic parameters for the standardized API interface, wherein the dynamic parameters are established based on a forced parameter set; a standardized API interface is adopted to realize request response, and a request of a user requesting to use the electric carrier is acquired; and obtaining recent requests of a certain number of users, and updating and optimizing dynamic parameters of the standardized API according to the recent requests of the certain number of users. The problems that a traditional carrying device is not uniform in interface and poor in compatibility are solved through a unified data specification and a communication protocol, a reasonable carrying strategy can be formulated according to specific conditions, the safety and efficiency of the carrying process are ensured, and the carrying stability is dynamically quantified through a mathematical model of an overturning 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 today's 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 equipment and the logistics management system.

[0003] Because the items are relatively large, the quantity and types of items to be carried 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 object, and cannot carry the heavy object 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 parse the three-dimensional feature 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 features 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 equipment of different brands. Summary of the Invention

[0005] 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: In the first aspect, an intelligent electric forklift control method based on a standardized API interface includes the steps of: 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. The dynamic parameters are established based on the mandatory parameter set, and the standardized API interface is at least applied to transmit the stability evaluation data of the handling object; Implement request response using a standardized API interface to obtain the requests of users who use electric forklifts for requests; Conduct a stability assessment of the object to be carried according to the user's request, and output a control command based on the stability assessment; Obtain the requests of a certain number of users in the near future, and update and optimize the dynamic parameters of the standardized API interface according to the requests of a certain number of users in the near future.

[0007] In a second aspect, an intelligent electric forklift control system based on a standardized API interface includes: A parameter management module for defining a set of mandatory parameters including the geometric characteristics of the objects 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 the set of mandatory parameters; An interaction module for implementing request response using a standardized API interface, where the standardized API interface is at least applied to transmit stability assessment data of the object to be carried, and obtain the requests of users who use the electric forklift for requests; An evaluation and control module for conducting a stability assessment of the object to be carried according to the user's request, and outputting a control command based on the stability assessment; A parameter update module for obtaining the requests of a certain number of users in the near future, and updating and optimizing the dynamic parameters of the standardized API interface according to the requests of a certain number of users in the near future.

[0008] The beneficial 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 inclination angle are comprehensively considered to dynamically quantify the handling stability, distinguish risk levels, and trigger different control strategies. And by statistically analyzing the request data of recent users, the API interface is automatically updated. Description of the Drawings

[0009] Figure 1 It is a flowchart of an intelligent electric forklift control method based on a standardized API interface of the present invention; Figure 2 It is a flowchart of updating and optimizing the dynamic parameters of the standardized API interface of the present invention; Figure 3 It is another flowchart of updating and optimizing the dynamic parameters of the standardized API interface of the present invention. Detailed Embodiments

[0010] 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, which specifically includes the steps: S1. Define a set of mandatory parameters including the geometric characteristics 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. Implement request response using the standardized API interface. The standardized API interface is at least applied to transfer the stability evaluation data of the handling object and obtain the request of the user requesting to use the electric forklift; S4. Perform the 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.

[0011] In S1. Define a set of mandatory parameters including the geometric characteristics of the handling object of the electric forklift: First of all, in the control method of the intelligent electric forklift based on the standardized API interface, defining a set of mandatory parameters including the geometric characteristics 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.

[0012] 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-bearing capacity requirements of the forklift. The power system, drive motor, etc. of the forklift need to provide appropriate power output according to the object weight.

[0013] It can be understood 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.

[0014] It can be understood that the center of gravity coordinates are crucial for ensuring stability during handling. During handling, the forklift needs to adjust the position and attitude of the cargo-carrying equipment according to the center of gravity position of the object to ensure the balance of the object.

[0015] Specifically, the shape parameter refers to the geometric type of the object, such as a cuboid, a cylinder, an irregular body. The shape parameter is a key factor affecting the handling strategy. Different geometric types of objects require different grasping methods and supporting methods.

[0016] 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 handling, which limits the allowable tilt degree of the object during handling. Exceeding this angle may cause the object to fall.

