319 results about "Stock-taking" patented technology

The invention discloses a storage checking method based on a multi-modal sensing technology, a robot and a storage system, and belongs to the technical field of storage management and intelligent sensing fusion. Multi-modal data such as a visual image, space depth, radio frequency sensing and infrared temperature are collected, and an image feature vector, a three-dimensional point cloud model, a radio frequency response matrix and a temperature map are constructed; generating a fusion recognition vector through a multi-channel fusion network based on an attention mechanism, and dynamically adjusting a modal weight; constructing an article space distribution map, and marking a perception missing region; automatically complementing low-confidence region data based on a priority scheduling algorithm; performing joint verification on the original fusion result and the completion result to form a final inventory list; if the confidence coefficient of a certain article is lower than an early warning threshold continuously for multiple times, triggering an abnormal alarm and generating a traceable sensing sequence; the method is suitable for a high-precision inventory task in a complex storage scene, and has the advantages of high recognition robustness, intelligent completion mechanism, traceable abnormity and the like.

The invention relates to the field of intelligent warehousing, and discloses an intelligent clothing inventory real-time monitoring and automatic checking system based on RFID, which aims at solving the problems of poor environmental adaptability, high dynamic sensing delay, high cross-scene deployment cost and the like in the prior art, and comprises a reconfigurable RFID tag, an integrated spiral-dipole composite antenna and a temperature compensation circuit, dual-band switching of 860 to 960 MHz and self calibration are supported; a heterogeneous read-write network is formed by a fixed reader-writer and AGV mobile nodes, and signal coverage is enhanced through beam forming; the edge calculation module adopts an LSTM trajectory prediction and hybrid filtering algorithm to realize millisecond-level processing; the cloud platform maps the inventory in real time based on the digital twin model and traces the source of the block chain, the dynamic time slot distribution protocol optimizes the cooperation of the reader-writer, and the transfer learning model realizes cross-scene rapid adaptation. According to the invention, the tag reading rate is 99.7%, the inventory efficiency is improved by 300%, the deployment period is shortened by 80%, and the problems of accurate inventory management and dynamic tracking in a complex environment are solved.

The invention discloses a storage intelligent monitoring and checking integrated system and method based on multi-technology fusion, and particularly relates to the technical field of storage monitoring, the system obtains environmental parameters and cargo data in real time through a multi-source data acquisition module, carries out cargo identification and segmentation by using YOLOv7 and Mask R-CNN, and carries out storage monitoring and checking on the cargo. A three-dimensional model is constructed in combination with a Poisson surface reconstruction algorithm to calculate volume weight, an environment anomaly analysis module generates an early warning signal through dynamic threshold and influence level evaluation, and an intelligent decision module fuses data to realize quantity anomaly alarm and multi-level response and outputs a three-dimensional visual inventory report. According to the method, the problems of multiple blind areas, low checking efficiency, slow abnormal response and the like of traditional storage monitoring are solved, full coverage of environment monitoring, high accuracy of goods identification, low error of volume calculation and intelligence of abnormal handling are realized, and the automation and digitization levels of storage management are remarkably improved.

The invention belongs to the technical field of product inventory management, and discloses an e-commerce product inventory management method based on machine vision, which realizes a full-automatic process of product information from acquisition, recognition to statistics by means of a machine vision technology, acquires images in real time from multiple angles by a high-definition industrial camera, inputs the images into a CNN model to extract features after preprocessing, and realizes product inventory management. Through accurate identification classification and quantity statistics, manual intervention of inventory and data entry is not needed; through the automatic inventory management process, the manpower cost expenditure of manual checking, data processing and the like is greatly reduced, and the personnel employment and training cost is reduced. And on the other hand, historical data is deeply mined by using algorithms such as time sequence analysis, the sales trend and the inventory demand are accurately predicted, the replenishment strategy is optimized, capital and storage space occupation caused by inventory overstock is avoided, meanwhile, order loss caused by stockout is prevented, and in addition, a distributed database storage technology ensures data reliability, and the efficiency is improved. And extra cost caused by data errors is reduced.

