28 results about "Smart bin" patented technology

The invention relates to the technical field of intelligent warehouse logistics, and discloses an intelligent warehouse logistics sorting system and method, and the system comprises a multi-dimensional data collection module, a global state perception and simulation model construction module, a demand prediction analysis module, a task optimization and resource configuration module, and an execution control and feedback adjustment module. The system realizes dynamic demand prediction, task optimization division and resource adaptation through a distributed sensing network, a three-dimensional simulation model and a deep learning algorithm, and ensures material storage safety in combination with environment adaptive regulation and control. The warehouse sorting efficiency can be improved, the resource allocation is optimized, the environmental adaptability is enhanced, and the method is suitable for modern intelligent warehouse scenes.

1. Name of the product in this design: Intelligent Electronic Warehouse. 2. Purpose of this design: for use in intelligent warehousing equipment. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

A reordering system for automatically reordering one or more objects. The reordering system includes at least one storage bin configured for storing the one or more objects and at least one reorder device positioned within the at least one storage bin. The at least one reorder device including a pressure sensor and a control unit operably coupled to the pressure sensor.

Embodiments of the present disclosure provide a cross-station picking method, device, equipment and storage medium, which are applied to an intelligent warehousing system. The method comprises: determining pre-picked materials and a pre-picking workstation based on a hit bin and a corresponding workstation of a to-be-processed outbound order, the pre-picked materials being used to represent materials in the bin that need to be cross-station picked; determining a sorting robot for carrying the pre-picked materials based on the pre-picking workstation and the pre-picked materials; sending pre-picking information to the bin workstation and sending instruction information to the sorting robot, the instruction information being used to instruct the sorting robot to carry the pre-picked materials from the bin workstation to the pre-picking workstation and put the pre-picked materials. The technical solution of the embodiments of the present disclosure solves the problem of the ineffective circulation of the bin on the conveying line and improves the picking efficiency when picking the bin across the workstations.

The application relates to the technical field of storage equipment, in particular to an integrated intelligent storage shelf which comprises a shelf main body and a storage unit. The shelf main body is composed of multiple layers of support frames, the storage unit comprises a bearing plate, a sliding assembly, a transmission mechanism and a positioning assembly, the bearing plate is horizontally moved through a driving module, and the sensor assembly and the control module are used to monitor the position and weight information of goods. The bottom of the bearing plate is provided with an antiskid pad, and the outer side wall of the support frame is provided with a reinforcing rib. The application can simplify the mechanical structure, reduce the manufacturing cost, improve the operation convenience, significantly improve the positioning accuracy of goods storage and taking, is suitable for various storage environments, and has high practicability and popularization value.

1. The name of the design product: smart warehouse of film. 2. The use of the design product: for assisting mobile phone film. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective drawing.

The invention discloses an intelligent warehouse storage and transfer scheduling system and an application method thereof, and relates to the technical field of intelligent warehouse logistics, the system comprises a server module, a handheld terminal module and an express access module, the server module dynamically allocates the number of storage bits through a machine learning time sequence prediction model based on real-time requirements and historical use data; the handheld terminal module visually displays the real-time available space of the access box through a color coding map and automatically generates an optimal delivery path; the express access module creates an independent virtual storage space for the cooperative express company through the virtual resource unit, and the application method comprises the steps of real-time data collection, demand peak prediction, virtual quota adjustment, visual guide interface generation and diversion suggestion triggering. Intelligent dynamic scheduling, fair and elastic distribution, convenient operation guidance and congestion early warning optimization of storage bit resources are realized, and the storage transfer efficiency and the system adaptability are remarkably improved.

Smart labels, methods of operating smart labels, and related contexts in which such smart labels can be used are disclosed. The smart labels, which are used in conjunction with consumer product packaging, include an energy harvester for capturing ambient energy to provide a source of electrical energy, and an electronic circuit powered by the electrical energy. A fuse provides an electrical connection between the energy harvester and the electronic circuit, and destruction of the fuse permanently disconnects the energy harvester from the electronic circuit. Unwanted continued operation of the electronic circuit powered by the energy harvester, which can be an undesirable heat source when the consumer product packaging is discarded or recycled, for example, can thus be prevented. A network of connected smart labels and smart bins that can read the smart labels can also be used to facilitate consumer recycling of consumer product packaging.

The invention provides an intelligent storage picking optimization method and system and application, and relates to the technical field of intelligent storage logistics. The method comprises the steps of obtaining scheduling information of a movable goods storage shelf carrying goods in a goods picking area of the intelligent warehouse; matching a sorting task corresponding to at least one logistics list according to the scheduling information; the sorting task is executed, and after sorting is completed, the sorted goods are placed in a goods sorting basket; the picking basket is provided with a unique label; and the labels on the picking baskets are scanned, and the labels and the logistics lists are subjected to postposition matching. According to the invention, the goods picking basket is not configured in advance according to the goods picking information on the logistics list, but the logistics list is randomly selected to execute the goods picking task according to the goods condition on the goods storage shelf which is currently placed in the goods picking area, so that the goods picking mode is more flexible.

