399 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 discloses a cold chain warehouse unmanned aerial vehicle obstacle avoidance and path planning checking method and system based on AI intelligence, and belongs to the field of intelligent obstacle avoidance, and the method comprises the steps: arranging different types of sensors used for sensing the environment change of a cold chain warehouse in the cold chain warehouse, the edge gateway integrates different types of sensors, preprocesses the collected data, and sends the processed data to a cloud database; constructing a digital twin model of the target cold chain warehouse and an intelligent inventory path planning algorithm in the cloud database; the cloud sends a path scheme output by the intelligent inventory path planning algorithm to the unmanned aerial vehicle terminal and the digital twin model at the same time; the unmanned aerial vehicle terminal completes a checking task according to the path scheme, and the digital twin model is updated in real time according to the path scheme and data fed back by the unmanned aerial vehicle terminal. According to the invention, it can be ensured that the unmanned aerial vehicle efficiently and safely performs inventory tasks in a complex cold chain warehouse environment.

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 provides an intelligent inventory robot path optimization method based on environment modeling and collaborative optimization, and relates to the technical field of intelligent warehouse management, and the method comprises the steps: scanning a warehouse region through an unmanned plane platform, and generating three-dimensional warehouse point cloud data; after point cloud denoising, plane fitting, shelf boundary extraction and channel detection processing, a two-dimensional storage plane graph is generated and transmitted to a robot data base; generating an initial inventory planning path by adopting an A * algorithm, optimizing the initial path through a simulated annealing algorithm, and generating a target inventory planning path; based on the dynamic obstacle influence factors, the RFID signal intensity and the robot residual electric quantity are combined, and a target path is corrected through a mixed algorithm of multi-target optimization and PSO dynamic weight; and the operation end checks the checking progress through the AR equipment and manually adjusts the target path, so that the checking path of the intelligent checking robot can be optimized in real time in a dynamic environment, and the checking efficiency, the coverage rate and the cruising ability of the robot are improved.

The invention relates to the technical field of warehouse management, in particular to an unmanned warehouse management method and system with a real-time inventory function, and the method comprises the steps: building a signal strength-probability statistical model through return signal data generated in a historical inventory process, and carrying out the stability verification of each RFID tag return signal in a current inventory period, and under the condition that the stability is confirmed, carrying out preliminary positioning based on the time difference of arrival and determining the probability of the storage unit. And finally, the preliminary positioning is verified in combination with the probability of the storage unit and the checking information of the last checking period, so that the situation that whether the position of the RFID tag is changed really cannot be confirmed due to the fact that verification cannot be carried out when the positioning jumps is avoided. According to the invention, low-cost and high-reliability material positioning can be realized by using an existing RFID system, so that real-time and accurate checking is realized, and an information basis is provided for management of unmanned warehouses.

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 relates to a stereoscopic warehouse checking method and system based on an unmanned aerial vehicle, and the method comprises the steps: receiving a cargo checking task, and obtaining the layout information of a stereoscopic warehouse; determining the position of a to-be-checked goods location in the goods checking task in the stereoscopic warehouse; according to the layout information of the stereoscopic warehouse and the position of the to-be-checked goods location in the stereoscopic warehouse, determining a safe flight area and a hovering point of the unmanned aerial vehicle based on a path planning algorithm, and generating a flight task; issuing a flight task to the unmanned aerial vehicle, and calculating pose information of the unmanned aerial vehicle during execution of the flight task in real time through an inertial measurement unit; based on the observation image of the unmanned aerial vehicle visual system, correcting the accumulated error of the pose information through a Kalman filtering algorithm; rGB color images and depth images collected by the unmanned aerial vehicle at the to-be-checked goods locations are obtained in real time; determining whether the box stack is in an abnormal condition according to the depth image; and for the box stack which is not in the abnormal working condition, the number of goods in the box stack is determined according to the RGB color image.

The invention discloses a material digital centralized management and control system based on the Internet of Things, which relates to the technical field of digital management and control and comprises a supply chain management unit, a loss management unit, a cost accounting unit, an inventory management unit, a dynamic adjustment unit and a user management unit. The system can accurately plan the purchase quantity and time, screen high-quality suppliers, guarantee the quality and stability of material supply from the source, deeply analyze the loss data in transportation, storage and processing, formulate a targeted strategy, reduce material loss, reduce waste, dynamically check the cost in real time, perform apportionment analysis according to different dimensions, and accurately control the cost. Through intelligent warehouse-in and warehouse-out management, regular inventory checking and intelligent inventory prediction, it is ensured that inventory data is accurate, inventory is reasonably planned, an inventory strategy is dynamically adjusted, inventory overstock or stockout is reduced, and inventory cost and service level are balanced.

