Goods allocation path planning method and device

Abstract

The invention discloses a goods allocation path planning method and device, and relates to the technical field of electronic commerce and intelligent logistics. A specific embodiment of the method comprises the following steps: receiving article query information, first position information and target scene information transmitted by terminal equipment; determining shelf article information and a shelf distribution model corresponding to the target scene information; determining a target article matched with the article query information according to the goods shelf article information, determining a goods allocation where the target article is located, and obtaining second position information of the goods allocation; and performing path planning according to the first position information, the second position information and the shelf distribution model, and returning the planned path and the information of the target article to the terminal device for display. According to the embodiment, the target article and the location of the target article can be intelligently determined, and accurate path planning is performed based on the shelf distribution model of the target scene, so that efficient and accurate navigation service is provided for the article seeker, and the shopping experience of the article seeker and the article seeking efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of e-commerce and intelligent logistics, and particularly to a method and device for planning a location path for goods. Background Art

[0002] In current store, warehouse area or shopping mall scenarios, the person looking for goods (such as a sorter or a customer) often needs to spend a lot of time looking for the required items in the designated scenario. This is mainly because the layout and classification method of the items lack sufficient intuitiveness, making it difficult for the person looking for goods to quickly locate the target item. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method and device for planning a location path for goods, which can at least solve the problem that the person looking for goods spends too much time looking for items in the prior art.

[0004] To achieve the above object, according to one aspect of the embodiments of the present invention, there is provided a method for planning a location path for goods, including:

[0005] Receiving item query information, first location information, and target scenario information transmitted by a terminal device; wherein, the first location information is the information located by the terminal device, and the terminal device determines the target scenario according to the first location information;

[0006] Determining shelf item information and a shelf distribution model corresponding to the target scenario information;

[0007] According to the shelf item information, determining a target item that matches the item query information, determining the location of the target item, and obtaining second location information of the location;

[0008] Performing path planning according to the first location information, the second location information, and the shelf distribution model, and returning the planned path and the information of the target item to the terminal device for display.

[0009] Optionally, the method further includes:

[0010] Receiving a shelf distribution model and shelf item information transmitted by the management terminal of each scenario; wherein, the shelf item information includes a location number and item information;

[0011] Storing the shelf distribution model and shelf item information of each scenario in a database.

[0012] Optionally, the determining the location of the target item and obtaining second location information of the location includes:

[0013] Obtaining the location number of the location where the target item is located from the shelf item information of the target item;

[0014] Determine the positioning tag corresponding to the goods location number, and send a positioning instruction to the positioning tag;

[0015] Receive the coordinate value feedback by the positioning tag, and use the coordinate value as the second location information; wherein, the positioning tag determines the coordinate value of the goods location by transmitting a signal to the positioning base station of the target scenario.

[0016] Optionally, the path planning according to the first location information, the second location information and the shelf distribution model includes:

[0017] Determine the grid map model of the target scenario, and determine the first node corresponding to the first location information and the second node corresponding to the second location information in the grid map model;

[0018] Determine the neighbor nodes adjacent to the first node, use the first node as the starting node and the neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node to the second node based on each current node, so as to screen the target neighbor node with the minimum estimated total cost;

[0019] Determine the other neighbor nodes adjacent to the target neighbor node, use the target neighbor node as the starting node and the other neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node to the second node based on each current node, so as to screen the target other neighbor node with the minimum estimated total cost;

[0020] Repeat the operations of determining the estimated total cost and screening the neighbor node with the minimum estimated total cost until the second node exists in the current nodes, and connect the first node, the determined neighbor nodes and the second node in sequence to obtain the planned path.

[0021] Optionally, the generation process of the grid map model of the target scenario includes:

[0022] According to the shelf distribution model of the target scenario, determine the passable area and the obstacle area of the target scenario, convert the passable area into grid nodes, and convert the obstacle area into grid graphics to obtain the grid map model of the target scenario.

[0023] Optionally, the obtaining of the estimated total cost from the starting node to the second node based on each current node includes:

[0024] Determine the cost from the starting node to each current node and the heuristic cost from each current node to the second node, and accumulate them to obtain the total cost corresponding to each current node.

[0025] Optionally, the path planning according to the first location information, the second location information and the shelf distribution model includes:

[0026] Send a statistical task to the camera devices in the target scenario to receive the pedestrian flow data of each channel collected by the camera devices;

[0027] Determine the congestion degree of each channel according to the pedestrian flow data of each channel, and perform path planning in combination with the first position information, the second position information and the shelf distribution model.

