Method for positioning warehouse containers based on visual perception of forklifts using internet of things

Abstract

The application provides a warehouse goods cabinet positioning method based on visual perception of a forklift in an Internet of Things, and comprises the following steps: S1, data configuration is performed for warehouse layout, and a two-dimensional code is deployed in the warehouse; S2, a visual perception calculation and communication device is deployed at the forklift equipment; S3, the forklift performs two-dimensional code detection analysis and processing when driving in the warehouse; and S4, the last position of the goods cabinet and the real-time position of the forklift are identified. The application can accurately position the storage position of the goods cabinet and the real-time position of the forklift, and solves the problem of difficult warehouse positioning and goods searching.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of Internet of Things application and visual perception, indoor positioning application, in particular to a method for positioning warehouse containers based on visual perception of Internet of Things forklifts. BACKGROUND

[0002] At present, the existing information system of most small and medium-sized warehouses cannot accurately grasp the storage position of inventory goods and containers, and the intelligent management level cannot keep up, resulting in a large discount in the space utilization rate and the warehouse efficiency of small and medium-sized warehouses. In order to solve the problem that the existing small and medium-sized warehouses cannot accurately grasp the storage position of inventory goods and containers, and the intelligent management level cannot keep up, the warehouse capacity utilization rate is improved, and the warehouse capacity is improved. The way of storing goods in a non-fixed position and a non-fixed container stacking type shelf is adopted to improve the warehouse operation efficiency. However, the existing information system of the warehouse cannot accurately grasp the storage position of inventory goods and containers, and the intelligent management level cannot keep up, resulting in low space utilization rate and low warehouse efficiency.

[0003] Therefore, the purpose of the present application is to provide a method for detecting and warning the operation safety of a lifting system based on Internet of Things perception, in particular to a method for positioning warehouse containers based on visual perception of Internet of Things forklifts, which can accurately position the storage position of containers and the real-time position of forklifts, and completely solve the problem of difficult search for goods in the warehouse. SUMMARY

[0004] The present application provides a method for positioning warehouse containers based on visual perception of Internet of Things forklifts, which can accurately position the storage position of containers and the real-time position of forklifts, and solve the problem of difficult search for goods in the warehouse.

[0005] The present application adopts the following technical solutions.

[0006] The method for positioning warehouse containers based on visual perception of Internet of Things forklifts comprises the following steps:

[0007] Step S1: data configuration is performed on the warehouse layout, and a two-dimensional code is deployed in the warehouse;

[0008] Step S2: a visual perception computing and communication device is deployed at the forklift equipment;

[0009] Step S3: the forklift performs two-dimensional code detection analysis and processing when driving in the warehouse;

[0010] Step S4: the last position of the container and the real-time position of the forklift are identified.

[0011] The step S1 comprises the following steps:

[0012] Step S101: a polygon boundary line of a warehouse top view is configured;

[0013] Step S102: Select the reference point in the warehouse plan view, configure the longitude and latitude of the reference point, and configure the longitude offset x = |180 / (π*Re*cos(latitude*π / 180))| and the latitude offset y = 180 / (π*Re) per meter near the reference point, where π is the approximate value of 3.1415926535897932385, and Re is the approximate value of 6371004 meters.

[0014] Step S103: In the warehouse plan view, a series of horizontal and vertical lines are used to form a ruler, and the warehouse boundary is divided into a plurality of 1 meter*1 meter square grids. The intersection points of the horizontal and vertical lines contained in the warehouse are numbered, and the number is saved in correspondence with the horizontal and vertical coordinates of the ruler;

[0015] Step S104: Generate a two-dimensional code for the number, and paste or paint a pattern with a size of 20cm*20cm on the corresponding intersection point.

[0016] Step S201: Deploy a vehicle-mounted power supply module at the rear of the forklift truck;

[0017] Step S202: Deploy a rearward scanning identification calculation and communication module at the top of the rear of the forklift truck;

[0018] Step S203: Deploy an RFID identification module at the front of the forklift truck, and set the identification range to 30cm;

[0019] Step S204: Set the warehouse configuration cabinet length l, width w, and RFID card number. Paste the RFID card with the same number on the forklift truck RFID card identification template at the same height position on the two long sides of the cabinet.

[0020] Step S205: Configure a rearward scanning camera on the forklift truck, with a position height h, a camera view direction angle γ, and a camera view horizontal angle range θ h , vertical angle range θ v .

[0021] Step S3 includes the following steps:

[0022] Step S301: The rearward scanning camera captures real-time video and takes a photo every second to scan any two-dimensional code number. According to the number, the horizontal and vertical coordinates (x1, y1) of the corresponding ruler are queried;

[0023] Step S302: According to the rearward scanning camera capturing real-time video, the direction of the two-dimensional code in the photo taken every second is calculated to calculate the forklift truck offset angle θ. θ is the angle from the due east direction clockwise to the vector direction from the tail of the forklift truck to the head.

