Warehouse management method and device based on forklift positioning and storage medium

Abstract

The invention discloses a warehouse management method and device based on forklift positioning and a storage medium, and belongs to the technical field of warehouse management systems. The method comprises the steps that first identification code information uploaded by a forklift is received, and target goods allocation information corresponding to the first identification code information is determined; obtaining the position of the forklift and the corresponding staying time, forming a moving track of the forklift based on the position of the forklift and the staying time, and extracting a track feature set of the moving track; and based on the track feature set, the deviation degree of the moving track and the target goods allocation information is determined, and when the deviation degree is larger than or equal to a preset deviation degree threshold value, the alarm action of the forklift is triggered. According to the method, the risk that the forklift deviates from the optimal path is recognized in advance through dynamic evaluation of the continuous track characteristics, the alarm is actively triggered when the deviation degree reaches the threshold value, and goods misplacement and operation time waste caused by path deviation are reduced.

Description

Technical Field

[0001] The present application relates to the technical field of warehouse management systems, and in particular to a warehouse management method, equipment, and storage medium based on forklift positioning. Background Art

[0002] Warehouse management based on forklift positioning primarily uses fixed identification codes (such as RFID or QR codes) to achieve location binding and task verification. In related technologies, the forklift scans the location identification code during operation, and the system compares the scanned location with the preset task target location. If the locations match, it is determined to be normal operation; otherwise, an alarm is triggered.

[0003] However, in this scenario, cargo placement verification relies solely on discrete location points (such as starting and ending points), lacking dynamic analysis of the forklift's complete trajectory. When a forklift deviates from the optimal path due to misoperation or detours, the risk of deviation cannot be identified in a timely manner, and an alarm is only triggered after it arrives at the wrong location, resulting in delayed error correction and increased time lost in warehousing operations. Summary of the Invention

[0004] The main purpose of this application is to provide a warehouse management method, equipment and storage medium based on forklift positioning, aiming to solve the technical problem that the verification of cargo placement cannot identify deviation risks in a timely manner, resulting in delayed error correction and increased time loss in cargo warehousing operations.

[0005] To achieve the above objectives, the present application provides a warehouse management method based on forklift positioning, the method comprising the following steps:

[0006] receiving first identification code information uploaded by a forklift, and determining target cargo location information corresponding to the first identification code information;

[0007] Acquiring a forklift position and a corresponding dwell time, forming a movement trajectory of the forklift based on the forklift position and the dwell time, and extracting a trajectory feature set of the movement trajectory;

[0008] Determining a degree of deviation between the movement trajectory and the target cargo location information based on the trajectory feature set;

[0009] When the deviation is greater than or equal to a preset deviation threshold, an alarm action of the forklift is triggered.

[0010] In one embodiment, after the step of receiving the first identification code information uploaded by the forklift and determining the target cargo location information corresponding to the first identification code information, the method further includes:

[0011] Receiving second identification code information acquired and uploaded by the forklift through a vehicle-mounted code scanning device;

[0012] Determining the actual cargo location information corresponding to the second identification code information according to the mapping relationship between the identification code information and the cargo location information;

[0013] Generating a placement verification result of the forklift by comparing the target cargo location information with the actual cargo location information;

[0014] When the verification result is passed, the cargo location status of the cargo location information is updated, or when the verification result is failed, a prompt message indicating abnormal placement is output.

[0015] In one embodiment, the step of determining the deviation between the movement trajectory and the target cargo location information based on the trajectory feature set includes:

[0016] Generate a preset number of reference paths based on the forklift position and the cargo location information;

[0017] The deviation between the movement trajectory and the reference path is calculated according to the trajectory feature set.

[0018] In one embodiment, the step of calculating the deviation between the movement trajectory and the reference path according to the trajectory feature set includes:

[0019] Obtaining the movement trajectory and the reference path through an intelligent agent module, and determining indicator information of different dimensions in the trajectory feature set;

[0020] Calculate the similarity between the indicator information and the feature information of the corresponding dimension of the reference path to obtain the indicator similarity;

[0021] According to preset weight values, a weighted sum calculation is performed on the indicator similarities of different dimensions to obtain the deviation between the movement trajectory and the reference path.

[0022] In one embodiment, the step of generating a preset number of reference routes based on the forklift position and the cargo location information includes:

[0023] Generate a cargo location planning path with the forklift position as the starting point and the cargo location corresponding to the cargo location information as the end point;

[0024] Obtaining a warehouse map and real-time map information, determining path segments of the cargo location planning path in the warehouse map, and resistance coefficients corresponding to the path segments based on the real-time map information;

[0025] Based on the path segmentation, performing a weighted sum calculation on the resistance coefficient, and generating a path score for the cargo location planning path according to the calculation result and the cargo location planning path;

[0026] A preset number of reference paths are selected from the cargo location planning paths according to the path scores, and the reference paths are output to a display terminal of the forklift.