[0028] To achieve the above object, according to another aspect of the embodiments of the present invention, there is provided a device for planning a goods location path, including:

[0029] A receiving module, configured to receive the item query information, the first position information, and the target scenario information transmitted by the terminal device; wherein, the first position information is the information located by the terminal device, and the terminal device determines the target scenario according to the first position information;

[0030] A determining module, configured to determine the shelf item information and the shelf distribution model corresponding to the target scenario information;

[0031] A positioning module, configured to determine a target item matching the item query information according to the shelf item information, determine the goods location where the target item is located, and obtain the second position information of the goods location;

[0032] A path planning module, configured to perform path planning according to the first position information, the second position information, and the shelf distribution model, and return the planned path and the information of the target item to the terminal device for display.

[0033] Optionally, the device further includes a storage module, configured to:

[0034] Receive the shelf distribution model and the shelf item information transmitted by the management end of each scenario; wherein, the shelf item information includes the goods location number and the item information;

[0035] Store the shelf distribution model and the shelf item information of each scenario in the database.

[0036] Optionally, the positioning module is configured to:

[0037] Obtain the goods location number of the goods location where the target item is located from the shelf item information of the target item;

[0038] Determine the positioning label corresponding to the goods location number, and send a positioning instruction to the positioning label;

[0039] Receive the coordinate value fed back by the positioning label, and use the coordinate value as the second position information; wherein, the positioning label determines the coordinate value of the goods location by transmitting a signal to the positioning base station in the target scenario.

[0040] Optionally, the path planning module is configured to:

[0041] Determine the grid map model of the target scenario, and determine a first node corresponding to the first position information and a second node corresponding to the second position information in the grid map model;

[0042] Determine the neighbor nodes adjacent to the first node, use the first node as the starting node and the neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node of each current node to the second node, so as to screen the target neighbor node with the minimum estimated total cost;

[0043] Determine the other neighbor nodes adjacent to the target neighbor node, use the target neighbor node as the starting node and the other neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node of each current node to the second node, so as to screen the target other neighbor node with the minimum estimated total cost;

[0044] Repeat the operations of determining the estimated total cost and screening the neighbor node with the minimum estimated total cost until the second node exists in the current nodes, and connect the first node, the determined neighbor nodes and the second node in sequence to obtain the planned path.

[0045] Optionally, the generation process of the grid map model of the target scenario includes:

[0046] According to the shelf distribution model of the target scenario, determine the passable area and the obstacle area of the target scenario, convert the passable area into grid nodes, and convert the obstacle area into grid graphics to obtain the grid map model of the target scenario.

[0047] Optionally, the path planning module is configured to:

[0048] Determine the cost from the starting node to each current node and the heuristic cost from each current node to the second node, and accumulate them to obtain the total cost corresponding to each current node.

[0049] Optionally, the path planning module is configured to:

[0050] Send a statistical task to the camera device of the target scenario to receive the pedestrian flow data of each channel collected by the camera device;

[0051] According to the pedestrian flow data of each channel, determine the congestion degree of each channel, and perform path planning in combination with the first position information, the second position information and the shelf distribution model.

[0052] To achieve the above object, according to another aspect of the embodiments of the present invention, a path planning electronic device is provided.

[0053] The electronic device according to an embodiment of the present invention includes: one or more processors; a storage device for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the goods location path planning method described in any one of the above.

[0054] To achieve the above object, according to another aspect of an embodiment of the present invention, there is provided a computer-readable medium having a computer program stored thereon, and when the program is executed by a processor, it implements the goods location path planning method described in any one of the above.

[0055] To achieve the above object, according to yet another aspect of an embodiment of the present invention, there is provided a computing program product. A computing program product according to an embodiment of the present invention includes a computer program, and when the program is executed by a processor, it implements the goods location path planning method provided by the embodiment of the present invention.

[0056] According to the solution provided by the present invention, an embodiment of the above invention has the following advantages or beneficial effects: By providing a search item service and positioning technology through a terminal device in a target scenario, the server quickly locates the target item and the shelf where it is located based on the positioning, target scenario, and search item information provided by the terminal device, locates the shelf position, so as to generate an optimal item-finding path in real time, guiding the item searcher to quickly find the required item, thereby solving the difficulties encountered by the item searcher when looking for items in the scenario, improving the item-finding efficiency and reducing the waiting time.