The invention relates to the technical field of intelligent warehouse management and Internet of Things perception, in particular to a warehouse checking method and a warehouse system. The method comprises the following steps: performing inventory demand path analysis on storage to obtain an inventory path scheme; performing inventory task issuing on the robot according to the inventory path scheme to obtain a carrying task instruction; carrying out inventory article grabbing processing according to the carrying task instruction to obtain static contact characteristic data; performing dynamic interaction and multi-mode signal acquisition based on the static contact characteristic data to obtain interactive sensing data; performing sensing signal separation on the interactive sensing data to obtain a mechanical parameter characteristic table and an acoustic characteristic spectrum; and performing article type identification matching on the mechanical parameter characteristic table and the acoustic characteristic spectrum to obtain an article type judgment result. According to the invention, the inventory function is seamlessly integrated into the daily operation process, so that the dimensionality and accuracy of the inventory information are improved, and the overall efficiency of warehousing operation is greatly improved.

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 an unmanned retail cabinet commodity expiration date management method based on a machine learning model, and the method comprises the following steps: S1, data preparation: collecting historical shelf commodity inventory data and related features from a database, and carrying out the data cleaning and feature engineering; s2, using the cleaned data to train a machine learning model; and S3, inputting the current feature information of the goods on the shelf into the model trained in the step S2, performing reasoning to identify high-immediate-risk goods, issuing an immediate checking list according to a reasoning result, executing immediate checking, and storing a checking result into a database for next model training. According to data characteristics such as historical sales volume, historical stock, commodity shelf life and replenishment cycle, the immediate risk probability of goods on a shelf is estimated, and immediate risk monitoring indexes are quantified; according to the on-time risk probability, a shelf commodity list needing to be checked is formulated, shelf commodities with high on-time risks are checked accurately, and the checking efficiency is improved.

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 present invention discloses an intelligent electronic tag management device, which relates to the field of intelligent electronic tag management technology. Nowadays, in the storage environment, there are many types of goods, including large metal products, ordinary packaged goods, and small precision goods. Traditional identification systems mostly use a single frequency or a simple antenna layout. For large metal products, due to their shielding and interference with radio frequency signals, it is difficult for the signal to effectively penetrate, resulting in difficulty in identifying goods or failure to read information, and it is easy to misread or miss reading, affecting the reliability of inventory management. The present invention reasonably allocates radio frequency signal resources to avoid signal conflicts and interference. In terms of antenna layout, it provides all-round and multi-level signal coverage for different types of goods, greatly improving the success rate and accuracy of goods identification. Whether it is in the warehousing of goods, inventory counting or outbound links, it can quickly and accurately obtain goods information, significantly improving the overall efficiency of warehousing operations.

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 relates to the technical field of inventory optimization, and discloses a dynamic inventory optimization method, which is used for dynamically determining an industrial optimal inventory. Through real-time data collection and preprocessing, accurate demand prediction and a dynamic replenishment strategy, an enterprise can quickly respond to market changes, and the risks of stock overstock and stockout are effectively avoided. Meanwhile, the inventory cost is further reduced through the dynamic safe inventory strategy and economic order quantity optimization calculation, and the fund utilization efficiency is improved. In addition, the method further pays attention to inventory minimization and cost optimization, and effective control of the total cost is achieved by optimizing a supply chain and formulating an inventory minimization strategy. And the accuracy of inventory data is ensured through periodic inventory and difference analysis, and the transparency and credibility of inventory management are improved.

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 method focuses on the non-standard warehouse checking problem in the warehouse logistics field. Aiming at the problems of low efficiency, poor accuracy and high labor cost of traditional manual checking and limitation of unmanned aerial vehicle checking in a non-standard warehouse, the invention provides a non-standard warehouse AI intelligent checking system. The system integrates robot / unmanned aerial vehicle automatic checking, AI algorithm and path planning, special scene processing and data acquisition and processing technologies. By customizing a robot chassis, a lifting device, an array camera, a multi-layer camera disc and other hardware and combining various AI recognition algorithms and path planning algorithms, efficient and accurate checking is achieved. The method has the advantages of improving the checking efficiency, improving the accuracy, reducing the labor cost, adapting to a complex environment, enhancing the reliability, facilitating algorithm iteration and deployment, being good in compatibility and high in expandability and the like, and an innovative and practical solution is provided for non-standard warehouse checking.

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 present invention belongs to the technical field of material inventory, and discloses a material warehousing management system, method, device and storage medium. The system includes: a management terminal; a plurality of identification tags, with the basic information of one piece of material entered in each identification tag, and each identification tag being detachably connected to the surface of the corresponding material; a plurality of position tags, at least two position tags being installed on each layer of the shelf, the position tags being used to record the position information of the shelf, and the position information of the shelf including: shelf number and the number of layers on the shelf; an inventory instrument, deployed in the material warehouse, the inventory instrument being communicatively connected to the management terminal, and being used to obtain the basic information of the materials stored on each shelf and the position information of the shelf, and calculate the first signal strength of each position tag and the second signal strength of each identification tag. The present invention can effectively improve the efficiency and accuracy of inventory, and enable medical staff to more clearly understand the distribution of materials in the material warehouse.

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.