[0017] It is understandable that the width of the support surface 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 equipment or select a suitable support method according to the requirements of the support surface width. For a wider object, the handling vehicle will adjust the spacing of the cargo-carrying equipment to a suitable position to provide a wide enough support surface to ensure the stability of the object during handling.

[0018] In S2. Establishing a standardized API interface and configuring at least modifiable dynamic parameters for the standardized API interface: 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, selects the HTTP / HTTPS protocol, uses the JSON format for data transmission, and has a unified interface address naming rule for handling handling requests.

[0019] Specifically, define core fields for the API interface. The core field definition includes object characteristics, handling instructions, and safety parameters. Among them, object characteristics include the mandatory parameter set defined in step S1, that is, basic parameters, shape parameters, and constraint parameters. These parameters provide detailed information about the object for the handling vehicle.

[0020] 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. The handling sequence is sorted according to the priority of the task and the actual situation.

[0021] Exemplarily, the content of the handling instructions: Clarify the starting point of the handling task, accurate to specific coordinates (such as three-dimensional coordinates (X, Y, Z), unit: meter) or warehouse location number. For example, the location code A-01-05 in the automated warehouse represents the 5th layer of the 1st column in area A.

[0022] 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.

[0023] Location number: Warehouse area 3 - Shelf 2 - Location 18.

[0024] When there are multiple handling tasks, define the priority and sequence of task execution, and support sorting by task ID or sorting by time / weight priority.

[0025] Handling sequence: Task ID - 001 (high priority, execute first) → Task ID - 002 (low priority, execute later).

[0026] Path sequence: First, move from the starting position A to the intermediate temporary storage area B, and then move from B to the target position C.

[0027] Specifically, the safety parameters are used to specify the maximum traveling speed and the maximum load weight limit. The maximum traveling 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 forklift.

[0028] Exemplarily, the specific content of the safety parameters: Specify the maximum traveling speed allowed for the electric forklift under different loads or scenarios to avoid the center of gravity shifting or insufficient braking distance due to excessive speed.

[0029] The data format adopts a numerical type (unit: km / h or m / s). For example, 20 km / h (when unloaded) and 10 km / h (when fully loaded and the support surface is narrow).

[0030] Specify the maximum weight that the forklift can safely carry, which is determined by the mechanical structure of the equipment and the performance of the power system.

[0031] For example, for a forklift with a rated load of 25 tons, exceeding this value is clearly prohibited in the safety parameters.

[0032] The data format adopts a numerical type (unit: ton or kg), such as 25000 kg.

[0033] It can be understood that by establishing a standardized API interface, heavy-duty electric forklifts of different brands and various logistics management systems can be quickly and conveniently connected.

[0034] Specifically, configurable 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.

[0035] Specifically, the configurable 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 forklift according to the weight of the object. When the object is lighter, the power of the drive motor is reduced to save energy. When the object weight is close to the maximum load-bearing capacity of the forklift, the power output is increased to ensure the stable operation of the forklift.

[0036] Specifically, the path planning optimization parameters optimize the path planning of the forklift 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.

[0037] Specifically, the attitude adjustment parameters of the cargo handling equipment adjust the position and attitude of the cargo handling equipment in real time according to the center-of-gravity coordinates of the object. When the center of gravity shifts, the height and angle of the cargo handling equipment are automatically adjusted to ensure the balance of the object during handling. Specifically, the adaptation parameters of the cargo handling equipment automatically select the appropriate cargo handling equipment and adjust the grasping parameters according to the geometric type of the object. For a cuboid object, the spacing and depth of the parallel cargo handling equipment are adjusted to ensure uniform grasping; for a cylindrical object, the curvature and clamping force of the arc-shaped fixture are adjusted to prevent the object from rolling.

[0038] 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 forklift according to the constraints of the maximum tilt angle and the width of the support surface. When the maximum tilt angle is small, the driving speed is reduced to avoid dropping the object due to excessive tilting; when the width of the support surface is narrow, the spacing of the cargo handling equipment is adjusted or a more stable support method is selected.

[0039] 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).

[0040] Exemplarily, the path planning optimization parameters adjust the path width and turning radius 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 of meter (m).