[0057] The further effects of the above non-conventional optional ways will be described in combination with specific embodiments below. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The drawings are used to better understand the present invention and do not constitute an improper limitation to the present invention. Among them:

[0059] Figure 1 is a main flow schematic diagram of a goods location path planning method according to an embodiment of the present invention;

[0060] FIG. 2(a) is a schematic diagram of an in-store shelf distribution model;

[0061] FIG. 2(b) is an elevation view of an item shelf;

[0062] FIG. 2(c) is a schematic diagram of a positioning tag located based on a store positioning base station;

[0063] FIG. 3(a) is a schematic diagram of determining a starting point coordinate and an ending point coordinate;

[0064] FIG. 3(b) is a schematic diagram of a terminal device displaying a planned path;

[0065] FIG. 3(c) is a schematic diagram of the information of the target item displayed on the terminal device;

[0066] Figure 4 FIG. 4 is a schematic flowchart of an optional method for planning a storage location path according to an embodiment of the present invention;

[0067] Figure 5 FIG. 5 is a schematic diagram of an in-store grid map model;

[0068] Figure 6 FIG. 6 is a schematic diagram of the main modules of a storage location path planning device according to an embodiment of the present invention;

[0069] Figure 7 FIG. 7 is an exemplary system architecture diagram to which an embodiment of the present invention can be applied;

[0070] Figure 8 FIG. 8 is a schematic diagram of the structure of a computer system of a mobile device or a server suitable for implementing an embodiment of the present invention. Detailed Embodiments

[0071] The following describes exemplary embodiments of the present invention with reference to the accompanying drawings. Various details of the embodiments of the present invention are included to assist in understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted below.

[0072] It should be noted that in the technical solutions of the present disclosure, in terms of the collection, gathering, updating, analysis, processing, use, transmission, storage, etc. of user personal information, they all comply with the provisions of relevant laws and regulations, are used for legal purposes, and do not violate public order and good customs. Necessary measures are taken for user personal information to prevent illegal access to user personal information data, and to safeguard user personal information security, network security, and national security.

[0073] When a current shopper (such as a sorter or a customer) enters a store (such as an instant retail business store or an ordinary store) or a shopping mall, it usually takes a lot of time to find the items they need. This is because the layout of the items and the way the items are classified are not intuitive enough, making it difficult for shoppers to quickly find the target items. Although some stores have tried to improve this situation through digital tags or staff assistance, these measures still have certain limitations: 1) During peak hours, the limited number of staff may not be able to respond to the needs of all shoppers in a timely manner, resulting in an extended shopping time. 2) Digital tags and signs need to be updated and maintained regularly, which not only increases the operating costs but may also affect the shopper experience due to untimely maintenance. 3) The shopping method mainly relies on manual experience, which is likely to increase the time to find medicine due to an unreasonable route and is also prone to the situation of passing through the same area repeatedly, increasing physical consumption. Therefore, in order to improve the shopper experience, optimize the item layout and classification method, reduce the time for shoppers to find items, and at the same time reduce the operating costs are urgent problems to be solved.

[0074] See Figure 1 , which shows the main flowchart of a goods location path planning method provided by an embodiment of the present invention, including the following steps:

[0075] S101: Receive the item query information, the first location information, and the target scenario information transmitted by the terminal device; wherein, the first location information is the information located by the terminal device, and the terminal device determines the target scenario according to the first location information;

[0076] S102: Determine the shelf item information and the shelf distribution model corresponding to the target scenario information;

[0077] S103: According to the shelf item information, determine the target item that matches the item query information, determine the goods location where the target item is located, and obtain the second location information of the goods location;

[0078] S104: Perform path planning according to the first location information, the second location information, and the shelf distribution model, and return the planned path and the information of the target item to the terminal device for display.

[0079] In the above embodiments, for steps S101 and S102, this solution can be applied to various scenarios, such as stores and shopping malls. For illustration purposes, the store is taken as an example. Multiple terminal devices are configured in the store, such as PDA (Personal Digital Assistant) devices. When the item finder enters the store, they can use the PDA to search for the items they need. For example, by clicking the drug query function and entering the drug information they need to purchase. However, considering the large number of people in shopping malls and stores, the number of PDA devices configured may be too large, resulting in excessive cost consumption. In this case, a shopping mall mini-program can be set up, and the item finder can achieve route planning by accessing this mini-program. Therefore, the terminal device can be a PDA device or a personal device such as the item finder's mobile phone. Among them, the PDA terminal: is an electronic product used in the supermarket and retail industries, and the charging method is through a USB port.

[0080] The items required here can be the items needed by the user themselves. For example, if the user needs to buy a cold medicine, the cold medicine here is the drug information entered in the search bar. It can also be the items specified in the online order received by the sorter. For example, the sorter holds a PDA and receives an online order specifying that a stomach medicine needs to be bought. The PDA automatically links with the server based on the stomach medicine information to determine its specific location, and finally displays its specific shelf location number on the sorting page.