[0024] Step S303: Calculate the horizontal angle α and the vertical angle β between the center point of the two-dimensional code and the camera view direction, where the horizontal angle α ≈ θ h *00 h / CD, the vertical angle β ≈ θ v *00v / AB;

[0025] Step S304: Calculate the horizontal and vertical coordinates (x, y) of the camera vertical position, where the horizontal distance between the camera and the center point of the two-dimensional code is distance = h * tag(β + γ) / cos(α);

[0026] x = x1 + distance * sin(θ); y = y1 - distance * cos(θ);

[0027] Step S305: Identify the RFID card number id within 30 cm using the RFID identification module, and return empty if not identified;

[0028] Step S306: Upload the forklift number no, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id, and current time t to the data center through the IoT network.

[0029] The step S4 includes the following steps:

[0030] Step S401: According to the reported horizontal and vertical coordinates (x, y) of the forklift camera and the reference point latitude and longitude, calculate the latitude and longitude (X, Y) of the forklift rear camera position, where X = logitude + x * Δx, Y = latitude + y * Δy;

[0031] Step S402: When the RFID card number is not empty, query the cabinet width w according to the RFID card number id, and calculate the center latitude and longitude (X1, Y1) of the cabinet according to the reported horizontal and vertical coordinates (x, y) and the reference point latitude and longitude, the forklift length l, the forklift offset angle θ, and the cabinet width w,

[0032] Where

[0033]

[0034] Step S403: According to the calculated center latitude and longitude (X1, Y1) of the cabinet and the number of other cabinets existing in the database at the storage point, calculate the layer number n where the cabinet is located.

[0035] In step S1, when the two-dimensional code is pasted or printed, the top is aligned with true north; the RFID card is matched with the position of the forklift RFID identification module at the pasting position of the cabinet, so that when the forklift fork exists, the corresponding RFID card number can be read;

[0036] When the forklift successfully connects to the network service or data update, the data of the camera height and the angle of view are synchronized to the cache in the forklift visual perception computing communication device, and all data of the intersection number corresponding to the scale horizontal and vertical coordinates are synchronized to the cache in the forklift visual perception computing communication device, so that once loading is realized and multiple uses are achieved.

[0037] In step S4, the horizontal and vertical coordinates (x, y) of the forklift (camera), the longitude and latitude of the reference point, and the longitude and latitude offset (Δx, Δy) per meter near the reference point are calculated to calculate the longitude and latitude (X, Y) of the rear camera of the forklift, and further obtain the longitude and latitude and direction information of the forklift.

[0038] In step S2, the reading range of the RFID identification module for the RFID card is within 30 cm, the RFID identification module is arranged in the middle position of the forklift fork, and when the fork is placed on the cabinet, the RFID identification module can identify the RFID card number on the cabinet. When the fork is lowered and leaves the cabinet, the RFID card of the cabinet leaves the reading range of the RFID identification module.

[0039] In step S3, the rear camera installed on the forklift is used to identify and obtain the two-dimensional code, the relative position of the camera and the offset angle of the forklift are obtained according to the direction of the two-dimensional code and the position in the figure, the current forklift transported cabinet is identified through the RFID, and the forklift number, vertical position horizontal and vertical coordinates of the camera, forklift direction, RFID card number, and current time are sent to the service module of the platform layer through the IoT network. The service module calculates and analyzes the longitude and latitude of the forklift and the longitude and latitude of the cabinet and the number of placed layers, and finally realizes the positioning of the final storage position of the cabinet and the real-time positioning of the forklift.

[0040] The method uses an Internet of Things-based forklift visual perception warehouse cabinet positioning system, which includes a perception layer, a network layer, a platform layer, and an application layer. Specifically,

[0041] The perception layer: the functions include collecting and reporting the forklift number, relative position coordinates (x, y), forklift offset angle, cabinet corresponding RFID card number, current time t, and other information.

[0042] The network layer: the functions include transmitting the data obtained by the perception layer to the platform layer as an information channel, supporting the forklift to access WIFI, 2G / 3G / 4G / 5G, and NB-IoT wireless access, and supporting local area network networking mode and wide area network networking mode.

[0043] Platform layer: its functions include responsible for data configuration management, receiving the perception layer collection reported information and analysis processing, platform layer includes the corresponding function module of RFID card management, cabinet management, warehouse information management, two-dimensional code management, goods corresponding to cabinet management, forklift terminal management, warehouse identification processing, warehouse identification processing, move identification processing, its deployment in the remote center room, cloud computing center, or deployment in the near-end service computing unit;

[0044] Application layer: its functions include the results of signal analysis and processing identification on the platform layer, according to the analysis of the acquisition of cabinet storage location, forklift real-time position, start the corresponding application to query the goods storage cabinet and cabinet location and show on the warehouse map, real-time display forklift position on the warehouse map, query forklift historical track, query to obtain cabinet warehouse, move time, operation forklift and corresponding historical track.