[0027] In one embodiment, the steps of obtaining a forklift position and a corresponding dwell time, forming a movement trajectory of the forklift based on the forklift position and the dwell time, and extracting a trajectory feature set of the movement trajectory include:

[0028] Receiving forklift positioning information uploaded by the indoor positioning device and determining time information of the forklift positioning information;

[0029] Mapping the positioning information to a warehouse map to determine the location of the forklift;

[0030] sorting the forklift positions based on the time information, and connecting the forklift positions according to the sorting result to form the movement trajectory of the forklift;

[0031] The feature information of the movement trajectory is extracted through time series analysis to obtain the trajectory feature set.

[0032] In one embodiment, the step of extracting feature information of the movement trajectory through time series analysis to obtain the trajectory feature set includes:

[0033] Determining speed information and / or dwell time of the forklift at the forklift position in the movement trajectory;

[0034] Extracting the instantaneous speed vector and the heading deflection angle corresponding to the forklift position in the speed information, and constructing the dwell time distribution information of the movement trajectory according to the dwell time;

[0035] generating a path curvature feature based on the heading deflection angle, and generating a speed fluctuation feature based on the instantaneous speed vector and the dwell time distribution information;

[0036] The path curvature feature and the speed fluctuation feature are integrated to obtain the trajectory feature set.

[0037] In one embodiment, the step of receiving the first identification code information uploaded by the forklift and determining the target cargo location information corresponding to the first identification code information includes:

[0038] Receiving the first identification code information acquired and uploaded by the forklift through the vehicle-mounted code scanning device;

[0039] Obtain identification information by identifying the first identification code information, and obtain pallet information and cargo information corresponding to the identification information from a database;

[0040] In the cargo location interval corresponding to the cargo information, a target cargo location corresponding to the pallet information is selected, and the target cargo location information of the target cargo location is obtained.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a warehouse management device based on forklift positioning, the device including: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the warehouse management method based on forklift positioning as described above.

[0042] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the warehouse management method based on forklift positioning as described above are implemented.

[0043] One or more technical solutions proposed in this application have at least the following technical effects:

[0044] This application constructs the forklift's movement trajectory and extracts the trajectory feature set based on the forklift's position and dwell time. By analyzing the deviation between the trajectory features and the target cargo location information, the application monitors in real time whether the forklift's path conforms to the preset logic during its travel. Through dynamic evaluation of continuous trajectory features, the application identifies in advance the risk of the forklift deviating from the optimal path and actively triggers an alarm when the deviation reaches a threshold, thereby reducing the misplacement of goods and waste of operating time due to path deviation. At the same time, this application deploys on-board barcode scanning equipment on forklifts and indoor positioning equipment to collect data and upload it to the warehouse management system, thus realizing an automated warehouse management system, effectively reducing the transformation cost and operation and maintenance cost of warehouse automation management. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 This is a flow chart of the first embodiment of the warehouse management method based on forklift positioning of the present application;

[0048] Figure 2 This is a flow chart of a second embodiment of the warehouse management method based on forklift positioning of the present application;

[0049] Figure 3 It is a structural diagram of a warehouse management device based on forklift positioning in the hardware operating environment involved in the embodiment of the present application.

[0050] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0052] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0053] The main solution of the embodiment of the present application is: receiving first identification code information uploaded by a forklift, and determining the target cargo location information corresponding to the first identification code information; obtaining the forklift position and the corresponding residence time, forming the movement trajectory of the forklift based on the forklift position and the residence time, and extracting the trajectory feature set of the movement trajectory; based on the trajectory feature set, determining the deviation between the movement trajectory and the target cargo location information, and triggering the alarm action of the forklift when the deviation is greater than or equal to a preset deviation threshold.

[0054] In the existing technology, when a forklift is operating, it scans the cargo location identification code. The system compares the scanned location with the preset task target cargo location. If the locations match, it is determined to be normal operation, otherwise an alarm is triggered. However, in this case, the verification of cargo placement only relies on the verification of discrete location points (such as the starting point and the end point), and lacks dynamic analysis of the complete movement trajectory of the forklift. When the forklift deviates from the optimal path due to misoperation or detour, it is unable to identify the deviation risk in time, and the alarm can only be triggered after arriving at the wrong cargo location, resulting in a delay in error correction and increased loss of cargo warehousing operation time.