[0081] In addition, whether it is a PDA device or a personal device such as the item finder's own mobile phone, the positioning function needs to be enabled, such as the GPS (Global Positioning System) positioning function, to achieve the purpose of automatic positioning. The item finder's current location is located through the terminal device, and then the location of the store where the item finder is located is located based on this location. In actual operation, although the terminal device can send the item finder's location to the server for the server to determine the store location, this will increase the processing burden on the server. Therefore, this solution preferably determines the store location by the terminal device itself, reducing the amount of data interaction with the server, alleviating the server's pressure and improving the response speed.

[0082] After that, the terminal device transmits the located item finder's location (i.e., the first location information), store information, and item query information to the server. The server determines the shelf distribution model and shelf item information corresponding to the store from the database (such as MySQL). Among them, MySQL is one of the most popular relational database management systems, used to save data in different tables.

[0083] In practical applications, when arranging the layout of a store, a distribution model of the store's shelves will be drawn, as shown in Figure 2(a). The model includes shelves, checkout counters, passable areas, and the indoor layout. The passable areas indicate where passage is possible. The distribution model of the store's shelves and the actual shelf distribution in the store are drawn according to a ratio of 1:n. This distribution model of the store's shelves can be dynamically adjusted. For example, the positions of the shelves in a supermarket are adjusted once a week. In this case, the distribution model of the store's shelves also changes accordingly.

[0084] In addition, the store also needs to draw elevation views of the item shelves, as shown in Figure 2(b). The shelf storage areas are set as A, B, C, D... in sequence. Each shelf is numbered 01, 02, 03, 04, 05... from the upper layer to the lower layer in sequence. For example, the number of the top layer of the innermost shelf is A-01. Items are placed on each layer of each shelf. The information of the items on the shelf includes the shelf location number (shelfId, indicating the location of the item on the shelf, such as A-01-01-01, where A-01 represents the shelf number, the second 01 represents the first layer, and the last 01 represents the first position on the first layer), the item code (skuName), and the inventory quantity (usableQuantity). The item information can be obtained according to the item code.

[0085] The store can set up a store management terminal, which is used to manage the above-mentioned distribution model of the store's shelves, the elevation views of the item shelves, and the information of the items on the shelf, and upload this information to the server. The server stores this information in a database (such as MySQL), and at the same time associates the items with the elevation views of the item shelves. By querying the items, the shelf where the item is located can be determined. It should be noted that if there are too many types of items queried, these items need to be first returned to the terminal device for display for the item finder to select the items they need, and then the next operation can be carried out.

[0086] For step S103, in order to optimize the item query and positioning process, this solution combines the matching of the information of the items on the shelf, Ultra Wide Band (UWB) positioning technology, and path planning to ensure that the target item can be quickly and accurately found and its specific location can be determined. Among them, UWB positioning technology is a wireless carrier communication technology. It does not use a sine carrier, but uses nanosecond-level non-sine wave narrow pulses to transmit data. Therefore, the spectrum range it occupies is very wide. UWB technology has the advantages of low system complexity, low transmitted signal power spectral density, insensitivity to channel fading, low interceptability, and high positioning accuracy, and is especially suitable for high-speed wireless access in indoor and other dense multipath environments.

[0087] The server matches the target item that matches the item query information from the shelf item information. For example, it matches the target drug corresponding to the drug demand information from the shelf drug information, and determines the location number, drug name, and drug inventory of the target drug. Therefore, after determining the target item, the location number of the location where it is located can be determined according to the item information of the target item, and then the specific location of the target item can be determined according to the location number.

[0088] In this solution, positioning base stations are pre-installed in the store. For example, positioning base stations are installed at the four corners of the pharmacy room to communicate with the positioning tags to achieve the precise positioning function, as shown in Figure 2 (c). Similarly, positioning tags are pre-installed at each location number. For example, the shelfId of each location is used as the positioning tag and placed at each drug location. The positioning tag can not only receive and send signals, but also communicate with the base station to determine its own position. Therefore, the server determines the shelf position where the item is placed by querying the item name, location number, and inventory in the database, uses ultra-wideband technology to locate the item location coordinate value, and stores it in the MySQL database table to provide a basis for subsequent path planning. The coordinates here can also consider the height to improve the accuracy. However, considering that the position corresponding to the location number indicates the specific position of the specific layer of the shelf and the subsequent path planning does not consider the height, this solution preferably considers two-dimensional coordinates.