The invention discloses a mobile rescue intelligent management method based on RFID automatic identification and AI artificial intelligence interaction, and belongs to the field of mobile rescue intelligent management. According to the invention, the problem of low efficiency of medicine and material inventory management of the rescue carriage in an inpatient area due to an existing manual inventory mode is solved, batch accurate identification can be carried out by adopting an RFID remote identification technology, batch inventory is realized to replace one-by-one checking, the inventory efficiency is effectively improved, and the inventory management cost is reduced. Manual electrocardiogram data checking is replaced by image visual recognition of electrocardiogram data, secondary recording is not needed, rescue data can be automatically recorded, rescue efficiency is improved, medical advice recognition is assisted by AI voice instead of manual recording of medical advice, the workload of nurses is reduced, the workload of secondary recording is reduced, and rescue efficiency is improved. And through a rescue scene full-process digital AI closed loop, digital tracing can be completed in the rescue process, and the problems that traditional handwritten records and data are not real-time and inaccurate are solved.

The invention relates to the technical field of warehouse management, and discloses an in-warehouse goods checking method, system and device and computer equipment, and the method comprises the steps: obtaining a tray code on a target checking goods location and the information of a material box on a corresponding tray; identifying the material box information by adopting a deep learning identification algorithm, and determining material specifications; based on the material box information, a preset stacking rule corresponding to the material specification and an AI algorithm, the number of the material boxes on the tray is calculated; and binding the material specifications, the number of the material boxes and the tray codes, and comparing with the upper inventory data based on the tray codes to obtain a cargo inventory result. According to the invention, the tray code and the material box information on the target inventory goods allocation can be directly obtained without continuously moving out the goods at the target inventory goods allocation, the difference between the inventory data and the actual inventory data can be found in time, and the problems of low inventory efficiency and increased inventory time caused by continuously moving out the goods at the target inventory goods allocation are solved.

The invention discloses a physical asset space management method based on three-dimensional point cloud coordinate mapping, and relates to the field of three-dimensional coordinate reconstruction and warehouse management. The method comprises the following steps: performing three-dimensional point cloud modeling on a warehouse space, and constructing a unified coordinate system; collecting three-dimensional point cloud data of goods, generating a unique identifier and binding the unique identifier with a digital model; the digital model of the goods is anchored into a storage coordinate system through a point cloud registration algorithm, and the attitude angle and the spatial position of the goods are calculated; analyzing the geometrical relationship between the goods and the storage positions, and identifying space states such as border crossing, stacking and posture abnormity; and calculating a space utilization rate based on the cargo volume and the storage location volume, and outputting an optimization suggestion. According to the invention, ontology-level coupling management of the goods and the storage space is realized, space deduction type account checking and checking and anomaly detection are supported, and the method is suitable for complex storage scenes such as special-shaped objects and high-density stacking.

The invention discloses a warehouse goods accurate inventory method based on RFID and unmanned aerial vehicle cooperation, and the method comprises the steps: S1, pasting an RFID tag on a warehouse-in goods, binding the warehouse-in goods, and putting the warehouse-in goods on a shelf, and storing the goods inventory information in a warehouse management system; s2, establishing a three-dimensional model and a space coordinate system of the warehouse, wherein each storage location corresponds to a unique three-dimensional space coordinate; s3, the unmanned aerial vehicle executes an inventory task according to a preset route; s4, the unmanned aerial vehicle binds the RFID tag with the strongest signal when hovering in front of each storage location, so that the storage locations are in one-to-one correspondence with the goods; s5, comparing the RFID signal value acquired when the unmanned aerial vehicle flies to the next storage location with the RFID signal value acquired when the unmanned aerial vehicle flies to the previous storage location, and binding the tag with the strongest signal to the current storage location; and S6, after the checking task is finished and the unmanned aerial vehicle returns, the system automatically generates a checking report, compares the RFID real-time data with the WMS inventory record and marks a difference item. According to the invention, efficient and accurate unmanned inventory checking can be realized, and the inventory quantity and inventory position accuracy of inventory checking can be ensured.