[0045] The forklift visual perception warehouse cabinet positioning system based on Internet of Things, its working process includes the following steps:

[0046] Step A, data acquisition, preliminary analysis, calculation and upload, including the following steps:

[0047] Step A1, the forklift rear camera collects picture signal, and the RFID device identifies the current cabinet number at the forklift fork;

[0048] Step A2, analyze and calculate the horizontal and vertical coordinates of the camera vertical position, and the forklift offset angle;

[0049] Step A3, upload the forklift number, camera vertical position horizontal and vertical coordinates, forklift offset angle, RFID card number, current time t to data center message queue.

[0050] Step B, forklift position recognition, including the following steps:

[0051] Step B1, the forklift position recognition module subscribes and receives the message queue message in real time, and analyzes the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id;

[0052] Step B2, get the reference point longitude and latitude, and the longitude and latitude offset (Δx, Δy) of each meter near the reference point;

[0053] Step B3, calculate the forklift rear camera position longitude and latitude (X, Y);

[0054] Step B4, the forklift current position information is stored in the database, and the content includes camera position longitude and latitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id;

[0055] Step B5, the forklift current position information is cached, and the cache information content includes camera position longitude and latitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and the RFID card number id of the container;

[0056] Step C, container position recognition, comprising the following steps:

[0057] Step C1, the container position recognition module subscribes and receives the messages of the message queue in real time, and analyzes to obtain the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id;

[0058] Step C2, according to whether the RFID card number in the forklift message content at t time is empty, read whether the RFID card number in the previous cache message of the forklift is empty;

[0059] Step C3, when the RFID card number of the forklift this time is empty, and the previous RFID card number is not empty, it represents that the forklift unloads the container, according to the current forklift position, it is judged whether the forklift is in the warehouse area, if yes, it represents that the container is out of the warehouse, otherwise, it is in the warehouse or moves the container, and the container position state is updated and saved.

[0060] Step C4, when the RFID card number of the forklift this time is not empty, and the previous RFID card number is empty, it represents that the forklift loads the container event, and the container loading event is recorded and saved.

[0061] The application can accurately position the container storage position and the real-time position of the forklift, and completely solve the problem of difficult warehouse positioning and searching of goods.

[0062] Compared with the prior art, the application has the following beneficial effects:

[0063] (1) The positioning of the application is accurate, and the anti-interference ability is strong

[0064] In a conventional environment: the positioning accuracy error is less than 10 cm. The coordinate values (X1, Y1, unit: cm) of the center point of the container can be displayed on the platform.

[0065] In special environments: for example, if there is a small area of ​​dirt, water stains, or paper scraps on the ground of about 20cm*20cm, it will not affect the positioning, and the positioning accuracy error will still be kept within 10cm; for example, if there is illuminance interference, the illuminance can be adjusted to 30 lux, 20 lux, and 10 lux using a curtain, and the positioning accuracy error will still be kept within 10cm.

[0066] (2) This invention is visual and traceable. The current status of the warehouse is visualized. The distribution of warehouse containers and historical operation records can be viewed at any time through the positioning software platform. It also includes positioning trajectory, operation process records, etc.

[0067] (3) The implementation of this invention is flexible and can be deployed in a variety of ways. It requires fewer visual sensing devices and RFID identification devices, and has the characteristics of low cost and high reliability.

[0068] (4) The present invention is low in cost and simple to maintain, which can significantly reduce the various costs of daily operation and maintenance of warehouse positioning system, and bring advantages such as low cost, high accuracy and fast response. Attached Figure Description

[0069] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0070] Appendix Figure 1 This is a schematic diagram illustrating the principle of the visual positioning method according to a preferred embodiment of the present invention;

[0071] Appendix Figure 2 This is a schematic diagram of the deployment points of the forklift vision perception computing and communication device according to a preferred embodiment of the present invention;

[0072] Appendix Figure 3 This is a schematic diagram of the system structure of a preferred embodiment of the present invention;

[0073] Appendix Figure 4 This is a schematic diagram of the method flow of a preferred embodiment of the present invention;

[0074] Appendix Figure 5 This is a schematic diagram of the present invention, which uses a series of horizontal and vertical lines to form a ruler in a top view of a warehouse, dividing the warehouse boundary into multiple square grids of 1 meter by 1 meter. Detailed Implementation

[0075] As shown in the figure, the method for locating warehouse containers based on IoT forklift visual perception includes the following steps;

[0076] Step S1: Configure data for the warehouse layout and deploy QR codes in the warehouse;

[0077] Step S2: Deploy visual perception computing and communication equipment at the forklift equipment;

[0078] Step S3: Forklift performs two-dimensional code detection analysis and processing when driving in the warehouse;

[0079] Step S4: Identify the final position of the container and the real-time position of the forklift.

[0080] The step S1 includes the following steps:

[0081] Step S101: Configure the polygon boundary line of the warehouse top view;

[0082] Step S102: Select the reference point in the warehouse top view, configure the longitude and latitude of the reference point, and configure the longitude offset x = |180 / (π*Re*cos(latitude*π / 180))| and the latitude offset y = 180 / (π*Re) near the reference point, where π is the approximate value of 3.1415926535897932385, and Re is the approximate value of 6371004 meters.