[0089] The path planning device can be flexibly deployed on the server, PDA device, or small program, or even the store management terminal. This means that in addition to the direct interaction between the server and the positioning tag, the positioning instruction can also be transmitted in other ways. For example, the server can first send the positioning instruction containing the shelfId to the terminal device, and the terminal device then transmits the instruction to the corresponding positioning tag according to the shelfId. After the positioning tag determines its own position, it will feedback the position information to the terminal device to help the staff or the item finder quickly find the required item. Or the server sends the positioning instruction to the store management terminal, and after the positioning tag locates, it feedbacks the end position to the store management terminal to achieve the purpose of path planning. The whole process is efficient and accurate, greatly improving the pharmacy operation efficiency and service quality. Considering the relatively fast running speed of the server, this solution preferably considers the server method.

[0090] For step S104, the first position information where the item finder is currently located is used as the starting coordinate (z, w), and the second position information of the location is used as the ending coordinate (x, y). Based on the above information, the path planning device combines the shelf distribution model of the store to perform path planning. Among them, the starting coordinate and the ending coordinate can also be stored in the MySQL database table first, and then passed to the path planning device.

[0091] Suppose the seeker is currently at the store entrance with coordinates (5, 5), and the target drug is located at a position on the shelf with coordinates (10, 15). The path planning device calculates the optimal path from the starting point (5, 5) to the ending point (10, 15) according to the shelf distribution model of the store, considering avoiding obstacles and choosing the shortest distance. Finally, a path is generated and the optimal drug-finding path is displayed on the PDA. The seeker holds the PDA and smoothly reaches the position of the target drug from the entrance according to the path, as shown in Figures 3(a) and 3(b).

[0092] It should be noted that since only two-dimensional coordinates are considered, the planned path only guides the seeker to in front of which shelf. However, for which item is the target item in the specific shelf, it still needs to be displayed on the interface, as shown in Figure 3(c). The name, item code, shelving position (and actually the inventory quantity can also be included) of the target item are displayed together on the terminal device. In addition, this path can also continuously update the position of the seeker in the route as the seeker moves. This process requires the terminal device to collect the position of the seeker in real time and update the displayed information based on the position of the seeker.

[0093] In addition, in this solution, the server can also regularly send statistical tasks to the camera devices in the store. The camera devices collect the pedestrian flow data of each channel according to the instructions and feedback this information to the server. The server calculates the congestion degree of each channel based on the received number information. At the same time, combining the starting point coordinates (z, w), the ending point coordinates (x, y) and the shelf distribution model of the store, the server can plan the optimal walking path for the seeker to use. When it is detected that a certain channel is in a high congestion state for a long time, the system will automatically mark this channel as "temporarily impassable" to guide the seeker to choose other routes and ensure a smooth shopping experience.

[0094] For example, in a large supermarket, the server analyzes the data transmitted back by the camera and finds that Channel X is continuously congested due to a promotional activity. At this time, the server not only calculates that the congestion degree of Channel X is relatively high, but also re-plans the best path from the entrance to different areas based on the map information inside the supermarket (including the entrance, exit and shelf distribution), avoids the seeker passing through Channel X, and timely updates the in-store navigation guidance to remind the seeker to detour.

[0095] The method provided by the above embodiments can, by combining the first position information located by the terminal device and the target scenario information, enable the server to intelligently determine the target item and its location on the shelf, and perform accurate path planning based on the shelf distribution model of the target scenario, so as to provide efficient and accurate navigation services for the seeker, improve the shopping experience of the seeker and the efficiency of finding items, and at the same time reduce the labor cost.

[0096] SeeFigure 4 , which shows a schematic flow diagram of an optional goods location path planning method according to an embodiment of the present invention, including the following steps:

[0097] S401: Determine the grid map model of the target scenario, and determine the first node corresponding to the first position information and the second node corresponding to the second position information in the grid map model;

[0098] S402: Determine the neighbor nodes adjacent to the first node, use the first node as the starting node and the neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node to the second node based on each current node, so as to screen the target neighbor node with the minimum estimated total cost;

[0099] S403: Determine the other neighbor nodes adjacent to the target neighbor node, use the target neighbor node as the starting node and the other neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node to the second node based on each current node, so as to screen the target other neighbor node with the minimum estimated total cost;

[0100] S404: Repeat the operations of determining the estimated total cost and screening the neighbor node with the minimum estimated total cost until the second node exists in the current nodes, and connect the first node, the determined neighbor nodes and the second node in sequence to obtain the planned path.

[0101] In the above embodiment, according to the starting point coordinates, the ending point coordinates and the shelf distribution model, the path planning algorithm A* algorithm is preferably used to output the optimal path. Among them, the A* algorithm, as one of the heuristic search algorithms, is an algorithm that finds the lowest passing cost for a path with multiple nodes on a graphic plane and can find the shortest path. The starting point coordinates correspond to the starting node (i.e., the first node), and the ending point coordinates correspond to the target node (i.e., the second node). The specific implementation process is as follows:

[0102] 1. Define the search space: According to the shelf distribution model of the target scenario, determine the passable area and the obstacle area, convert the passable area into grid nodes, mark the obstacle area, and obtain a solid grid graph, so as to generate the grid map model of the target scenario. The shelf distribution model includes shelves, checkout counters, passable areas and indoor layouts. Therefore, obstacles such as corridors, shelves or columns in the store can be converted into a grid graph, and each grid node represents a possible position. See Figure 5 As shown, the solid position represents the obstacle area.