[0055] This application constructs the forklift's movement trajectory and extracts the trajectory feature set based on the forklift's position and dwell time. By analyzing the deviation between the trajectory features and the target cargo location information, the application monitors in real time whether the forklift's path conforms to the preset logic during its travel. Through dynamic evaluation of continuous trajectory features, the application identifies in advance the risk of the forklift deviating from the optimal path and actively triggers an alarm when the deviation reaches a threshold, thereby reducing the misplacement of goods and waste of operating time due to path deviation. At the same time, this application deploys on-board barcode scanning equipment on forklifts and indoor positioning equipment to collect data and upload it to the warehouse management system, thus realizing an automated warehouse management system, effectively reducing the transformation cost and operation and maintenance cost of warehouse automation management.

[0056] To better understand the above technical solutions, exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0057] It should be noted that the execution entity of this embodiment can be a warehouse management system, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device capable of performing the above functions, or a warehouse management device based on forklift positioning, etc. This embodiment does not specifically limit this. The following uses a warehouse management system as an example to illustrate this embodiment and the following embodiments.

[0058] Based on this, the embodiment of the present application provides a warehouse management method based on forklift positioning, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the warehouse management method based on forklift positioning of the present application.

[0059] In this embodiment, the warehouse management method based on forklift positioning includes steps S10 to S40:

[0060] Step S10: receiving the first identification code information uploaded by the forklift, and determining the target cargo location information corresponding to the first identification code information;

[0061] In this embodiment, the first identification code information is used to identify the coded information of the goods or pallet, such as a QR code or barcode. A forklift is used to enter goods into the warehouse, loading the goods or pallets with goods at the warehouse entrance and transporting the goods or pallets to the storage location corresponding to the target goods information. A code scanning device or information collection module on the forklift obtains the first identification code information on the pallet or goods, such as by scanning the QR code or barcode or reading the electronic tag, and converts the coded information into a string of digital or character data.

[0062] In one embodiment, the string data corresponding to the first identification code information includes the target storage location information of the pallet or the goods. The forklift's communication module uploads the acquired first identification code information to the warehouse management system. Upon receipt, the system parses the target storage location information corresponding to the identification code based on preset encoding rules and mapping relationships in the database. This involves querying and matching multiple database tables to obtain accurate storage location data.

[0063] In another embodiment, the warehouse management system can assign a storage location to the pallet or the cargo based on the string data corresponding to the first identification code information and determine the corresponding target storage location information. The warehouse management system receives the first identification code information acquired and uploaded by the forklift via the onboard code scanning device, recognizes the first identification code information, obtains the identification information, and retrieves the pallet information and cargo information corresponding to the identification information from the database. The warehouse management system selects the target storage location corresponding to the pallet information within the storage location range corresponding to the cargo information and obtains the target storage location information for the target storage location.

[0064] For example, the warehouse management system can determine the corresponding storage location range based on the cargo information's attributes, such as the category and storage requirements, or directly obtain the pre-assigned storage location range corresponding to the cargo information. Within this range, the warehouse management system uses a storage location allocation algorithm to select a suitable target storage location based on pallet information (such as pallet size and load capacity) and the warehouse's storage strategy (such as first-in-first-out and nearest storage). For example, the target storage location is selected as the vacant storage location closest to the forklift's current position and that meets the cargo storage requirements. The system then obtains the location's detailed location information, such as its coordinates (x, y, z), shelf number, and number of shelves.

[0065] Step S20: obtaining a forklift position and a corresponding dwell time, forming a movement trajectory of the forklift based on the forklift position and the dwell time, and extracting a trajectory feature set of the movement trajectory;

[0066] In this embodiment, the forklift location refers to the real-time physical location of the forklift in the warehouse, typically determined through indoor positioning technology, such as positioning systems based on Wireless Fidelity (Wi-Fi), Bluetooth, Ultra WideBand (UWB), or Radio Frequency Identification (RFID). Dwell time refers to the length of time the forklift remains at a particular location and can be used to analyze the forklift's operating status. The movement trajectory is the path of the forklift's position changes over a period of time. The trajectory feature set is a set of parameters obtained by feature extraction of the movement trajectory, which is used to describe key features of the trajectory, such as shape, speed, and direction.

[0067] As an optional implementation for extracting trajectory feature sets, the warehouse management system can extract trajectory feature sets based on time series analysis. The warehouse management system receives forklift positioning information uploaded by indoor positioning devices and simultaneously determines the time information associated with the forklift positioning information. By mapping this positioning information onto a warehouse map, the forklift's location is determined. Based on the time information, the forklift locations are sorted and connected to form a forklift movement trajectory. Furthermore, the warehouse management system extracts feature information from the movement trajectory through time series analysis to obtain a trajectory feature set.