[0083] Step S103: In the warehouse top view, use a series of horizontal and vertical lines to form a ruler, divide the warehouse boundary into a plurality of 1 meter*1 meter square grids, number the intersection points of the horizontal and vertical lines contained in the warehouse, and save the number corresponding to the horizontal and vertical coordinates of the ruler data;

[0084] Step S104: Generate a two-dimensional code for the number, and paste or paint a pattern with a size of 20cm*20cm on the corresponding intersection point.

[0085] Step S201: Deploy a vehicle-mounted power supply module at the rear of the forklift;

[0086] Step S202: Deploy a rearward scanning identification calculation communication module at the top of the rear of the forklift;

[0087] Step S203: Deploy an RFID identification module at the front of the forklift, and set the identification range to 30cm;

[0088] Step S204: Set the warehouse configuration container length l, width w, and RFID card number, and paste the same number of RFID cards on the two long sides of the container corresponding to the same height position of the forklift RFID card identification template;

[0089] Step S205: Configure a rearward scanning code camera on the forklift, with a position height h, a camera view direction angle γ, and a camera view horizontal angle range θ h , vertical angle range θ v .

[0090] Step S3 includes the following steps:

[0091] Step S301: The backward scanning camera captures real-time video and takes a photo every second to scan any two-dimensional code number. The corresponding scale horizontal and vertical coordinates (x1, y1) are queried according to the number.

[0092] Step S302: According to the backward scanning camera capturing real-time video, the direction of the two-dimensional code in the photo taken every second is used to calculate the forklift offset angle θ. θ is the angle from the due east direction clockwise to the vector direction from the forklift tail to the forklift head.

[0093] Step S303: The horizontal and vertical angles α and β between the center point of the two-dimensional code and the camera view direction are calculated, where the horizontal angle α ≈ θ h *00 h The vertical angle β ≈ θ v *00v / AB;

[0094] Step S304: The horizontal and vertical coordinates (x, y) of the vertical position of the camera are calculated, where the horizontal distance between the camera and the center point of the two-dimensional code is distance = h * tag (β + γ) / cos (α);

[0095] x = x1 + distance * sin (θ); y = y1 - distance * cos (θ);

[0096] Step S305: The RFID identification module identifies the RFID card number id within 30 cm. If no identification is made, it returns empty.

[0097] Step S306: The forklift number no, the horizontal and vertical coordinates (x, y) of the vertical position of the camera, the forklift offset angle θ, the RFID card number id, and the current time t are uploaded to the data center through the IoT network.

[0098] The step S4 includes the following steps:

[0099] Step S401: According to the reported horizontal and vertical coordinates (x, y) of the forklift camera and the reference point latitude and longitude, the forklift backward camera position latitude and longitude (X, Y) is calculated, where X = logitude + x * Δx, Y = latitude + y * Δy;

[0100] Step S402: When the RFID card number is not empty, the container width w is queried according to the RFID card number id. According to the reported horizontal and vertical coordinates (x, y) and the reference point latitude and longitude, the forklift length l, the forklift offset angle θ, and the container width w, the container center latitude and longitude (X1, Y1) is calculated,

[0101] where

[0102]

[0103] Step S403: According to the calculated container center longitude and latitude (X1, Y1) and the number of other containers in the storage point in the database, the layer number n where the container is located is calculated.

[0104] In step S1, when the two-dimensional code is pasted or printed, the top is aligned with the true north; the RFID card is matched with the position of the forklift RFID identification module in the container, so that the corresponding RFID card number can be read when the container is on the forklift fork;

[0105] When the forklift successfully connects to the network service or data updates, the data of the camera height and the angle of view are synchronized to the cache in the forklift visual perception computing communication device; and all data of the intersection number corresponding to the scale horizontal and vertical coordinates are synchronized to the cache in the forklift visual perception computing communication device, realizing one-time loading and multiple use.

[0106] In step S4, according to the calculated horizontal and vertical coordinates (x, y) of the forklift (camera), the longitude and latitude of the reference point, and the longitude and latitude offset (Δx, Δy) per meter near the reference point, the longitude and latitude (X, Y) of the rear camera position of the forklift are calculated, and the longitude and latitude and direction information of the forklift are further obtained.

[0107] In the step S2, the reading range of the RFID identification module for the RFID card is within 30 cm, and the RFID identification module is arranged in the middle position of the forklift fork. When the container is placed on the fork, the RFID identification module can identify the RFID card number on the container. When the fork lowers the container and leaves, the RFID card of the container is out of the reading range of the RFID identification module.

[0108] In step S3, the rear camera installed on the forklift identifies and obtains the two-dimensional code, obtains the relative position of the camera and the offset angle of the forklift according to the direction of the two-dimensional code and the position in the figure, identifies the current container carried by the forklift through the RFID, and sends the forklift number, vertical position horizontal and vertical coordinates of the camera, forklift direction, RFID card number, and current time to the service module of the platform layer through the IoT network. The service module calculates and analyzes the longitude and latitude of the forklift and the longitude and latitude of the container and the storage layer number, and finally realizes the positioning of the final storage position of the container and the real-time positioning of the forklift.