[0103] 2. The path planning device determines the starting position of the goods finder, i.e., the starting point coordinates (z, w), and the ending point coordinates (x, y) of the shelf where the target item is located.

[0104] 3. Define the heuristic function: The heuristic function is the shortest distance from the current node to the target node. In this solution, the Manhattan distance is preferably used as the heuristic function. The Manhattan distance is a geometric term used in a geometric metric space to denote the total absolute axial distance between two points in a standard coordinate system.

[0105] 4. Initialize the open set and the closed set: The open set stores the nodes to be evaluated, and the closed set stores the nodes that have been evaluated. The starting point (z, w) is added to the open set.

[0106] 5. Loop search: Repeat the following steps until the target node is found: Select the node with the lowest estimated total cost in the open set and move this node to the closed set. Starting from the starting node, obtain the grid nodes adjacent to and passable from the starting node in the four directions around the starting node (up, down, left, and right, without considering obstacles, i.e., the grid graph). Take this grid node as the current node, calculate the actual cost from the starting node to the current node, and the heuristic cost from the current node to the target node. The sum of the two gives the estimated total cost from the starting node to the target node based on this current node. Then select the node with the minimum estimated total cost from all neighbor nodes, that is, find a path that is both close to the target node and avoids high-cost areas.

[0107] Among them, the estimated total cost = the actual cost from the starting node to the current node + the heuristic cost from the current node to the target node. The actual cost from the starting node to the current node: represents the actual cost or price of the path from the starting node to the current node. This cost can be the actual distance of movement, time, etc. in specific application scenarios. The heuristic cost from the current node to the target node: is an estimated value representing the expected cost or price of the shortest path from the current node to the target node. This estimated value is usually calculated according to a certain rule or heuristic function, such as the Manhattan distance or the Euclidean distance.

[0108] Take Figure 5 as an example. Assume that the lower right corner is the starting node, and determine that the node on its left is the node with the minimum cost, assumed to be A. Thus, the starting node - A is obtained, and this relationship is stored in the closed set. Then, based on this node A, continue to determine, from the neighbor nodes of node A, the node with the minimum total cost of node A - neighbor node + neighbor node - target node, assumed to be node B. Store node A - node B in the closed set. Then continue based on this node B, and continue to determine, from the neighbor nodes of node B, the node with the minimum total cost of node B - neighbor node + neighbor node - target node, assumed to be node C, and so on until there is a target node among the neighbor nodes of the node. Starting from the target node, trace back along each node to the starting node to construct the shortest path.

[0109] The method provided by the above embodiments enables the server to perform path planning efficiently and accurately by designing a grid map model of the store and using a node screening algorithm based on cost estimation. It gradually expands the neighbor nodes and screens the nodes with the minimum estimated total cost, ensuring the selection of the optimal path each time and reducing unnecessary searches. At the same time, based on the grid map model, the obstacles and passable areas in the environment can be accurately represented, ensuring the accuracy of path planning. This method is applicable to various complex scenarios, can dynamically adapt to different target scenarios and changes in location information, and finally generates an optimal or approximately optimal path, improving the navigation experience of the goods finder.

[0110] In summary, the present invention proposes an optimal item-finding route scheme for in-store shopping. By searching for items through the store's PDA or applet and combining positioning technology, it can generate an optimal item-finding path in real time, guiding the goods finder to quickly find the required items, significantly improving the item-finding efficiency and reducing the waiting time. By designing a path planning device, using the location of the item searched by the goods finder as the end coordinate and the location of the goods finder as the start coordinate, and adopting the A* algorithm for path planning, the optimality of the path is ensured. This not only solves the difficulties encountered by the goods finder when looking for items in the store, but also improves the overall shopping experience, enhancing the service quality and operation efficiency of the store.

[0111] See Figure 6 , which shows a schematic diagram of the main modules of a location path planning device 600 provided by an embodiment of the present invention, including:

[0112] A receiving module 601, configured to receive item query information, first location information, and target scenario information transmitted by a terminal device; wherein, the first location information is the information located by the terminal device, and the terminal device determines the target scenario according to the first location information;

[0113] A determining module 602, configured to determine shelf item information and a shelf distribution model corresponding to the target scenario information;

[0114] A positioning module 603, configured to determine a target item matching the item query information according to the shelf item information, determine the location of the target item, and obtain second location information of the location;

[0115] A path planning module 604, configured to perform path planning according to the first location information, the second location information, and the shelf distribution model, and return the planned path and the information of the target item to the terminal device for display.