[0068] Exemplarily, the warehouse management system determines the speed information and / or dwell time of a forklift at a forklift position within the movement trajectory, extracts the instantaneous speed vector and heading deflection angle corresponding to the forklift position from the speed information, and constructs dwell time distribution information for the movement trajectory based on the dwell time. The warehouse management system generates a path curvature feature based on the heading deflection angle, combined with information such as the movement trajectory and the instantaneous speed vector, and generates a speed fluctuation feature for the movement trajectory based on the instantaneous speed vector and the dwell time distribution information. By integrating the path curvature feature and the speed fluctuation feature, a trajectory feature set is obtained.

[0069] Alternatively, the warehouse management system can obtain the forklift's real-time location information, including coordinates (x, y, z), from positioning devices installed in the warehouse (such as Wi-Fi access points and Bluetooth beacons), and record the corresponding timestamps. This information is then arranged in chronological order to form a forklift position sequence. Interpolation and other algorithms are then used to fill in any missing data and generate a complete movement trajectory.

[0070] Optionally, the warehouse management system can be based on the fusion of multi-source positioning technology, combined with UWB, Bluetooth AoA / AoD (angle of arrival / angle of departure), laser SLAM (simultaneous localization and mapping) or vision-assisted positioning technologies to significantly improve indoor positioning accuracy, such as in high-shelf areas or signal-blocked areas.

[0071] Step S30: determining the deviation between the moving trajectory and the target cargo location information based on the trajectory feature set;

[0072] Step S40: When the deviation is greater than or equal to a preset deviation threshold, triggering an alarm action.

[0073] In this embodiment, the deviation is an indicator that measures the degree of difference between the actual moving trajectory of the forklift and the ideal path of the target cargo location, and is usually calculated using methods such as distance, direction deviation or similarity. The preset deviation threshold is a pre-set judgment standard used to determine when to trigger an alarm action. The warehouse management system compares the parameters in the trajectory feature set with the pre-set ideal path of the target cargo location, calculates indicators such as the distance deviation and direction deviation between the two, and comprehensively obtains the deviation. The calculated deviation is compared with the preset deviation threshold. If the deviation is greater than or equal to the threshold, it means that there is a large deviation between the actual driving path of the forklift and the expected target, which may affect the accurate storage or removal of the goods. At this time, the forklift's alarm action is triggered, such as emitting an audible and visual alarm signal, sending an alarm message to the operator terminal, etc.

[0074] Specifically, step S30 includes steps S31 to S32:

[0075] Step S31: generating a preset number of reference routes based on the forklift position and the cargo location information;

[0076] In this embodiment, the reference path is a number of possible driving routes generated by a path planning algorithm based on the current position of the forklift and the target cargo location. The path planning algorithm is a calculation method for finding the optimal path from the starting point to the end point, such as the A* algorithm, the Dijkstra algorithm, etc., which comprehensively considers factors such as the path length and the resistance coefficient to generate the optimal path. The system first obtains the current position coordinates of the forklift and the position coordinates of the target cargo location. Then, the path planning algorithm is called to search for possible paths on the warehouse map with the forklift position as the starting point and the cargo location as the end point. According to the preset number of paths, such as generating 3 reference paths, the algorithm will comprehensively consider factors such as the straight-line distance of the path, the number of turns, the congestion level of the passing area, etc., to generate multiple different reference paths and record the node coordinate sequence of each path.

[0077] Exemplarily, the warehouse management system uses the forklift position as the starting point and the cargo location corresponding to the cargo location information as the end point to generate a cargo location planning path, obtain the warehouse map and real-time map information, determine the path segments of the cargo location planning path in the warehouse map, and the resistance coefficient corresponding to the path segment based on the real-time map information. Specifically, the real-time map information also includes the positioning information and reference paths of other forklifts. The warehouse management system can adjust the resistance coefficients of different locations in the warehouse map based on the positioning information and reference paths. Based on the path segmentation, the resistance coefficients are weighted and summed, and a path score for the cargo location planning path is generated based on the calculation results and the cargo location planning path. Based on the path score, a preset number of reference paths are selected from the cargo location planning path, and the reference path is output to the display terminal of the forklift.