[0109] The method uses an Internet of Things-based forklift visual perception warehouse container positioning system, which includes a perception layer, a network layer, a platform layer, and an application layer. Specifically:

[0110] The perception layer: the functions include collecting and reporting the forklift number, relative position coordinates (x, y), forklift offset angle, container corresponding RFID card number, current time t, and other information.

[0111] Network layer: the functions include transmitting the data obtained by the perception layer to the platform layer as an information channel, supporting the forklift to access WIFI, 2G / 3G / 4G / 5G, NB-IoT, and supporting local area network and wide area network networking modes;

[0112] Platform layer: the functions thereof include being responsible for data configuration management, receiving the information collected and reported by the perception layer and analyzing and processing, the platform layer includes function modules corresponding to RFID card management, cabinet management, warehouse information management, two-dimensional code management, goods corresponding to cabinet management, forklift terminal management, warehouse entry identification processing, warehouse exit identification processing, and warehouse transfer identification processing, and is deployed in a remote central computer room, a cloud computing center, or a near-end service computing unit;

[0113] Application layer: the functions thereof include, based on the results of signal analysis and processing identification in the platform layer, starting corresponding applications to query the goods storage cabinet and cabinet position and display on the warehouse map according to the obtained cabinet storage position and forklift real-time position, displaying the forklift position on the warehouse map in real time, querying the forklift historical track, querying the cabinet warehouse entry, exit and transfer time, and operating the forklift and corresponding historical track.

[0114] The working process of the forklift visual perception warehouse cabinet positioning system based on the Internet of Things includes the following steps.

[0115] Step A, data acquisition, preliminary analysis, calculation and uploading, including the following steps:

[0116] Step A1, the forklift rearward camera collects picture signals, and the RFID device identifies the current cabinet number at the forklift fork;

[0117] Step A2, analyze and calculate the horizontal and vertical coordinates of the camera vertical position and the forklift offset angle;

[0118] Step A3, upload the forklift number, camera vertical position horizontal and vertical coordinates, forklift offset angle, RFID card number and current time t to the data center message queue.

[0119] Step B, forklift position identification, including the following steps:

[0120] Step B1, the forklift position identification module subscribes and receives the messages of the message queue in real time, and analyzes to obtain the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id;

[0121] Step B2, obtain the reference point longitude and latitude, and the longitude and latitude offset (Δx, Δy) of each meter near the reference point;

[0122] Step B3, calculate the latitude and longitude (X, Y) of the forklift rear camera position;

[0123] Step B4, store the forklift current position information in the database, including the camera position latitude and longitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id;

[0124] Step B5, cache the forklift current position information, including the camera position latitude and longitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id of the container;

[0125] Step C, container position recognition, including the following steps;

[0126] Step C1, the container position recognition module subscribes and receives messages from the message queue in real time, and parses the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id;

[0127] Step C2, according to the state of whether the RFID card number in the forklift message content at time t is empty, read whether the RFID card number in the previous cache message of the forklift is empty;

[0128] Step C3, when the RFID card number of this forklift is empty and the previous RFID card number is not empty, it represents that the forklift unloads the container, and according to the current forklift position, it is judged whether the forklift is in the outbound area. If it is in the outbound area, it represents that the container is outbound, otherwise it is inbound or relocation, and the container position state is updated and saved.

[0129] Step C4, when the RFID card number of this forklift is not empty and the previous RFID card number is empty, it represents a forklift loading container event, and records and saves the container loading event.

[0130] Embodiment:

[0131] In this embodiment, when the two-dimensional code is pasted or printed, the upper part is aligned with true north.

[0132] In this embodiment, the deployment density of the two-dimensional code can be adjusted appropriately according to the engineering cost budget and positioning accuracy requirements.

[0133] In this embodiment, the RFID card needs to be consistent with the height of the forklift RFID identification device, and is pasted in the middle of the container, so as to ensure that the corresponding RFID card number can be read when the forklift fork exists.

[0134] In this embodiment, flexible networking can be implemented at the network layer. Each forklift visual perception computing and communication device can be connected to the platform layer directly through a 3G / 4G / 5G link, communicate with the platform layer through an Internet of Things gateway, communicate with the platform layer through WIFI, or even use the three networking modes according to the network signal state of different points.

[0135] Preferably, in this embodiment, in order to quickly analyze and calculate the horizontal and vertical coordinates of the camera, and timely query the camera height and the angle of view, the data of the camera height and the angle of view are synchronized to the cache in the forklift visual perception computing and communication device when the forklift successfully connects to the service or data is updated.

[0136] Preferably, in this embodiment, in order to quickly find the horizontal and vertical coordinates of the scale corresponding to the two-dimensional code number, avoid repeatedly loading and reading the related configuration table, and ensure low latency of the platform layer service, the data of the horizontal and vertical coordinates of the scale corresponding to the two-dimensional code number are synchronized to the cache in the forklift visual perception computing and communication device when the forklift successfully connects to the service or data is updated, and the data is loaded once and used multiple times.