The application relates to the technical field of intelligent warehousing, and specifically discloses a kind of plate material warehouse intelligent warehousing method, the method comprises: the position of travelling crane is acquired in real time through Gray bus system, warehouse management system and nesting system are combined, three-dimensional yard model is constructed, the extensive mode of first-in first-out or random stacking is fundamentally changed by combining intelligent stacking and plate turning risk prediction model, the model quantifies the nonlinear influence of storage time and call frequency on plate turning risk through mathematical formula, that is, the future call demand of each incoming warehouse plate is predicted, and the stacking position is allocated according to the call demand, so as to reduce the plate turning frequency in the future, then the plate turning minimization problem is converted into a solvable integer programming model based on the optimal delivery sequence formula, so that the system can quickly give a global optimal solution when facing complex delivery demand of multiple batches, multiple stacks and multiple levels, thereby improving the plate call efficiency.

According to the intelligent storage integrated management system provided by the invention, warehouse-in, warehouse-out and inventory data are uniformly acquired through the data processing module, decision-making deviation caused by data splitting of each algorithm unit is avoided, each unit in the algorithm decision-making module works cooperatively, and particularly, the inventory distribution unit calls predicted data of the shelf popularity analysis unit to correct a sorting scheme, so that the sorting efficiency is improved. The method does not depend on orders and real-time inventory any more, high-heat short-distance goods shelves can be preferentially selected, and carrying time consumption is reduced; the algorithm units are linked around the whole process, for example, warehouse position recommendation provides reasonable layout for order group wave and inventory distribution, and local optimization loss is avoided. And the instruction execution module controls the equipment according to the cooperative instruction, so that action conflicts are avoided, and the defect that a warehouse management system in the prior art cannot realize a full-process intelligent cooperative effect is overcome.

The invention discloses a warehouse multi-RGV task planning method and device, and belongs to the technical field of intelligent warehousing. According to the method, a multi-RGV task planning model with logistics efficiency and energy consumption cost as targets is established, and RGV and elevator task planning codes and algorithms are provided; the optimal task planning scheme with the minimum time cost and the minimum energy consumption cost required by transportation of all distributed cargos is completed through iterative optimization, and each RGV is controlled to execute the cargo transportation task through the optimal task planning scheme, so that the logistics transportation efficiency is improved, and the problems that the task planning of the current intelligent warehouse on the RGV is unreasonable, and the task planning efficiency is poor are solved. The energy consumption is high; and the transfer efficiency is low.

This invention belongs to the field of intelligent warehousing technology, specifically relating to an intelligent automated warehouse with an intelligent automated sorting robot and its control method. The control method for the intelligent automated warehouse includes the following steps: Step 1, a cargo box on a shelf is delivered to a freight robot via a storage and retrieval device; Step 2, the freight robot delivers the cargo box to a workstation; Step 3, after the workstation identifies the cargo box, the freight robot delivers the cargo box to a sorting rack; Step 4, the intelligent automated sorting robot performs sorting operations on the goods in the cargo boxes delivered to the sorting rack; In Step 4, a load balancing algorithm is used to select a suitable individual from among multiple intelligent automated sorting robots to perform the sorting operation.

The invention discloses an optimal destination selection method for a carrying task of an intelligent storage robot, and the method comprises the following steps: representing the flexibility through the driving time range of the robot, and calculating the flexibility of each robot; sorting the robots in a descending order according to the flexibility; initializing the ready time of the destination; distributing the robots to destinations one by one according to the robots sorted in the descending order; the maximum value of the time for each destination to finish all delivery tasks is calculated finally, and an initial solution is obtained; and further optimizing the initial solution by using a heuristic search optimization algorithm to obtain an optimal solution. According to the invention, through an optimization algorithm of optimal destination selection, the total delivery time of all workstations is reduced, and the overall operation efficiency of the whole warehousing system is greatly improved.

The invention relates to the technical field of warehouse management, in particular to a PCBA (Printed Circuit Board Assembly) intelligent warehouse management method, which comprises the following steps of: generating a unique traceability code through an ERP (Enterprise Resource Planning) system, and in response to a disassembling instruction, disassembling materials which are packaged and segmented by using an automatic tray dividing machine; determining the stripping type of the unique traceability code of the minimum material unit based on the pasting area of the unique traceability code of the disassembled minimum material unit and the pasting position complexity; based on the stripping type of the unique traceability code of the minimum material unit and / or the structural strength of the minimum material unit, it is determined that the unique traceability code is stripped through a strong stripping method or a non-strong stripping method; based on a comparison result of the damage characteristic parameter of the minimum material unit which is not completely stripped and a preset damage characteristic parameter, determining a secondary stripping residual unique traceability code or sending the minimum material unit which is not completely stripped to a residual material bin; according to the invention, the integrity of the unique traceability code is improved by improving the control accuracy of the updating process of the unique traceability code.