[0041] Exemplarily, the attitude adjustment parameters of the cargo handling equipment adjust the height and tilt angle of the cargo handling equipment according to the center-of-gravity coordinates of the object. The data storage adopts a three-dimensional coordinate + angle combination, for example: {"offset_x": 0.5, "height": 1.2, "tilt_angle": 2}, with the unit of meter (m) and degree (°).

[0042] Exemplarily, the adaptation parameters of the cargo handling equipment select the cargo handling equipment and configure the parameters according to the geometric type of the object. The data storage adopts an enumeration + numerical value combination, for example: {"tool_type": "parallel_fork", "spacing": 1.65, "clamping_force": 500}, with the unit of meter (m) and Newton (N).

[0043] Exemplarily, for the support method adjustment parameter, the support surface range is determined according to the geometric type of the object. Structured dimensional parameters are used for data storage, for example: {"shape":"irregular","min_support_width":1.2,"min_support_length":2.0}, with the unit being meters (m).

[0044] Exemplarily, for the speed and attitude adjustment parameter, the driving speed is restricted according to the tilt angle and the support surface width. Threshold + numerical combination is used for data storage, for example: {"max_speed":5,"tilt_threshold":10,"compensation_factor":0.8}, with the units being kilometers per hour (km / h) and degrees (°).

[0045] In S3, a standardized API interface is adopted to implement request response. The standardized API interface is at least applied to transfer the stability evaluation data of the handled object, and in the request from the user who requests to use the electric handling vehicle: Specifically, a standardized API interface is adopted to implement request response. The request processing includes: Send a POST request to the endpoint through the HTTPS protocol. The request body includes the task identifier, object feature parameters, target location, priority identifier, and timestamp.

[0046] Exemplarily, the 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} (such as TRUCK-001_202504071430_001). It contains the device identifier (such as the handling vehicle number), the request time (accurate to seconds), and a uniqueness verification code to ensure global uniqueness.

[0047] Exemplarily, the object feature parameters include the geometric features and constraint conditions of the handled object, corresponding to the "mandatory parameter set". It includes basic parameters, shape parameters, and constraint parameters.

[0048] Exemplarily, the 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 of {warehouse area}-{shelf}-{layer / column / position} (such as Area A - Shelf 3 - 5th layer, 2nd column or standardized encoding A03 - 05 - 02).

[0049] Exemplarily, the priority identifier includes the priority marked for task execution to ensure that high-priority tasks are processed first. For example, integers from 1 to 10 are used, with 1 being the highest priority (such as setting the emergency mold handling task to 1 and ordinary goods 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.

[0050] Exemplarily, the timestamp records the specific time when the request is sent and is used for task time sequence management and abnormal timeout judgment.

[0051] Exemplarily, for example, when a user requests to move a 20-ton cuboid cargo (dimensions 4m×2m×3m, center of gravity coordinates [2.0, 1.0, 1.5m]) to Shelf 2, Layer 10, Area B of the warehouse, the request body content is as follows: Task identifier: TRUCK-002_202504071500_003; Object characteristics: 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 values (maximum tilt angle 15°); Target location: Area B - Shelf 2 - Layer 10; Priority: 5 (regular task); Timestamp: 2025-04-07T15:00:05+08:00.

[0052] Protocol parsing: includes version negotiation, automatic identification of API version number, data cleaning, removal of redundant fields, unification of timestamp format, and coordinate origin conversion; Parameter verification: includes field integrity check, numerical range check, and unit unified conversion.

[0053] Exemplarily, version negotiation and automatic identification of API version number 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 natively supports the latest version (such as the current 2.0) and is also compatible with the core functions of historical versions (such as 1.0).

[0054] 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, dimensions), and ignores the dynamic parameter extension functions (such as the correction logic of the safety margin coefficient λ).

[0055] If the version declared by the client is higher than the supported range of the server, 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.

[0056] 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 bottom height of the object is not lower than the ground), and be logically consistent with the length, width, and height dimensions (e.g., the x coordinate of the center of gravity needs to be within the range of [0, length]). Shape parameter verification: Only three enumerated values of cuboid, cylinder, and irregular shape are allowed for the geometric type, and other inputs (such as cone) are automatically mapped to the irregular shape 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.