[0137] The visual positioning method principle diagram is shown in FIG. 1. Figure 1 The principle diagram includes the following contents.

[0138] (1) Calculate the horizontal and vertical angles α and β of the center point of the two-dimensional code and the camera view direction.

[0139] (2) Calculate the offset angle θ of the forklift according to the direction of the two-dimensional code in the photo captured in the real-time video captured by the backward scanning camera every second.

[0140] (3) Calculate the horizontal and vertical coordinates (x, y) of the vertical position of the camera according to the camera height h, the horizontal and vertical angles α and β of the camera view direction, and the corresponding coordinates (x1, y1) of the two-dimensional code.

[0141] (4) Calculate the longitude and latitude (X, Y) of the position of the backward camera of the forklift according to the horizontal and vertical coordinates (x, y) of the forklift (camera) calculated in the previous step, the longitude and latitude of the reference point (logitude, latitude), and the longitude and latitude offset (Δx, Δy) of each meter near the reference point. Thus, the longitude and latitude and direction information of the forklift can be obtained.

[0142] The forklift visual perception computing and communication device deployment point diagram is shown in FIG. 2. Figure 2 The diagram includes the following contents.

[0143] (5) The vehicle-mounted power supply module is deployed near the seat at the rear of the forklift.

[0144] (6) Deploy a backward scanning identification computing communication module at the top of the vehicle rear;

[0145] (7) Deploy an RFID identification module at the front of the forklift.

[0146] The system structure diagram, as shown in Figure 3 , includes the following contents:

[0147] (1) The system implemented in this embodiment is divided into four layers: a perception layer, a network layer, a platform layer, and an application layer. Among them, the perception layer and the platform layer are the core of the entire system.

[0148] (2) The perception layer mainly completes the collection and reporting of forklift number, relative position coordinates (x, y), forklift offset angle, corresponding RFID card number of the container, current time t, and other information.

[0149] (3) The network layer mainly serves as an information channel to transmit the data obtained by the perception layer to the platform layer. It can support wireless access forms such as WIFI, 2G / 3G / 4G / 5G, and NB-IoT, and can support local area network networking and wide area network networking.

[0150] (4) The platform layer is mainly responsible for data configuration management, receiving and analyzing the information collected and reported by the perception layer. It is composed of RFID card management, container management, warehouse information management, two-dimensional code management, goods corresponding container management, forklift terminal management, warehouse entry identification processing, warehouse exit identification processing, and warehouse relocation identification processing. It can be deployed in a remote central computer room, cloud computing center, or a near-end service computing unit.

[0151] (5) The application layer mainly analyzes and processes the results of the platform layer. According to the obtained container storage location and real-time forklift position, the corresponding application can query the goods storage container and container location and display it on the warehouse map, display the forklift position on the warehouse map in real time, query the forklift historical track, query the container warehouse entry and exit relocation time, and operate the forklift and corresponding historical track.

[0152] The method flowchart, as shown in Figure 4 , mainly describes data collection, preliminary analysis, calculation, and uploading, forklift position identification, and container position identification, and does not include preconditions such as data configuration and equipment installation in the entire method. The method flowchart includes the following contents:

[0153] a) Data collection, preliminary analysis, calculation, and uploading

[0154] (1) The rear camera collects picture signals, and the RFID device identifies the current container number.

[0155] (2) Analyze and calculate the horizontal and vertical coordinates of the camera vertical position, and the forklift offset angle;

[0156] (3) Upload the forklift number, camera vertical position horizontal and vertical coordinates, forklift offset angle, RFID card number, and current time t to the data center message queue.

[0157] b) Forklift position recognition

[0158] (4) The forklift position recognition module subscribes and receives messages from the message queue in real time, and obtains the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id, etc. by analysis;

[0159] (5) Obtain the longitude and latitude of the reference point, and the longitude and latitude offset (Δx, Δy) of each meter near the reference point;

[0160] (6) Calculate the longitude and latitude (X, Y) of the forklift rear camera position.

[0161] (7) Store the current forklift position information, including camera position longitude and latitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id;

[0162] (8) Cache the current forklift position information, including camera position longitude and latitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id.

[0163] c) Container position recognition

[0164] (9) The container position recognition module subscribes and receives messages from the message queue in real time, and obtains the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and RFID card number id, etc. by analysis;

[0165] (10) According to the state of whether the RFID card number in the forklift message content at time t is empty, read whether the RFID card number in the previous cache message of the forklift is empty;

[0166] (11) When the RFID card number of this forklift is empty and the previous RFID card number is not empty, it represents that the forklift unloads the container, and according to the current forklift position, it is judged whether the forklift is in the outbound area. In the outbound area, it represents that the container is outbound, otherwise it is inbound or relocation, and the container position state is updated and saved.

[0167] (12) When the forklift current RFID card number is not empty and the previous RFID card number is empty, it represents that the forklift loads the container, and the container loading event is recorded.