The invention discloses a warehouse cargo management method and device, equipment, a medium and a program product. The method comprises the following steps: generating a checking path according to the position of a to-be-checked target shelf in a warehouse checking task; aGV equipment is controlled to run to the position of the target goods shelf according to the checking path; identifying the label information of the first label of the target goods shelf through an RFID checking device, and querying the layer height of each goods shelf layer plate of the target goods shelf according to a preset mapping relationship between the label information and the goods shelf information; a lifting control instruction is generated according to the layer height of the goods shelf layer plates, so that a lifting device on the AGV equipment is controlled to lift the RFID checking device to each goods shelf layer plate; and identifying the label information of the second label corresponding to the goods on the goods shelf laminate through the RFID checking device. According to the invention, the method can meet the requirements of goods checking of multiple layers of goods shelves in a warehouse, and improves the storage and logistics management efficiency.

The invention provides an intelligent archive management method and system, and relates to the technical field of archive management, and the method comprises the steps: building an archive location information map, initializing an archive location database, and configuring an equipment communication protocol; after the operation end passes through the warehousing face entrance guard, the to-be-shelved archives are placed in a warehousing temporary storage area; matching a racking position according to the RFID tag and generating an instruction; scheduling a file taking and returning robot to execute a shelving task; the operation end inputs a file taking query instruction through the intelligent interaction terminal and then determines a file to be taken off, the file taking-off position is matched according to the RFID tag, and an instruction is generated; scheduling the file taking and returning robot to execute the off-shelf task; after the operation end passes through the warehouse-out face entrance guard, the files are taken away from the warehouse-out handover area; and according to the archive checking instruction, the robot is scheduled to carry out scanning and identification, a storage position record is generated, a database is updated, and a checking report is generated, so that the archive access efficiency is remarkably improved, and the accuracy, safety and intelligent level of archive management are ensured.

The invention relates to the technical field of warehouse management, in particular to a warehouse management system for a logistics supply chain and a management method thereof, and the system comprises a batch checking adjustment module, a goods shelf space monitoring module, an order circulation discrimination module, a load space matching module and a vehicle scheduling sorting module. According to the invention, through continuous dynamic analysis of validity period and batch data, real-time optimization and adjustment of an inventory cycle are realized, shelf spaces and order flows are cooperatively monitored, inventory circulation bottlenecks are rapidly positioned, and in combination with order timeliness and warehouse partition circulation data, potential abnormal shelves are automatically identified and labeled, and transportation resources and cargo characteristics are overlapped for matching and allocation. Intelligent sorting is carried out between vehicle in-place and task assignment, multi-link self-adaptive linkage is achieved, the response speed and task connection efficiency of the whole process are improved, the multi-scene management adaptability of data driving is enhanced, and the concurrence situation of high-frequency fluctuation and multiple types of tasks is effectively dealt with.

The invention provides an elevated warehouse cargo visual identification checking method and related equipment, and the method comprises the steps: obtaining a cargo box region image, carrying out the gray transformation and noise reduction, obtaining a label local information image sequence, recognizing the focus blurring and light refraction caused by projection angle deviation and distance error, and generating a cargo box label image set; determining a texture feature set according to the texture details, analyzing character strokes and pattern distribution according to the texture feature set, and forming a label local feature description set; performing feature comparison on the label local feature description set and a label template database to obtain a feature matching degree, and if the feature matching degree exceeds a preset threshold value, performing feature weight adjustment according to projection light refraction to determine a candidate label matching list; generating a final label candidate set according to the candidate label matching list, and determining complete contents of labels; a mapping relation is established according to the complete content of the label, an inventory checking result is determined, and the inventory identification accuracy is improved; the method can be applied to the technical field of information.