[0078] Optionally, the warehouse management system can also use environmental perception and dynamic calibration, using forklift sensors (IMU inertial measurement unit) or environmental beacons for dynamic calibration. Build a digital map of the warehouse and map the forklift position to the map coordinate system in real time to improve the availability of location information. At the same time, the warehouse management system can dynamically adjust the threshold based on the scenario according to the information obtained by the forklift. Among them, the preset deviation threshold may not be suitable for all areas, such as narrow aisles or spacious loading and unloading areas. The system dynamically adjusts the threshold based on the map attributes (aisle width, shelf density) or historical data of the area where the forklift is located to reduce false alarms caused by environmental interference.

[0079] Step S32: Calculate the deviation between the moving trajectory and the reference path based on the trajectory feature set, and trigger the alarm action of the forklift when there is no reference path with the deviation less than the preset threshold.

[0080] In this embodiment, the trajectory feature set is a collection of characteristic parameters of the movement trajectory, used to describe key features of the trajectory, such as shape, speed, and direction. Deviation is a metric that measures the difference between the actual movement trajectory and the reference path. It can be calculated based on distance deviation, direction deviation, or similarity between path points. The preset threshold is a pre-set standard value used to determine whether the trajectory deviates too much.

[0081] Specifically, the warehouse management system compares the actual movement trajectory of the forklift with multiple generated reference paths. For each reference path, its key node coordinates and direction information are extracted and calculated with the corresponding features of the actual trajectory. The deviation between the actual trajectory and the reference path is calculated using methods such as dynamic time warping algorithm or Euclidean distance to obtain the deviation value corresponding to each reference path. These deviation values ​​are then compared with the preset threshold. If the deviation of all reference paths is greater than or equal to the preset threshold, it is determined that the forklift's driving trajectory has seriously deviated from expectations, triggering the forklift's alarm action, such as lighting the warning light on the forklift and sending an alarm prompt to the operator.

[0082] As an optional implementation, a pre-trained agent module is also deployed in the warehouse management system. The agent module can actively obtain the mobile trajectory and reference path, and perform decision-making tasks of deviation calculation and alarm. Among them, after the agent module actively obtains the mobile trajectory and reference path, and determines the indicator information of different dimensions in the trajectory feature set, it calculates the similarity between the indicator information and the feature information of the corresponding dimension of the reference path to obtain the indicator similarity, and performs weighted sum calculation on the indicator similarities of different dimensions according to the preset weight value to obtain the deviation between the mobile trajectory and the reference path. When there is no reference path with a deviation less than a preset threshold, an alarm instruction is sent to the forklift according to the deviation level corresponding to the deviation, so that the forklift performs a graded alarm action.

[0083] It's important to note that an intelligent agent is an agent capable of perceiving its environment and taking actions to achieve specific goals. It possesses autonomy, adaptability, and interaction. By sensing changes in the environment, such as through sensors or data input, the agent makes judgments and decisions based on its learned knowledge and algorithms, and then executes actions to influence the environment or achieve its intended goals. Through learning and iteration, the agent can optimize its own coefficients, such as preset weights and thresholds, to ensure the accuracy of alert results.

[0084] Furthermore, the agent can calculate the reference feature data corresponding to the reference path at different reference path locations based on historical data. For example, the expected path curvature and expected speed characteristics of the reference path at different reference path locations can be determined based on the reference path. The similarity between the expected path curvature and the path curvature characteristics in the trajectory feature set can be calculated, and the similarity between the expected speed characteristics and the speed fluctuation characteristics can be calculated. Alternatively, the instantaneous speed vector, heading deflection angle, dwell time distribution information, and other information can be used as dimensional indicators for similarity calculation.

[0085] In one example, when a forklift approaches a target cargo location, the agent expects the forklift to gradually reduce its speed to place the pallet, and thus reduces the expected speed characteristic of the target reference path position near the target cargo location, and calculates the similarity between the expected speed characteristic and the forklift speed fluctuation characteristic, thereby prompting the forklift to avoid missing the target cargo location.

[0086] In another example, the intelligent agent module first receives the data of the mobile trajectory, including the position, speed, direction and other information of the forklift at each moment. Through the built-in analysis algorithm, the trajectory data is decomposed and the index information of different dimensions is extracted. For example, the speed change rate of each section in the trajectory is calculated as the index of the speed dimension, and the number and angle of the heading change are counted as the index of the heading dimension, etc. The index information extracted from the trajectory feature set is compared with the corresponding dimensional feature information of the reference path. For each dimension, a suitable similarity calculation algorithm is selected. For example, for the speed dimension, the Euclidean distance between the trajectory speed index and the reference path speed feature can be calculated. The smaller the distance, the higher the similarity. For the heading dimension, the cosine similarity of the two can be calculated. The closer the value is to 1, the higher the similarity, thereby obtaining the index similarity of each dimension. According to the pre-set weight value of each dimensional index (for example, the speed dimension weight is 0.4, the heading dimension weight is 0.3, and the curvature dimension weight is 0.3), the similarity of each dimensional index is multiplied by the corresponding weight, and the sum operation is performed to obtain the comprehensive deviation.

