A use of an unmanned AGV for stacking and preparing raw tobacco leaves

Abstract

This invention belongs to the technical field of tobacco leaf re-drying equipment, specifically relating to an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves. The AGV has a camera mounted on the fork root, which can identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame. This invention addresses the problem of traditional AGVs blindly stacking tobacco leaves after positioning using map coordinates, assuming the goods are aligned without recognizing the placement of the tobacco frames, leading to stacking failures or safety hazards. This invention uses a camera mounted on the fork root to identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame, and adjusts the posture of the frames to be stacked based on the identification results until they are aligned before stacking, thus avoiding safety hazards caused by inaccurate stacking posture.

Description

Technical Field

[0001] This invention belongs to the technical field of tobacco leaf re-drying equipment, specifically relating to the use of an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves. Background Technology

[0002] The processing of raw tobacco leaves by tobacco leaf processing and re-drying enterprises is a crucial step in ensuring the quality of raw tobacco. However, due to the influence of natural climate and other factors on tobacco production, the yield and quality of tobacco leaves are unstable. Therefore, storing raw tobacco leaves is the main means to alleviate the contradiction between tobacco supply and demand, but this also places high demands on the warehousing of tobacco leaf processing and re-drying enterprises.

[0003] Traditional tobacco leaf storage in re-drying plants, due to the large quantity of raw materials and limited space, typically employs a four-layer pallet stacking system. The pallet stacking and raw material preparation processes are primarily completed manually using forklifts and manual trailers, along with manual record-keeping. This process inevitably requires a significant amount of manual labor on-site, posing high safety requirements for the storage area. In actual stacking and preparation, when using forklifts for pallet handling, the limited height of the forklifts and the relatively fixed seating angle severely restrict the operator's visibility. This frequently results in pallets falling during handling or stacking operations, seriously impacting the safety of personnel and the raw tobacco leaves. Clearly, this traditional stacking and preparation method also suffers from low efficiency and inaccurate manual record-keeping.

[0004] To address at least one of the above problems, this invention is proposed. Summary of the Invention

[0005] To address the problem that traditional AGVs rely on map coordinates for positioning and then blindly stack tobacco frames, resulting in stacked goods that are assumed to be aligned without recognizing and adjusting the placement of the frames, ultimately leading to stacking failures or safety hazards, this invention provides an unmanned AGV for raw tobacco stacking and preparation. Innovatively, a camera is installed at the base of the AGV's forks to identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame. Based on the identification results, the posture of the frames to be stacked is adjusted until the tobacco frames are aligned before stacking, thus avoiding safety hazards caused by inaccurate frame stacking postures.

[0006] The technical solution adopted in this invention is:

[0007] This invention provides an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves. The unmanned AGV is equipped with a camera at the base of its forks, which can identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame.

[0008] Preferably, there are two cameras, which are symmetrically installed at both ends of the fork root of the AGV trolley.

[0009] Preferably, the unmanned AGV also includes a vision-assisted detection mechanism.

[0010] Preferably, the visual assistance detection mechanism is an auxiliary detection camera, which is installed above the manual processing area.

[0011] The Assisted Detection (Bright Eyes) system, as part of the AGV global scheduling system, is based on deep learning image recognition technology. By configuring cameras and related hardware, it enables real-time detection of warehouse locations. Leveraging big data and AI intelligent algorithms, the system can effectively identify and track objects such as goods, pallets, AGVs, and operators in the warehouse, and feed this information back to the user's warehouse management system and AGV control system in real time, assisting AGVs in unmanned operations.

[0012] Preferably, the camera is installed at a height of 5-12 meters above the manual processing area.

[0013] Preferably, a laser detector is also provided at the root of the forks of the AGV, the laser detector being located between the two cameras, and the laser detector is used to sense whether the smoke frame is in the correct position.