The invention relates to an RFID-based fixed asset physical management method and system, and the method comprises the steps: firstly obtaining the signal intensity data and positioning data of an RFID tag corresponding to a fixed asset in a use state at a plurality of historical inventory time points, and then carrying out the data sample screening through the signal intensity data and positioning data at the plurality of historical inventory time points; and signal abnormal time points caused by external signal interference are removed. Then, the inertial dynamic feature of each RFID is constructed through accurate positioning, so that whether each RFID tag has the inertial dynamic feature or not is found out, and the inertial dynamic features are extracted; meanwhile, the synchronous use features among different RFID tags are found by utilizing accurate positioning, so that the synchronous inertia atlas is constructed. And performing early warning management and inventory management on the dynamic characteristics of the RFID tags under various conditions by using the inertia dynamic characteristics and the synchronous inertia atlas. The method is more flexible and fits the use habit of the fixed assets in the use state.

The invention belongs to the technical field of commercial inventory management, and discloses a store inventory commodity management and search system based on RFID induction, and the system comprises the steps: collecting a phase change time sequence of candidate RFID tags at high frequency when a user executes a moving operation; before matching, analyzing actual motion characteristics of a user according to instantaneous frequency of a sequence, and performing dynamic normalization processing on a time axis; and when a plurality of targets exist in a matching result, further performing coded modulation on the transmitting power of the reader and analyzing the relevance of echo response to finish the final uniqueness arbitration. A traditional mode of probabilistic judgment depending on signal instantaneous quantity is converted into a deterministic inventory management process based on dynamic process feature confirmation, so that the problem of uncertainty of inventory searching and checking caused by commodity density and signal instability in a commercial environment is solved.

The invention provides a stereoscopic warehouse stacked goods checking method based on improved YOLO11-Seg. The stereoscopic warehouse stacked goods checking method comprises the steps of collecting goods images and performing labeling processing on the goods images; the method comprises the following steps: constructing an improved YOLO11-Seg model; carrying out segmentation identification on the cargo image by utilizing the trained improved YOLO11-Seg model; judging whether the condition is legal or not according to the segmentation mask and the mask category information; according to the geometric relationship of the convex hull points, judging whether the cargo top layer is in a full load condition, and if the cargo top layer is in the full load condition, directly calculating the cargo quantity; otherwise, calculating the number of the sub-top-layer boxes according to an estimation algorithm, and then calculating the total number of the cargo boxes. According to the method, the identification of stacked goods is realized by utilizing an improved YOLO11-Seg model, a goods segmentation mask and a mask type are generated, and the total goods quantity is calculated by identifying and distinguishing different layers of goods boxes; the method has the advantages of high generalization, low deployment cost, high checking efficiency and the like.

The invention provides an artificial intelligence-based polar region unmanned warehouse cargo identification and inventory method and system, and relates to the field of artificial intelligence and computer vision, and the identification and inventory method specifically comprises the steps that at least one unmanned vehicle carries out the data collection of cargos in an unloading area, obtaining video data and point cloud data of the goods; at least one unmanned aerial vehicle serves as a data relay, and video data and point cloud data collected by the unmanned aerial vehicle are transmitted to a cloud system; performing multi-modal fusion based on the pure cargo surface point cloud and the features of the video data to realize cargo instance segmentation, and identifying the content category of each cargo instance in combination with the image information in the region of interest; generating a three-dimensional digital map of the unloading area; and based on the three-dimensional digital map, performing multi-dimensional dynamic warehousing planning to generate a dynamic task queue for transporting goods from the unloading area to the unmanned storage room.

The invention relates to the technical field of retail management, in particular to a retail end online management method and system based on concurrency control, and the method comprises the steps: constructing a retail knowledge graph based on historical transaction logs through employing a space-time interaction entropy weighting algorithm; calculating a local topology edge density increment by applying a streaming dense subgraph increment mining algorithm, and determining a topology aggregation state of a target node; if the state is the mixed concurrent state, constructing an inventory time slice mirror image containing a reference inventory domain and a dynamic increment domain; and writing the request into the lock-free annular buffer during checking, and merging data by adopting a time sequence alignment algorithm after checking to carry out atomized updating. According to the method, static inventory and dynamic sales are physically isolated by constructing the inventory time slice mirroring and lock-free buffer mechanism, the read-write conflict in the scene of inventory while sales is solved, and zero-blocking hybrid concurrence is realized while the final consistency of inventory data is guaranteed.