[0087] As another optional implementation, the warehouse management system calculates the shortest vertical distance from each point on the actual path to the reference path by parameterizing the reference path into a mathematical equation, and calculates the average, maximum, or root mean square error as the deviation. The actual path and the reference path are time-aligned, the point-to-point matching relationship is optimized through dynamic programming, and the sum or mean of the aligned Euclidean distances is calculated as the deviation. The two paths are regarded as continuous curves, and the area of ​​the enclosed area is calculated by integration or polygonal approximation, and the overall path deviation is measured by the size of the area. The tangent direction angle of each point on the path is extracted, and the angular difference between the corresponding points on the actual path and the reference path is calculated, and the average or maximum angular deviation is calculated as the direction deviation. The two paths are defined as continuous curves, and the minimum and maximum instantaneous distances when they move synchronously are solved to determine the deviation, for example, using the Frechet distance value as a strict measure of path shape similarity.

[0088] Optionally, the warehouse management system is modeled as a graph structure based on the warehouse layout of shelves, aisles, functional areas, etc., wherein the graph structure uses key points in the shelf or warehouse layout as nodes and navigable paths or spatial adjacency relationships as edges. The contextual embedding of the target cargo location and forklift position is learned by using a graph neural network (GNN) to represent the node. Specifically, the discrete positioning points of the forklift are mapped to graph nodes or edges to form the movement trajectory of the forklift, and the graph edit distance or graph similarity of the actual movement trajectory with the reference path or the shortest / optimal path from the starting point to the target cargo location is calculated. Alternatively, the target cargo location embedding representation learned by the GNN is used to calculate the vector distance between the embedding of the forklift's current position node and the embedding of the target node, such as the Euclidean distance and cosine similarity, and the deviation is comprehensively judged in combination with the time context, such as whether the residence time is near the target node. Among them, by explicitly modeling the warehouse space topology constraints, the warehouse management system can understand deviation behaviors such as "taking a detour" and "entering the wrong area".

[0089] The embodiment of the present application constructs the forklift's movement trajectory and extracts a set of trajectory features based on the forklift's position and dwell time. By analyzing the deviation between the trajectory features and the target cargo location information, the embodiment monitors whether the forklift's path conforms to the preset logic in real time during its travel. Thus, through the dynamic evaluation of continuous trajectory features, the risk of the forklift deviating from the optimal path is identified in advance. When the deviation reaches a threshold, an alarm is actively triggered, thereby reducing the misplacement of goods and waste of operation time caused by path deviation. At the same time, the present application deploys on-board scanning equipment on forklifts and indoor positioning equipment to collect data and upload it to the warehouse management system, thereby realizing an automated warehouse management system, effectively reducing the transformation cost and operation and maintenance cost of warehouse automation management.

[0090] Based on the same inventive concept, this application also provides a second embodiment, referring to Figure 2, Figure 2 This is a flow chart of the second embodiment of the warehouse management method based on forklift positioning of the present application.

[0091] In this embodiment, the warehouse management method based on forklift positioning further includes steps S10 to S14:

[0092] Step S10: receiving the first identification code information uploaded by the forklift, and determining the target cargo location information corresponding to the first identification code information;

[0093] Step S11: receiving the second identification code information acquired and uploaded by the forklift through the vehicle-mounted code scanning device;

[0094] Step S12: determining the actual cargo location information corresponding to the second identification code information according to the mapping relationship between the identification code information and the cargo location information;

[0095] Step S13: generating a placement verification result of the forklift by comparing the target cargo location information with the actual cargo location information;

[0096] Step S14: when the verification result is passed, updating the cargo location status of the cargo location information, or, when the verification result is failed, outputting a prompt message indicating abnormal placement.

[0097] In this embodiment, the second identification code information is the cargo location identification information obtained again by the on-board code scanning device after the forklift completes the transportation of the goods to the target cargo location, and is used to verify whether the goods are correctly placed in the target cargo location. The on-board code scanning device is a data acquisition device installed on the forklift, usually equipped with a laser scanner, image sensor, etc., which can quickly and accurately read the identification code on the cargo location. The mapping relationship between the identification code information and the cargo location information is a data association established in advance in the warehouse management system, which is used to quickly determine the cargo location corresponding to the identification code. The actual cargo location information refers to the specific location information of the cargo location where the forklift actually places the goods, including coordinates, number of layers, number, etc.