[0168] The above merely describes preferred embodiments of the present application, and any equivalent changes and modifications made within the scope of the present application should be included in the scope of the present application.

Claims

1. A method for positioning a warehouse container based on visual perception of a forklift using Internet of Things, characterized in that: Comprising the following steps; Step S1: data configuration for warehouse layout, deploying QR code in warehouse; Step S2: deploying visual perception computing communication device at forklift equipment; Step S3: forklift performs QR code detection analysis and processing when driving in warehouse; Step S4: identify the last position of the container and the real-time position of the forklift, that is, according to the RFID card number id to query the container width w, according to the horizontal and vertical coordinates (x, y) reported after the two-dimensional code analysis in step S3 and the reference point longitude and latitude, the forklift length l, the forklift offset angle θ, the container width w, the center longitude and latitude (X1, Y1) of the container are calculated, wherein According to the calculated horizontal and vertical coordinates (x, y) of forklift camera, the longitude and latitude of reference point (logitude, latitude), the longitude and latitude offset (Δx, Δy) of each meter near the reference point, the position longitude and latitude (X, Y) of forklift rear camera are calculated, and further the forklift longitude and latitude and direction information are obtained.

2. The method for visual perception of warehouse container positioning based on Internet of Things forklifts according to claim 1, characterized in that: The step S1 comprises the following steps: Step S101: configuring the polygon boundary line of warehouse top view; Step S102: selecting the reference point in warehouse top view, configuring the longitude and latitude (logitude, latitude) of reference point, configuring the longitude offset x = |180 / (π*Re*cos(latitude*π / 180))| and latitude offset y = 180 / (π*Re) of each meter near the reference point, wherein π is the circular ratio and Re is the earth radius; Step S103: in warehouse top view, using a series of horizontal and vertical lines to form a scale, dividing the warehouse boundary into a plurality of square grids, numbering the intersection points of horizontal and vertical lines contained in the warehouse, and saving the number corresponding to the horizontal and vertical coordinates of the scale data; Step S104: pasting or painting the pattern of generating QR code on the corresponding intersection point.

3. The method for visual perception of warehouse container positioning by forklift based on Internet of Things according to claim 2, characterized in that: Step S201: deploying vehicle-mounted power module at the rear of forklift; Step S202: deploying rear scanning and identification computing communication module at the top of forklift rear; Step S203: deploying RFID identification module at the front of forklift; Step S204: configuring the length l and width w of warehouse, and the RFID card has a number, and the same number of RFID cards are pasted on the same height position of the two long sides of the container corresponding to the forklift RFID card identification template; Step S205: After the forklift is configured, the scanning camera is arranged in a backward direction, with a position height h, a camera view direction angle γ, and a camera view horizontal angle range θ h , a vertical angle range θ v .

4. The method for visual sensing warehouse container positioning based on Internet of Things forklifts according to claim 3, characterized in that: The step S3 comprises the following steps: Step S301: rearward scanning camera captures real-time video, and any QR code number scanned by photographing every second is intercepted, and the horizontal and vertical coordinates (x1, y1) of the corresponding scale are queried according to the number; Step S302: according to the real-time video captured by the rearward scanning camera, the direction of the QR code in the photograph taken every second is calculated to calculate the offset angle θ of the forklift, θ being the angle from the positive east direction clockwise to the vector direction from the tail of the forklift to the head of the forklift; Step S303: Calculate the horizontal angle a and the vertical angle β between the center point of the two-dimensional code and the camera view direction, wherein the horizontal angle a ≈ θ h *00 h / CD, the vertical angle β ≈ θ v *00 v / AB; Step S304: calculating the horizontal and vertical coordinates (x, y) of the vertical position of the camera, wherein the horizontal distance between the camera and the center point of the QR code is distance = h*tag(β+γ) / cos(α); x = x1 + distance*sin(θ); y = y1-distance*cos(θ); Step S305: identifying the RFID card number id within 30cm by RFID identification module, and returning empty if no RFID card is identified; Step S306: uploading the forklift number no, the horizontal and vertical coordinates (x, y) of the vertical position of the camera, the offset angle θ of the forklift, the RFID card number id and the current time t to the data center through IoT network.

5. The method for visual perception of warehouse container positioning by forklift based on Internet of Things according to claim 4, characterized in that: The step S4 comprises the following steps: Step S401: According to the reported horizontal and vertical coordinates (x, y) of the forklift camera and the reference point latitude and longitude, the forklift rear camera position latitude and longitude (X, Y) is calculated, wherein X = logitude + x * Δx, Y = latitude + y * Δy; Step S402: When the RFID card number is not empty, the center latitude and longitude (X1, Y1) of the container is calculated, Step S403: According to the calculated center latitude and longitude (X1, Y1) of the container and the number of other containers in the database storage point, the layer number n of the container is calculated.