The invention provides an independent visual checking device, method and system for a stereoscopic warehouse, and belongs to the technical field of automatic warehousing. The independent visual checking device comprises a device main body with a tray type base, a multi-dimensional movement mechanism (comprising a horizontal sliding mechanism and a lifting mechanism) arranged on the main body, a visual assembly mounted on the multi-dimensional movement mechanism, and a local controller configured in the main body. The method is executed by a local controller and comprises the following steps: receiving an inventory instruction of an upper system; the multi-dimensional movement mechanism is autonomously controlled to adjust the pose of the visual assembly and collect images; carrying out localized analysis on the image to obtain an inventory result; and a result is reported. By endowing the visual component with the two-dimensional plane movement capability, the method can actively avoid shielding, obtain the image from the optimal visual angle and remarkably improve the checking accuracy, and has the advantages of high cost effectiveness, high autonomy, easiness in maintenance and the like.

The utility model discloses an intelligent goods shelf. The intelligent goods shelf comprises a goods shelf shell, a multi-channel storage module, an automatic supply module and an automatic checking module. A mounting mechanism is arranged in the goods shelf shell; the multi-channel storage module comprises a tray assembly and a position-adjustable partition plate. The tray assembly is detachably arranged on the mounting mechanism, a storage location channel is arranged in the tray assembly, and the storage location channel is divided into a plurality of channels by the partition plates; the automatic supply module is arranged in the channel in a sliding mode, and the automatic supply module conveys goods located on one side of the automatic supply module to a goods outlet of the goods shelf shell in sequence; and the automatic checking module is connected with the automatic supply module and is used for detecting the quantity of the goods in the channel. The size of the channel can be adjusted, the space utilization rate in the goods shelf can be improved, meanwhile, the goods located on one side of the automatic supply module are automatically conveyed to the goods outlet, the number of the goods in the goods shelf channel is checked in real time through the automatic checking module, and the storage and taking efficiency of the goods is improved.

The invention discloses a logistics warehouse cargo storage method and system and a storage medium, relates to the field of logistics warehouse cargo storage, realizes intelligent warehouse management through multi-module cooperation, remarkably improves inventory monitoring and cargo scheduling efficiency, and improves the cargo scheduling efficiency based on video image recognition and contour matching technologies in combination with database information. Accurate inventory data is generated in real time, unregistered goods are effectively identified, manual inventory errors are reduced, goods flow indexes are quantified through a dynamic time decay model, and goods turnover rules are accurately reflected by combining weighted analysis of carrying proportion and quantity, so that data support is provided for scheduling decision making. Multi-dimensional factors such as environmental parameters, transportation distance and storage capacity are integrated, a callout-storage staged optimization model is established, environmental adaptability, storage safety and scheduling rationality are organically combined, manual intervention is reduced, the warehouse turnover efficiency is improved, the storage cost is reduced, and a full-process closed-loop intelligent warehouse management system is formed.

The invention provides a cargo storage inventory recognition system and method based on image recognition, and belongs to the technical field of cargo storage management.The cargo storage inventory recognition system comprises the steps that firstly, storage area multi-source image sets which are provided with collection position identifiers and collected by different collection devices at different time periods are obtained, and then space correlation modeling is conducted on the storage area multi-source image sets; the method comprises the steps of obtaining an image space correlation model, identifying storage state features of stored goods based on the image space correlation model, including a stacking form and a goods allocation occupation feature, and generating a stored goods distribution model marked with image space correlation information according to the storage state features, and finally, according to the distribution model, generating an inventory list containing the cargo identifier and the storage position information, thereby efficiently and accurately completing the cargo storage inventory work.

The invention discloses a mobile information asset inventory management system based on a parallel chain, and relates to the technical field of information asset management, the mobile information asset inventory management system comprises a main chain, the parallel chain, a cross-chain interaction module, a management platform, a mobile terminal and an asset label, and the main chain stores asset metadata, core transaction records, a cross-chain protocol and an authority token. In the invention, the system records the core metadata, the state change and the core transaction log of the assets through the main chain, the whole process chain evidence storage of the assets from warehousing, checking and transfer to recovery is realized, all data are encrypted and written in in a block form, the integrity and the non-tampering property of the data are ensured, a credible basis is provided for asset supervision and audit analysis, and the asset management and audit efficiency is improved. The parallel chain adopts an authorized Byzantine fault-tolerant consensus mechanism, has the processing capability of more than 1500 transactions per second, and is matched with a reinforcement learning dynamic allocation module to generate an optimal inventory task allocation scheme according to seven dimensions such as asset state, personnel position and task load, so that the task execution efficiency is remarkably improved.