[0057] Exemplarily, the standardization of the timestamp format includes supporting the client to send timestamps in multiple formats (such as 2025-04-07 15:00:05, 20250407T150005+0800, Unix timestamp 1680855605), and uniformly converting them to the ISO8601 standard format (including the time zone, such as 2025-04-07T15:00:05+08:00) during parsing.

[0058] 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).

[0059] Exemplarily, the origin transformation of coordinates means defining a globally unified coordinate system origin (such as the logistics warehouse entrance is (0, 0, 0)), the Z axis is perpendicular upward (unit: meter), the X axis points to the warehouse length direction, and the Y axis points to the width direction. If the client sends local coordinate system coordinates (such as the origin of a certain storage area is (100, 50, 0)), the coordinate system offset parameters (such as offset_x = 100, offset_y = 50, offset_z = 0) are attached in the request body, and the server converts according to the formula global coordinate = local coordinate + offset; if the offset is not declared, it is default processed 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 (such as "The target position coordinates cannot be negative") is returned.

[0060] In S4. Conduct a stability assessment of the handled object according to the user's request, and output a control command based on the stability assessment: Specifically, after obtaining the request of a user who requests to use an electric forklift truck, a stability assessment of the object to be carried is performed according to the user's request. The stability assessment of the object to be carried 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 forklift truck (spacing between loading devices, traveling speed), and the constraint parameters (maximum tilting angle). Through the coupling calculation of multi-dimensional parameters, a dynamic assessment of the tipping risk is realized.

[0061] Specifically, the calculation of the tipping risk coefficient includes the steps: 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 loading device are (x c , y c , z c ), and the center of gravity offset of the object in the horizontal direction along the x-axis is: ; The center of gravity offset of the object in the horizontal direction along the y-axis is: ; The offset distance d offset of the object is: ; Define the width of the adjusted support surface of the forklift truck's loading device along the x-axis as W, and the length of the adjusted support surface of the forklift truck's loading device along the y-axis as L. Then the half-width and half-length of the adjusted support surface of the forklift truck's loading device are W / 2 and L / 2 respectively.

[0062] When the geometric type of the object is a cuboid or a cylinder, the support surface range is jointly determined by the spacing between the loading devices and the bottom surface size of the object; for an irregular object, the support surface range is determined by the minimum stable support surface width W min and length L min defined by the user.

[0063] Define the real-time tilting angle of the forklift truck as θ (the inclination angle around the x-axis or y-axis), and the center of gravity height h g , where h g = z g - z c . Then the calculation formula for the increment d θ of the center of gravity horizontal offset caused by tilting is: d θ = h g × sinθ; 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 for the tipping risk coefficient K is: ; The physical meaning of the tipping risk coefficient K: When K < 1, the centroid projection is within the support surface, and the handling state is stable; when K ≥ 1, the centroid projection exceeds the edge of the support surface, there is a risk of tipping over, and the greater the value of K, the higher the risk.

[0064] The constraint parameters are corrected, and the correction of the constraint parameters is based on the maximum tilt angle θ defined for the object max and the width W of the support surface req , the length L of the support surface req is corrected. A safety margin coefficient λ (0 < λ < 1) is introduced. If λ is preset, the actual allowable maximum offset distance d max is: d max = λ × min(W req / 2, L req / 2), and then the risk coefficient is corrected to: ; The object feature parameters (centroid coordinates, geometric type, constraint parameters) and the real-time state of the handling vehicle (spacing between cargo-carrying devices, tilt angle, speed) are obtained from the API interface, and the tipping risk coefficient K is calculated to determine the tipping risk. Preferably, two levels of risk thresholds are preset: The warning threshold K 1 (such as K 1 = 0.8), the emergency threshold K 2 (such as K 2 = 0.95).

[0065] Before outputting the command, the risk coefficient is judged: If K ≥ K 1 , then the spacing between the cargo-carrying devices is expanded according to the geometric type of the object. The adjustment formula for the spacing between the cargo-carrying devices is: , .