6. The method for visual perception of warehouse container positioning by forklift based on Internet of Things according to claim 5, characterized in that: In step S1, when the two-dimensional code is pasted or printed, the upper part is aligned with the north; the RFID card is matched with the position of the forklift RFID identification module in the container, so that when the forklift fork exists, the corresponding RFID card number can be read; When the forklift successfully connects to the network service or data update, the camera height and the data of the viewing angle are synchronized to the cache in the forklift visual perception calculation communication device; and the intersection number corresponding to the scale horizontal and vertical coordinates of all data are synchronized to the cache in the forklift visual perception calculation communication device, realizing one-time loading and multiple use.

7. The method for visual perception of warehouse container positioning by forklift based on Internet of Things according to claim 6, characterized in that: In the step S2, the reading range of the RFID identification module to the RFID card is within 30cm, the RFID identification module is arranged in the middle position of the forklift fork, and when the fork is put into the container, the RFID identification module can identify the RFID card number on the container. When the fork puts down the container and leaves, the RFID card of the container is out of the reading range of the RFID identification module.

8. The method for visual perception of warehouse container positioning by forklift based on Internet of Things according to claim 5, characterized in that: In step S3, the two-dimensional code is identified and obtained by the rear camera installed on the forklift, the relative position of the camera and the forklift offset angle are obtained according to the direction of the two-dimensional code and the position in the figure, the current container carried by the forklift is identified by the RFID, and the forklift number, camera vertical position horizontal and vertical coordinates, forklift direction, RFID card number and current time are sent to the platform layer service module through the IoT network. The service module calculates and analyzes the forklift latitude and longitude, the container latitude and longitude and the storage layer number, and finally realizes the final storage position positioning of the container and the real-time positioning of the forklift.

9. The method for visual perception of warehouse container positioning by forklift based on Internet of Things according to claim 5, characterized in that: The method uses a forklift visual perception warehouse container positioning system based on Internet of Things, which comprises a perception layer, a network layer, a platform layer and an application layer; specifically: The perception layer: the functions include collecting and reporting the forklift number, relative position coordinates (x, y), forklift offset angle, container corresponding RFID card number, current time t and other information; The network layer: the functions include transmitting the data obtained by the perception layer to the platform layer as an information channel, which supports WIFI, 2G / 3G / 4G / 5G, NB-IoT wireless access of the forklift, and can support local area network networking mode and wide area network networking mode; Platform layer: its functions include responsible for data configuration management, receiving the perception layer to collect and analyze the information reported, platform layer includes the corresponding function modules of RFID card management, cabinet management, warehouse information management, two-dimensional code management, goods corresponding to the cabinet management, forklift terminal management, warehouse identification processing, warehouse identification processing, move identification processing, its deployment in the remote center computer room, cloud computing center, or deployment in the near-end service computing unit; Application layer: its functions include on the platform layer signal analysis and processing identification results, according to the analysis of the acquisition of cabinet storage location, forklift real-time position, start the corresponding application to query the goods storage cabinet and cabinet location and display on the warehouse map, real-time display forklift position on the warehouse map, query forklift historical track, query to obtain the cabinet warehouse, warehouse, move time, operation forklift and corresponding historical track.

10. The method for visual perception of warehouse pallet positioning by forklifts based on Internet of Things according to claim 9, characterized in that: The working process of the forklift visual perception warehouse cabinet positioning system based on Internet of Things Comprise the following steps; Step A, data acquisition, preliminary analysis, calculation and upload, comprising the following steps: Step A1, the forklift rear camera collects picture signal, and the RFID device identifies the current cabinet number at the forklift fork; Step A2, analyze and calculate the horizontal and vertical coordinates of the camera vertical position, the forklift offset angle; Step A3, upload the forklift number, camera vertical position horizontal and vertical coordinates, forklift offset angle, RFID card number, current time t to data center message queue; Step B, forklift position recognition, comprising the following steps; Step B1, the forklift position recognition module subscribes and receives the message queue message in real time, and obtains the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id; Step B2, get the reference point longitude and latitude, the longitude and latitude offset (Δx, Δy) of each meter near the reference point; Step B3, calculate the longitude and latitude (X, Y) of the forklift rear camera position; Step B4, store the forklift current position information into the database, which contains the camera position longitude and latitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id; Step B5, cache the forklift current position information, which contains the camera position longitude and latitude (X, Y), current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, and the RFID card number id of the cabinet; Step C, cabinet position recognition, comprising the following steps; Step C1, the forklift position recognition module subscribes and receives the message queue message in real time, and obtains the current message generation time t, forklift number No, camera vertical position horizontal and vertical coordinates (x, y), forklift offset angle θ, RFID card number id; Step C2, according to the state of whether the RFID card number in the forklift message content at t time is empty, read whether the RFID card number in the previous cache message of the forklift is empty. Step C3, when the forklift this time RFID card number is empty, the previous RFID card number is not empty, which represents that the forklift unloads the container. According to the current forklift position, it is judged whether the forklift is in the outbound area. If it is in the outbound area, it represents that the container is outbound. Otherwise, it is inbound or relocation. The container position state is updated and saved. Step C4, when the forklift this time RFID card number is not empty, the previous RFID card number is empty, which represents that the forklift loads the container event. The container loading event is recorded and saved.

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