The invention belongs to the technical field of intelligent warehouse logistics, and particularly relates to a warehouse shuttle vehicle path planning method and system based on multi-source coupling collaborative optimization, and the method comprises the steps: firstly, carrying out the fusion of task chain logic and time-space diagram neural network congestion prediction, and quantifying a dynamic urgency degree weight; further constructing a mixed integer programming model which takes minimization of weighted total completion time as a target and takes space-time mutual exclusion as a constraint, solving a conflict-free space-time corridor at one time, and realizing conflict pre-resolution and global optimization collaboration; the stability of the system is monitored on line by designing a Lyapunov function based on a task weight, and rapid local adjustment is triggered when the risk exceeds the threshold; and finally, automatically optimizing the urgency degree fusion function and target model parameters by using a meta-learner in a digital twinning environment to form closed-loop evolution. Based on multi-mechanism deep coupling, the throughput efficiency, the robustness and the intelligent level of a multi-vehicle system in a complex dynamic environment are remarkably improved.

The invention relates to the technical field of intelligent warehousing, in particular to an AI-enabled intelligent warehousing sorting robot and method. The robot comprises a 3D vision intelligent positioning module, an AI dynamic path planning module, a multi-category self-adaptive sorting execution module, a whole-process data security collaboration module and an energy consumption-efficiency balance control module. The 3D visual intelligent positioning module collects cargo characteristics and corrects positioning deviation, the AI dynamic path planning module generates an optimal path, the self-adaptive sorting execution module adjusts sorting parameters, the data security collaboration module encrypts traceability data, and the energy consumption balance control module optimizes energy consumption; according to the scheme, the problems that an existing robot is inaccurate in positioning, low in efficiency, high in loss and unsafe in data are solved, the sorting suitability and safety are improved, and the method is suitable for multi-category storage scenes.

The application belongs to the technical field of intelligent warehousing logistics, and particularly relates to a warehouse shuttle vehicle path planning method and system based on multi-source coupling collaborative optimization. The method firstly quantifies the dynamic urgency weight by fusing task chain logic and space-time graph neural network congestion prediction; then a mixed integer programming model is constructed with the minimum weighted total completion time as the target and space-time mutual exclusion as the constraint, and a conflict-free space-time corridor is solved at one time to realize conflict pre-dissolution and global optimization collaboration; the system stability is monitored online by designing a Lyapunov function based on task weight, and a rapid local adjustment is triggered when the risk exceeds the threshold; finally, the meta-learner in the digital twin environment is used to automatically optimize the urgency fusion function and the target model parameters to form a closed-loop evolution. The application is based on multi-mechanism deep coupling, which significantly improves the throughput efficiency, robustness and intelligent level of the multi-vehicle system in a complex dynamic environment.

The invention provides a warehouse-in and warehouse-out assembly line type settlement and access control linkage method and system for an intelligent warehouse, and relates to the technical field of intelligent warehousing, and the method comprises the steps: receiving a warehouse-out operation request for target goods, generating a corresponding to-be-executed warehouse-out task, and according to the to-be-executed warehouse-out task, executing the warehouse-out operation request; analyzing and acquiring a specific storage location identifier occupied by the target cargo in the warehouse storage plane model, retrieving coordinates of an original closed polygon boundary vertex sequence uniquely corresponding to the storage location identifier or describing a plane contour of the storage location identifier, and performing adaptive compression on the original vertex sequence by applying a polygon simplification algorithm, and generating a simplified polygon boundary vertex sequence coordinate. Through a series of automatic, digital and linkage technical means, the problems of risk release without settlement, low efficiency and the like are solved, and finally the safe, efficient and accurate intelligent management and control effect is achieved.

This invention relates to the field of intelligent warehousing technology, and discloses an intelligent warehousing inventory dynamic management method and system oriented towards multi-objective optimization. The method includes: acquiring synchronous time-series data streams of warehousing inventory; identifying a set of key elements of the warehousing inventory and constructing a multi-objective competition relationship graph; matching warehousing inventory with operational tasks based on the synchronous time-series data stream and the multi-objective competition relationship graph to obtain a warehousing operation instruction set; analyzing the changes in the key element set caused by the warehousing operation instruction set to obtain a discrete disturbance event set; performing a transmission analysis on the superimposed impact of the discrete disturbance event set based on the key element set and the change information to obtain a disturbance target impact mapping table; and coordinating the warehousing operation instruction set according to the disturbance target impact mapping table and the multi-objective competition relationship graph to obtain a collaborative operation execution scheme. This invention can improve the efficiency of multi-objective collaborative operation execution in warehousing under dynamic disturbance environments.

1. Name of the product in this design: Intelligent warehouse weighing cabinet. 2. Purpose of this design: for storing and weighing items. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.