[0116] The implementation device of the present invention further includes a storage module, configured to:

[0117] Receive the shelf distribution model and shelf item information transmitted by the management end for each scenario; among them, the shelf item information includes the location number and item information.

[0118] Store the shelf distribution model and shelf item information for each scenario in the database.

[0119] In the implementation device of the present invention, the positioning module 603 is used for:

[0120] Obtain the location number of the location where the target item is located from the shelf item information of the target item;

[0121] Determine the positioning label corresponding to the location number, and send a positioning instruction to the positioning label;

[0122] Receive the coordinate value feedback by the positioning label, and use the coordinate value as the second location information; wherein, the positioning label determines the coordinate value of the location by transmitting a signal to the positioning base station of the target scenario.

[0123] In the implementation device of the present invention, the path planning module 604 is used for:

[0124] Determine the grid map model of the target scenario, and determine the first node corresponding to the first location information and the second node corresponding to the second location information in the grid map model;

[0125] Determine the neighbor nodes adjacent to the first node, use the first node as the starting node and the neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node to the second node based on each current node, so as to screen the target neighbor node with the smallest estimated total cost;

[0126] Determine the other neighbor nodes adjacent to the target neighbor node, use the target neighbor node as the starting node and the other neighbor nodes as the current nodes, and obtain the estimated total cost from the starting node to the second node based on each current node, so as to screen the target other neighbor node with the smallest estimated total cost;

[0127] Repeat the operations of determining the estimated total cost and screening the neighbor node with the smallest estimated total cost until the second node exists among the current nodes, and connect the first node, the determined neighbor nodes and the second node in sequence to obtain the planned path.

[0128] In the implementation device of the present invention, the generation process of the grid map model of the target scenario includes:

[0129] According to the shelf distribution model of the target scenario, determine the passable area and obstacle area of the target scenario, convert the passable area into grid nodes, and convert the obstacle area into grid graphics to obtain the grid map model of the target scenario.

[0130] In the implementation device of the present invention, the path planning module 604 is used for:

[0131] Determine the cost from the starting node to each current node and the heuristic cost from each current node to the second node, and accumulate to obtain the total cost corresponding to each current node.

[0132] In the implementation device of the present invention, the path planning module 604 is used for:

[0133] Send a statistical task to the camera devices in the target scenario to receive the pedestrian flow data of each channel collected by the camera devices;

[0134] Determine the congestion degree of each channel according to the pedestrian flow data of each channel, and perform path planning in combination with the first position information, the second position information and the shelf distribution model.

[0135] In addition, the specific implementation content of the device in the embodiments of the present invention has been described in detail in the above method, so the repeated content will not be described here.

[0136] Figure 7 An exemplary system architecture 700 to which the embodiments of the present invention can be applied is shown, including terminal devices 701, 702, 703, a network 704, and a server 705 (merely examples).

[0137] The terminal devices 701, 702, 703 can be various electronic devices with a display screen and supporting web browsing, installed with various communication client applications. The shopper can use the terminal devices 701, 702, 703 to interact with the server 705 through the network 704 to receive or send messages, etc.

[0138] The network 704 is a medium for providing a communication link between the terminal devices 701, 702, 703 and the server 705. The network 704 can include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0139] The server 705 can be a server that provides various services. For example, it is a background management server that supports the shopping websites browsed by the shopper using the terminal devices 701, 702, 703 (merely an example). The background management server can analyze and process data such as product information query requests received, and feedback the processing results (such as target push information, product information - merely examples) to the terminal devices. It should be noted that the method provided by the embodiments of the present invention is generally executed by the server 705. Correspondingly, the device is generally set in the server 705.

[0140] It should be understood, Figure 7The numbers of the terminal devices, networks, and servers in [the description] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, networks, and servers.

[0141] Reference is made below to Figure 8 , which shows a schematic structural diagram of a computer system 800 of a terminal device suitable for implementing the embodiments of the present invention. Figure 8 The terminal device shown is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0142] As Figure 8 shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage section 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the system 800 are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0143] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed so that a computer program read from it can be installed into the storage section 808 as needed.

[0144] Specifically, according to the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 809 and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-mentioned functions defined in the system of the present invention are executed.