[0098] Specifically, after a forklift transports the goods to the target storage location, the operator uses the forklift's onboard barcode scanner to scan the identification code on the storage location. The barcode scanner uses a built-in image recognition algorithm or laser reflection principle to convert the scanned identification code into a second identification code in digital or character form. The forklift's communication module then uploads this information to the warehouse management system for subsequent verification. After receiving the second identification code, the warehouse management system queries a pre-established mapping table between identification codes and storage location information in the database. Using a matching algorithm, the system quickly locates the storage location corresponding to the identification code and obtains detailed storage location information, including its physical coordinates, zone, maximum load capacity, and other parameters, thereby determining the actual storage location information. The system compares the target storage location information with the actual storage location information to determine whether they match. If they match, the placement verification result is considered passed, the storage location status of the storage location is updated to "occupied," the occupied flag of the storage location is set to 1 in the database, and data such as the cargo information and the time of entry is recorded. If there is any inconsistency, it will be judged as failed, and the system will generate a placement abnormality prompt message, displaying the text prompt "Wrong placement position" on the display screen on the forklift, triggering the buzzer to sound an alarm, and sending a text message or pop-up reminder to the warehouse manager.

[0099] Optionally, the forklift can guide the operator to put the pallet into storage based on the reference path through its own display terminal.

[0100] The embodiment of the present application ensures that the goods are accurately placed in the target cargo location by performing timely verification after the forklift completes the placement of the goods, thereby improving the accuracy of warehouse management, reducing inventory confusion and subsequent search difficulties caused by incorrect placement of goods, and further improving the efficiency and reliability of warehousing operations.

[0101] Since the system described in Example 2 of this application is the system used to implement the method of Example 1 of this application, those skilled in the art will be able to understand the specific structure and variations of the system based on the method described in Example 1 of this application, and therefore, no further description is given here. All systems used in the method of Example 1 of this application fall within the scope of protection to be provided by this application.

[0102] The present application provides a warehouse management device based on forklift positioning, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the warehouse management method based on forklift positioning in the above-mentioned embodiment one.

[0103] Reference below Figure 3, which shows a schematic diagram of the structure of a warehouse management device based on forklift positioning suitable for implementing the embodiments of the present application. The warehouse management device based on forklift positioning in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 3 The warehouse management device based on forklift positioning shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0104] like Figure 3 As shown, the warehouse management device based on forklift positioning may include a processing device 1001 (e.g., a core processor, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The random access memory 1004 also stores various programs and data required for the operation of the warehouse management device based on forklift positioning. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the forklift-based positioning warehouse management device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a forklift-based positioning warehouse management device with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented or have instead.

[0105] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0106] The forklift positioning-based warehouse management device provided in this application, which utilizes the forklift positioning-based warehouse management method of the aforementioned embodiment, can resolve the technical problem that the verification of goods placement cannot promptly identify deviation risks, resulting in delayed error correction and increased time loss in goods warehousing operations. Compared with the prior art, the beneficial effects of the forklift positioning-based warehouse management device provided in this application are the same as the beneficial effects of the forklift positioning-based warehouse management method provided in the aforementioned embodiment, and the other technical features of the forklift positioning-based warehouse management device are the same as those disclosed in the method of the aforementioned embodiment, and are not further described here.

[0107] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0108] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0109] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer program) stored thereon, and the computer-readable program instructions are used to execute the warehouse management method based on forklift positioning in the above embodiment.

[0110] The computer-readable storage medium provided in this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM, Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM, CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, radio frequency (RF, Radio Frequency), etc., or any suitable combination thereof.

[0111] The computer-readable storage medium may be included in the warehouse management device based on forklift positioning, or may exist independently without being assembled into the warehouse management device based on forklift positioning.

[0112] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the warehouse management device based on forklift positioning, the warehouse management device based on forklift positioning: receives the first identification code information uploaded by the forklift, and determines the target cargo location information corresponding to the first identification code information; obtains the forklift position and the corresponding residence time, forms the movement trajectory of the forklift based on the forklift position and the residence time, and extracts the trajectory feature set of the movement trajectory; determines the deviation between the movement trajectory and the target cargo location information based on the trajectory feature set, and triggers the alarm action of the forklift when the deviation is greater than or equal to the preset deviation threshold.

[0113] The computer program code for performing the operations of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect via the Internet).

[0114] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0115] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0116] The computer-readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned warehouse management method based on forklift positioning. This computer-readable storage medium can address the technical issue of the inability to promptly identify deviation risks during cargo placement verification, leading to delayed error correction and increased time lost during cargo warehousing operations. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the warehouse management method based on forklift positioning provided in the aforementioned embodiments, and are not further elaborated here.