The invention discloses a storage material checking system, belongs to the technical field of intelligent storage and Internet of Things, and is used for solving the problem that an existing storage material checking method is difficult to give consideration to dual requirements of efficiency and credibility. The system comprises a sensing layer which comprises an RFID reader-writer network and is used for collecting material label data in real time to obtain real-time sensing data; the block chain layer comprises a BID identity authentication node which is used for generating a unique block chain identity label for the Internet of Things equipment and realizing equipment identity verification, and also comprises an intelligent contract engine which is used for realizing business rule verification; the co-processing layer comprises a double-chain data verification module used for comparing the real-time sensing data with block chain historical evidence storage data and generating a verification state, and further comprises an exception handling unit used for performing hierarchical response under the condition that the verification state is abnormal; and the application layer comprises a WMS interface and is used for synchronizing the material checking result with the warehouse management system. According to the system, efficient, accurate and credible warehousing material checking is realized.

The invention relates to the technical field of inventory management, in particular to a wine sample library management method and system. According to the wine sample library management method, RFID tags are used for identifying warehousing samples with one object and one code, and rule attributes are marked for each sample; defining a rule priority through a preset business rule, and distributing a storage location for the storage sample; a warehouse checking table is generated, and the samples in the warehouse are scanned and checked; when the borrowed samples in the library correspond to the samples which are returned and put in storage, identification and examination and approval are firstly carried out, and the state of each sample is determined; if the sample is damaged or overdue, destroying the sample, directly carrying out warehouse-out operation, and not carrying out return treatment; and if the corresponding replacement materials exist, the replacement materials are put into storage according to new products to be processed. According to the wine sample library management method, real-time sample positioning and tracking and automatic, intelligent and efficient warehouse management are realized, the management cost is reduced, the management efficiency is improved, and the wine sample library management method is suitable for popularization and application.

The invention relates to an article real-time tracking and checking method and system based on an RFID technology and an access door. The access door and an RFID base station are arranged in advance to acquire tracking information records. Considering that the RFID signal is easily interfered, the tracking information record is verified based on the signal data. The tracking information records are divided into effective records and ineffective records based on verification results, the effective records can be directly positioned to obtain storage positions of the articles, and the ineffective records can be used for deducing inertial storage positions by the aid of inertial databases. And updating the storage information by using the storage position, when the updating degree reaches a certain degree, automatically issuing a checking task, and generating a checking range based on the difference information. According to the invention, full-process management can be carried out on warehouse inventory based on the RFID technology, the inventory task is guided, and the asset inventory efficiency based on the RFID technology in the warehouse can be effectively improved.

The invention relates to an electric power storage material intelligent detection and management system based on the Internet of Things, and the system comprises a warehouse material management module which is used for storing, maintaining and carrying out the classification management of basic information of various electric power materials in a warehouse, and the basic information comprises material numbers, types, storage positions, number, warehousing time and material states; meanwhile, synchronous data updating with an upper management system can be carried out; according to the electric power storage material intelligent detection and management system based on the Internet of Things, through cooperative work of the warehouse material management module and the RFID positioning module, real-time storage, maintenance and position tracking of material information are realized, and an operator can acquire serial numbers, categories, quantity, storage positions and states of various electric power materials in a warehouse at any time; errors and omissions easily occurring in traditional manual checking are avoided, and the accuracy of warehouse management is improved.