[0145] It should be noted that the computer-readable medium shown in the present invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the above two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0146] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks can occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, as well as the combination of blocks in a block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0147] The modules involved in the embodiments of the present invention can be implemented in software or in hardware. The described modules can also be provided in a processor. For example, it can be described as: a processor includes a receiving module, a determining module, a positioning module, and a path planning module. Among them, the names of these modules do not constitute a limitation on the module itself in some cases. For example, the determining module can also be described as an "acquiring module".

[0148] As another aspect, the present invention also provides a computer-readable medium, which can be included in the device described in the above embodiments; or can exist alone without being assembled into the device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by the device, the device is caused to execute any of the above-described goods location path planning methods.

[0149] The computer program product of the present invention includes a computer program, and the computer program implements the goods location path planning method in the embodiments of the present invention when executed by a processor.

[0150] The above specific embodiments do not limit the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for planning the path of storage locations, characterized in that Including: Receiving item query information, first location information, and target scenario information transmitted by a terminal device; wherein, the first location information is the information located by the terminal device, and the terminal device determines the target scenario according to the first location information; Determining shelf item information and a shelf distribution model corresponding to the target scenario information; Determining a target item that matches the item query information according to the shelf item information, determining the location of the target item, and obtaining second location information of the location; Performing path planning according to the first location information, the second location information, and the shelf distribution model, and returning the planned path and the information of the target item to the terminal device for display.

2. The method according to claim 1, wherein The method further includes: Receiving a shelf distribution model and shelf item information transmitted by the management terminal of each scenario; wherein, the shelf item information includes a location number and item information; Storing the shelf distribution model and shelf item information of each scenario into a database.

3. The method according to claim 1 or 2, characterized in that, The determining the location of the target item and obtaining second location information of the location includes: Obtaining the location number of the location where the target item is located from the shelf item information of the target item; Determining a positioning tag corresponding to the location number, and sending a positioning instruction to the positioning tag; Receiving the coordinate value feedback by the positioning tag, and using the coordinate value as the second location information; wherein, the positioning tag determines the coordinate value of the location by transmitting a signal to a positioning base station of the target scenario.

4. The method according to claim 1, wherein The performing path planning according to the first location information, the second location information, and the shelf distribution model includes: Determining a grid map model of the target scenario, and determining a first node corresponding to the first location information and a second node corresponding to the second location information in the grid map model; Determining neighbor nodes adjacent to the first node, using the first node as the starting node and the neighbor nodes as the current nodes, obtaining an estimated total cost from the starting node to the second node based on each current node, so as to screen a target neighbor node with the minimum estimated total cost; Determining other neighbor nodes adjacent to the target neighbor node, using the target neighbor node as the starting node and the other neighbor nodes as the current nodes, obtaining an estimated total cost from the starting node to the second node based on each current node, so as to screen a target other neighbor node with the minimum estimated total cost; Repeating the operations of determining the estimated total cost and screening the neighbor node with the minimum estimated total cost until the second node exists in the current nodes, and sequentially connecting the first node, the determined neighbor nodes, and the second node to obtain the planned path.

5. The method according to claim 4, wherein The generation process of the grid map model of the target scenario includes: Determining a passable area and an obstacle area of the target scenario according to the shelf distribution model of the target scenario, converting the passable area into grid nodes, and converting the obstacle area into grid graphics to obtain the grid map model of the target scenario.

6. The method according to claim 4 or 5, characterized in that The obtaining an estimated total cost from the starting node to the second node based on each current node includes: Determine the cost from the starting node to each current node and the heuristic cost from each current node to the second node, and accumulate to obtain the total cost corresponding to each current node.

7. The method according to claim 1 or 4, characterized in that, The path planning according to the first position information, the second position information, and the shelf distribution model includes: Send a statistical task to the camera device in the target scenario to receive the pedestrian flow data of each channel collected by the camera device; Determine the congestion degree of each channel according to the pedestrian flow data of each channel, and perform path planning in combination with the first position information, the second position information, and the shelf distribution model.

8. A goods location path planning device, characterized in that, It includes: A receiving module, configured to receive the item query information, the first position information, and the target scenario information transmitted by the terminal device; wherein, the first position information is the information located by the terminal device, and the terminal device determines the target scenario according to the first position information; A determining module, configured to determine the shelf item information and the shelf distribution model corresponding to the target scenario information; A positioning module, configured to determine the target item that matches the item query information according to the shelf item information, determine the location of the target item, and obtain the second position information of the location; A path planning module, configured to perform path planning according to the first position information, the second position information, and the shelf distribution model, and return the planned path and the information of the target item to the terminal device for display.

9. An electronic device, characterized in that, It includes: One or more processors; A storage device, configured to store one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method according to any one of claims 1-7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method according to any one of claims 1-7.

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