[0117] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A warehouse management method based on forklift positioning, characterized in that: The method comprises the following steps: receiving first identification code information uploaded by a forklift, and determining target cargo location information corresponding to the first identification code information; Acquiring a forklift position and a corresponding dwell time, forming a movement trajectory of the forklift based on the forklift position and the dwell time, and extracting a trajectory feature set of the movement trajectory; Determining a degree of deviation between the movement trajectory and the target cargo location information based on the trajectory feature set; When the deviation is greater than or equal to a preset deviation threshold, an alarm action is triggered.

2. The method according to claim 1, wherein After the step of receiving the first identification code information uploaded by the forklift and determining the target cargo location information corresponding to the first identification code information, the method further includes: Receiving second identification code information acquired and uploaded by the forklift through the vehicle-mounted code scanning device; Determining the actual cargo location information corresponding to the second identification code information according to the mapping relationship between the identification code information and the cargo location information; Generating a placement verification result of the forklift by comparing the target cargo location information with the actual cargo location information; When the verification result is passed, the cargo location status of the cargo location information is updated, or when the verification result is failed, a prompt message indicating abnormal placement is output.

3. The method according to claim 1, wherein The step of determining the deviation between the movement trajectory and the target cargo location information based on the trajectory feature set includes: Generate a preset number of reference paths based on the forklift position and the cargo location information; The deviation between the movement trajectory and the reference path is calculated according to the trajectory feature set.

4. The method according to claim 3, wherein The step of calculating the deviation between the moving trajectory and the reference path according to the trajectory feature set includes: Obtaining the movement trajectory and the reference path through an intelligent agent module, and determining indicator information of different dimensions in the trajectory feature set; Calculate the similarity between the indicator information and the feature information of the corresponding dimension of the reference path to obtain the indicator similarity; According to preset weight values, a weighted sum calculation is performed on the indicator similarities of different dimensions to obtain the deviation between the movement trajectory and the reference path.

5. The method according to claim 3, wherein The step of generating a preset number of reference paths based on the forklift position and the cargo location information includes: Generate a cargo location planning path with the forklift position as the starting point and the cargo location corresponding to the cargo location information as the end point; Obtaining a warehouse map and real-time map information, determining path segments of the cargo location planning path in the warehouse map, and resistance coefficients corresponding to the path segments based on the real-time map information; Based on the path segmentation, performing a weighted sum calculation on the resistance coefficient, and generating a path score for the cargo location planning path according to the calculation result and the cargo location planning path; A preset number of reference paths are selected from the cargo location planning paths according to the path scores, and the reference paths are output to a display terminal of the forklift.

6. The method according to claim 1, wherein The steps of obtaining a forklift position and a corresponding dwell time, forming a movement trajectory of the forklift based on the forklift position and the dwell time, and extracting a trajectory feature set of the movement trajectory include: Receiving forklift positioning information uploaded by the indoor positioning device and determining time information of the forklift positioning information; Mapping the positioning information to a warehouse map to determine the location of the forklift; sorting the forklift positions based on the time information, and connecting the forklift positions according to the sorting result to form the movement trajectory of the forklift; The feature information of the movement trajectory is extracted through time series analysis to obtain the trajectory feature set.

7. The method according to claim 6, wherein The step of extracting characteristic information of the movement trajectory through time series analysis to obtain the trajectory feature set includes: Determining speed information and / or dwell time of the forklift at the forklift position in the movement trajectory; Extracting the instantaneous speed vector and the heading deflection angle corresponding to the forklift position in the speed information, and constructing the dwell time distribution information of the movement trajectory according to the dwell time; generating a path curvature feature based on the heading deflection angle, and generating a speed fluctuation feature based on the instantaneous speed vector and the dwell time distribution information; The path curvature feature and the speed fluctuation feature are integrated to obtain the trajectory feature set.

8. The method according to claim 1, wherein The step of receiving the first identification code information uploaded by the forklift and determining the target cargo location information corresponding to the first identification code information includes: Receiving the first identification code information acquired and uploaded by the forklift through the vehicle-mounted code scanning device; Obtain identification information by identifying the first identification code information, and obtain pallet information and cargo information corresponding to the identification information from a database; In the cargo location interval corresponding to the cargo information, a target cargo location corresponding to the pallet information is selected, and the target cargo location information of the target cargo location is obtained.

9. A warehouse management device based on forklift positioning, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the warehouse management method based on forklift positioning according to any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the warehouse management method based on forklift positioning according to any one of claims 1 to 8 are implemented.

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