[0066] Among them, △w is a constant, W max is the maximum adjustable width of the cargo-carrying device, W old is the width of the cargo-carrying device before expansion, and W new is the width of the cargo-carrying device after expansion. By increasing W new , the support surface is enlarged and the value of K is reduced.

[0067] When K ≥ K2, the traveling speed is also adjusted. The speed adjustment formula is: ; In the formula, v new is the adjusted speed, and v old is the speed before adjustment; the speed decreases linearly with the increase of the risk coefficient, reducing the influence of inertial force on the centroid offset.

[0068] If the detected tilt angle is greater than half of the maximum tilt angle, an inclination adjustment command for the cargo handling device is output to reverse-compensate the tilt angle.

[0069] This application generates commands for adjusting the spacing, speed, and attitude of the cargo handling device according to the tipping risk coefficient K, and outputs the adjustment commands.

[0070] In S5. Obtain the 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 a certain number of users in the recent period: In the "cargo handling device adaptation parameters", for the geometric type of "cuboid", an "optional list" is correspondingly set, and at least the option of "parallel cargo handling device" is included in the "optional list".

[0071] Specifically, count the proportion of users who choose to grab with a parallel cargo handling device when handling a cuboid in the recent requests. If more than 80% of the users choose to grab with a parallel cargo handling device when handling a cuboid, the default tool for the cuboid in the "cargo handling device adaptation parameters" is forcibly set to a parallel cargo handling device to reduce invalid parameter verification.

[0072] Exemplarily, such as Figure 2 , select the valid handling requests within the recent 30 days (or a cumulative total of 1000 similar requests, whichever is reached first) as the statistical period to ensure that the data covers high-frequency scenarios and has real-time performance. Only include requests with the shape parameter marked as "cuboid" and the cargo handling device actively specified by the user to ensure that the statistical results reflect the true preferences of the users. During the statistical period, the proportion of the number of cuboid handling requests where the user selects a "parallel cargo handling device" to the total number of requests of this type, when this proportion is ≥80% for 3 consecutive statistics (with a 24-hour interval each time), trigger the forced update of the default tool to avoid interference from short-term accidental data to the strategy stability. In the "cargo handling device adaptation parameters", adjust the default cargo handling device corresponding to the geometric type of "cuboid" from the "optional list" to a "parallel cargo handling device", so that the system preferentially calls the adaptation parameters of this tool. For all subsequent requests with the shape parameter of "cuboid", skip the cargo handling device type verification link automatically and directly match the standard parameters of the parallel cargo handling device, reducing the invalid verification steps during interface data parsing and improving the request response efficiency.

[0073] For the geometric type of "cylinder" in the "cargo handling device adaptation parameters", a "wrapping angle - weight" mapping table is correspondingly configured to generate control instructions for the arc-shaped fixture according to the weight of the cylinder, and the control instructions include the wrapping angle.

[0074] Specifically, count the distribution of the wrapping angles of the arc-shaped fixtures in the recent cylinder handling requests in the recent requests, stratify by load weight (such as an average wrapping angle of 135° when ≤25 tons and 160° when >25 tons), generate a "wrapping angle - weight" mapping table, and update the "cargo handling device adaptation parameters" of the API interface.

[0075] Exemplarily, such as Figure 3 , Package Angle Acquisition: Each request records the actual configured package angle (unit: degree) of the user. This angle needs to meet the physical constraints of the arc-shaped fixture (such as a minimum of 120° and a maximum of 180°). Out-of-range outliers (such as 110° or 190°) are automatically marked as invalid and excluded. The median of the valid package angles within each weight range is taken (for example: 135° for the light load range, 150° for the medium load range, 165° for 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 package angle". The example is as follows: weight ≤ 20 tons → 135°; 20 tons < weight ≤ 25 tons → 150°; weight > 25 tons → 170°; When a cylinder handling request is received, the object weight is automatically read, and the "package angle - weight" mapping table is matched to generate a control instruction for the arc-shaped fixture.

[0076] The "Speed and Attitude Adjustment Parameters" sets scenario-specific configuration items, which are at least used to adjust the tilt angle threshold in different scenarios.