The invention discloses a warehouse management system and method based on RFID electronic tag positioning, and the method comprises the following steps: deploying a plurality of RFID reader-writers, and constructing a time sequence resonance excitation field; writing a response control parameter set, and binding the RFID electronic tag to the to-be-managed article; judging whether a response state is entered or not, and constructing a label response time set; preliminary label positioning is carried out, and initial three-dimensional space coordinates are generated; electromagnetic environment information is collected to execute further judgment, and whether a response state is entered is jointly judged; constructing a virtual label response model, and generating a complemented three-dimensional space coordinate; constructing label response behavior characteristics, and generating disturbance scheduling parameters; and writing the spatial behavior attribute set of the RFID electronic tag into a warehouse management system. According to the method, time sequence resonance and virtual tag modeling are adopted, and accurate positioning, anomaly complementation and high-density and high-efficiency checking of the RFID warehouse are achieved.

The invention relates to the technical field of logistics equipment, in particular to a new-generation intelligent inventory checking station inventory checking method based on machine vision, and the method comprises the following steps: carrying out the morphological operation of a first azimuth picture set of each container, inputting the second orientation picture set of each cargo box after the second preprocessing and the morphological operation into a cargo box identification identification model, and calculating the whole stack prediction volume V1 of the cargos at the inventory taking station based on the identified cargo categories, the number of the cargo boxes loaded by the different categories of cargos and the accommodating volumes of the cargo boxes corresponding to the different categories of cargos; whether the whole stack of goods on the tray is in a complete shape or not is judged, and if the whole stack of goods on the tray is in the complete shape, the volume V2 of the whole stack of goods at the inventory taking station is calculated based on the pictures of the whole stack of goods stacked on the tray in different directions and the pixel proportion of the pictures of the whole stack of goods; on the basis of a comparison result between the volume V2 of the whole stack of the goods and the predicted volume V1 of the whole stack of the goods at the inventory taking station, the identified goods categories, the number of the containers loaded with the different categories of the goods and the accommodating volumes of the containers corresponding to the different categories of the goods, the actual categories and the actual number of the goods at the inventory taking station are determined; based on a comparison result of the determined actual category and the actual number of the goods at the inventory taking station and the actual category and the actual number of the goods stacked on the tray obtained after the RFID is read, the actual category and the actual number of the goods at the inventory taking station are rechecked for the first time; therefore, whether the goods stacked on the trays at the inventory taking station are missing or not can be judged.

The invention discloses an intelligent warehouse logistics management system and method based on a mobile robot, and relates to the technical field of warehouse logistics, and the system comprises a warehouse-in management module, a warehouse-out management module, an operation management module, an inventory management module, a report management module, a task management module and a log management module. The warehousing management module comprises an arrival list sub-module, a production plan list sub-module, a red character material warehouse-out sub-module and a manual warehousing list sub-module; the warehouse-out management module comprises a material picking application list sub-module, a delivery list sub-module, a manual warehouse-out list sub-module and a sales order sub-module; and the operation management module comprises a spot receiving operation sub-module, a sampling inspection confirmation sub-module, an inspection submodule, a quality inspection operation sub-module, a warehouse returning operation sub-module, a racking operation sub-module, a goods picking operation sub-module and a warehouse moving operation sub-module. Automatic storage and taking of the robot are achieved, the material carrying accuracy and efficiency are improved, and line side warehouses and three-dimensional warehouses are dynamically managed. And cost reduction and benefit increase of enterprises are realized.

The invention relates to the technical field of goods checking devices, in particular to a goods checking device for warehouse management and a using method thereof.The goods checking device for warehouse management comprises a warehouse, multiple sets of goods shelves, a fixing plate, a movable adjusting assembly, an intelligent checking unit and a warehouse management system; a bar code scanning gun and an RFID reader are fixedly connected to the outer portion of the fixing plate, and the movable adjusting assembly is arranged on the outer portion of the goods shelf and used for adjusting the position of the fixing plate. The intelligent inventory unit is used for dynamically optimizing the inventory efficiency and accuracy of the goods; the warehouse management system is used for storing data of goods, the bar code scanning gun and the RFID reader are driven to move through the moving adjusting assembly, checking recording of the goods is achieved, through control setting of the intelligent checking unit, the checking efficiency and accuracy of the goods are dynamically optimized, and the checking efficiency is improved.