[0077] Specifically, in the statistical port container transportation scenario, the tilt angle threshold adjustment data when the user faces a slope section (such as on average reducing the default 15° to 12°) is statistically analyzed to generate an association rule and update the speed and attitude adjustment parameters of the API interface.

[0078] Exemplarily, for the slope section in port container transportation, this scenario is sensitive to the tilt 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 the user has actively adjusted the tilt angle threshold (such as the user manually modifying the default 15° to 12° in the port system to avoid the system automatically ignoring invalid default values); Use a sliding window to select valid requests within the last 30 days (accumulative ≥ 200 requests of the same type of scenario) to ensure that the data covers high-frequency operation periods and reflects seasonal changes (such as users tending to lower thresholds when the port slope is slippery during the rainy season). Record the original default threshold θ_default (system preset 15°), the user-adjusted threshold θ_user (such as 12°, 10°) of each request, and the slope gradient α (real-time collected by the vehicle-mounted slope sensor, unit: °); The association rule generation adopts a triple of "scenario label - slope grade - recommended threshold". The example is as follows: 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 rule 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.

[0079] The "speed and attitude adjustment parameters" are at least configured with an initial speed limit to clarify the safety speed limit of the forklift truck.

[0080] Specifically, analyze the relationship between the load weight and the user-set speed in the scenario of transporting factory molds (for example, the average speed is 4 km / h when the load is 30 tons, and 6 km / h when the load is 20 tons), establish a "weight-speed" dynamic mapping, and automatically adjust the initial speed limit in the "speed and attitude adjustment parameters".

[0081] Exemplarily, based on the valid requests in the past 30 days, eliminate the request data with speed settings exceeding the safety speed limit of the forklift truck (such as 10 km / h when the forklift is unloaded) or with a tipping risk coefficient K≥0.8 to avoid interference of extreme operations on the model. Divide the molds into 3 core weight ranges and match different speed limit rules. For example, in the light load range (≤20 tons): the default initial speed is 6 km / h, and the user is allowed to adjust the speed within the range of 4 - 8 km / h to meet the efficient handling requirements of smaller molds. In the medium load range (20 tons - 30 tons): based on historical data (such as the average speed is 5 km / h when the load is 25 tons), set the initial speed to 5 km / h, and the speed adjustment step is 0.5 km / h to avoid frequent acceleration and deceleration causing the center of gravity to shift. In the heavy load range (>30 tons): the initial speed is forced to be ≤4 km / h (such as the average speed is 3.5 km / h when the load is 35 tons). The "weight-speed" dynamic mapping adopts a linear decreasing model to determine the speed limit.

[0082] It can be understood that the relationship between "evaluating the stability of the transported object according to the user's request and outputting a control command based on the stability evaluation" and "managing the standardized API interface" in this application is as follows: 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 during 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 true value of the management interface.

[0083] The embodiment of the present invention further provides an intelligent electric forklift control system based on a standardized API interface, including: A parameter management module for defining a set of mandatory parameters including the geometric features of the handling object of the electric forklift truck; 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; An interaction module, configured to implement request response by using a standardized API interface. The standardized API interface is at least applied to transmit stability evaluation data of a carried object, and obtain a request from a user who requests to use an electric forklift. An evaluation and control module, configured to perform stability evaluation of a carried object according to the user's request, and output a control command based on the stability evaluation. A parameter update module, configured to obtain requests of a certain number of users in the recent period, and update and optimize dynamic parameters of the standardized API interface according to the requests of the certain number of users in the recent period.

[0084] 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.

[0085] Therefore, it can be understood that the present invention discloses an electronic device, including: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the above-mentioned forestry survey planning design and analysis method based on three-dimensional laser modeling.

[0086] The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A control method for an intelligent electric transport vehicle based on a standardized API interface, characterized in that: Includes steps: Define the mandatory parameter set containing the geometric features of the transport object of the electric transport vehicle; Establish a standardized API interface, configure at least modifiable dynamic parameters for the standardized API interface, the dynamic parameters are established based on the mandatory parameter set, and the standardized API interface is at least used to transmit stability assessment data of the transported object; A standardized API interface is used to implement request responses and obtain requests from users who request to use the electric transport truck; Perform stability assessment of the transported object according to the user's request, and output control commands based on the stability assessment; Get the requests of a certain number of users recently, and update and optimize the dynamic parameters of the standardized API interface based on the requests of a certain number of users recently.

2. According to claim 1, a control method for an intelligent electric transport vehicle based on a standardized API interface is characterized in that: The mandatory parameter set includes basic parameters, shape parameters, and constraint parameters, wherein the basic parameters include the weight, length, width, height, and center of gravity coordinates of the object, the shape parameters are the geometric type of the object, and the shape parameters include a cuboid, a cylinder, and an irregular body, and the constraint parameters include a maximum tilt angle and a support surface width.

3. According to claim 2, a control method for an intelligent electric transport vehicle based on a standardized API interface is characterized in that: Establishing a standardized API interface includes defining core fields for the API interface. The core field definitions include object characteristics, handling instructions, and safety parameters. Object characteristics include mandatory parameter sets, handling instructions are used to specify the starting position, target position, and handling sequence; safety parameters are used to specify the maximum driving speed and maximum load weight limit.

4. According to claim 3, a control method for an intelligent electric transport vehicle based on a standardized API interface is characterized in that: The modifiable dynamic parameters include power output adjustment parameters, path planning optimization parameters, cargo equipment posture adjustment parameters, cargo equipment adaptation parameters, support mode adjustment parameters, and speed and posture adjustment parameters.

5. The intelligent electric transport vehicle control method based on a standardized API interface according to claim 4 is characterized in that: The stability assessment of the transported object according to the user's request specifically includes calculating the overturning risk coefficient K, then determining the stability based on the overturning risk coefficient K, and judging whether the overturning risk coefficient K value is higher than the risk threshold.

6. The intelligent electric transport vehicle control method based on a standardized API interface according to claim 5 is characterized in that: The dynamic parameters of the standardized API interface have been updated and optimized based on recent requests from a certain number of users, including: if the proportion of users choosing to use parallel cargo equipment to grab when transporting rectangular blocks is greater than a threshold, the default tool for the rectangular block in the cargo equipment adaptation parameters will be forcibly set to a parallel cargo equipment.

7. The intelligent electric transport vehicle control method based on a standardized API interface according to claim 6 is characterized in that: Based on recent requests from a certain number of users, the dynamic parameters of the standardized API interface have been updated and optimized, including: load weight stratification based on the parcel angle distribution of the arc clamp in recent cylindrical handling requests, generation of a "parcel angle-weight" mapping table, and updating of the cargo equipment adaptation parameters of the API interface.

8. The intelligent electric transport vehicle control method based on a standardized API interface according to claim 7 is characterized in that: Based on recent requests from a certain number of users, the dynamic parameters of the standardized API interface are updated and optimized, including: counting the tilt angle threshold adjustment data when users face slope sections, generating association rules, and updating the speed and posture adjustment parameters of the API interface.

9. The intelligent electric transport vehicle control method based on a standardized API interface according to claim 8, characterized in that: According to recent requests from a certain number of users, the dynamic parameters of the standardized API interface have been updated and optimized, including: statistical relationship between load weight and user-set speed, establishment of "weight-speed" dynamic mapping, and automatic adjustment of the initial speed upper limit in the speed and posture adjustment parameters.

10. An intelligent electric transport vehicle control system based on a standardized API interface, characterized in that: include: A parameter management module, used to define a set of mandatory parameters including geometric features of an object to be transported by the electric transport vehicle; An API interface module, used to establish a standardized API interface, and configure at least modifiable dynamic parameters for the standardized API interface, where the dynamic parameters are established based on a mandatory parameter set; An interaction module, used to implement a request response using a standardized API interface, the standardized API interface being used at least to transmit stability assessment data of a transported object and obtain a request from a user requesting to use the electric transport vehicle; An evaluation control module, used to evaluate the stability of the transported object according to a user's request and output a control command based on the stability evaluation; The parameter update module is used to obtain the 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 a certain number of users in the recent period.

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