[0014] Preferably, the unmanned AGV further includes at least a drive unit, a control motherboard, a fork lifting mechanism, a fork angle adjustment mechanism, and an RFID reader; the drive unit is used to drive the unmanned AGV to move; the control motherboard is used to process the signals fed back by the camera at the fork end of the unmanned AGV and its auxiliary detection camera, and accordingly control the unmanned AGV to complete the corresponding actions; the fork lifting mechanism can lift or lower the frame placed on the fork in a direction perpendicular to the horizontal plane; the fork angle adjustment mechanism can adjust the angle of the frame by adjusting the fork angle; the RFID reader is used to read the RFID information of the cigarette frame.

[0015] Preferably, the unmanned AGV also includes a 3D laser positioning and navigation mechanism.

[0016] Preferably, the method for using the unmanned AGV (Automated Guided Vehicle) for raw tobacco stacking and preparation includes the following steps:

[0017] The stacking process includes the following steps:

[0018] Step (1): The unmanned AGV identifies the position of the empty pallet using the vision-assisted detection mechanism and sends the signal back to the control motherboard;

[0019] Step (2): The control motherboard controls the unmanned AGV to travel to the empty pallet position according to the pre-stored map coordinates based on the signal from the vision-assisted detection mechanism.

[0020] Step (3): After the unmanned AGV moves to the empty pallet position, the control motherboard controls the unmanned AGV forks to place the first frame according to the map coordinates.

[0021] Starting from the second frame, two cameras at the base of the forks of the unmanned AGV identify the relative positions of the four feet of the upper frame and / or the four uprights of the lower frame. Based on the identified positions, the frame posture is adjusted and placed in the corresponding placement area. If the frame posture is adjusted twice consecutively and the feet and / or the uprights of the lower frame are still not aligned, the control board will determine that the frame to be placed is an abnormal smoke frame, and then control the unmanned AGV to transport the abnormal smoke frame to the abnormal smoke frame placement area.

[0022] The preparation of materials includes the following steps:

[0023] Step (1): Control the main board to prepare the preset target, plan the route for the unmanned AGV according to the pre-stored map coordinates, and control the unmanned AGV to move to the pallet position where the waiting frame is located.

[0024] Step (2): The mainboard controls the unmanned AGV trolley to insert its forks into the bottom of the frame according to the predetermined scheduling plan;

[0025] Step (3): The laser detector at the root of the fork of the unmanned AGV detects the crossbeam and the upright of the smoke frame.

[0026] When the frame is in the correct position, the machine-optical detector will send a signal to the control motherboard, and the control motherboard will control the unmanned AGV forks to remove the goods.

[0027] When the frame is shifted or tilted, the machine-optical detector will send a signal to the control board. The control board will then control the unmanned AGV forks to automatically correct the frame. Once the frame is in the correct position, the control board will control the unmanned AGV forks to remove the goods.

[0028] Step (4): Control the mainboard to move the unmanned AGV and place the frame according to the preset position.

[0029] The beneficial effects of this invention are:

[0030] 1. This invention innovatively installs a camera at the base of the forks of the AGV trolley, which can identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame. Based on the identification results, the posture of the frames to be stacked is adjusted until the frames are aligned and stacked, thus avoiding safety hazards caused by inaccurate stacking posture.

[0031] 2. When the unmanned AGV vehicle of the present invention picks up goods, the laser scanner first identifies the position of the goods. If there is any displacement or tilting, the fork posture will be automatically adjusted to align and pick up the goods.

[0032] 3. The unmanned AGV of this invention supports automatic deviation correction. In the handover area between the unmanned AGV and the manual, or in the storage location, when the manual placement of the frame is offset or the manual movement of the frame, the unmanned AGV can automatically correct its deviation to complete the frame handling operation. There is no need to deploy positioning pins or other auxiliary tools on the ground, ensuring the cleanliness of the work area.

[0033] 4. The unmanned AGV of this invention automatically identifies RFID information and verifies the data with the information system, thereby improving the accuracy of data during operation;

[0034] 5. Based on the identification of the frame fence by the unmanned AGV, data traceability can be realized through interaction with the information system.

[0035] Instruction manual illustrations

[0036] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of frame offset in a specific embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the stacking of frames in a specific embodiment of the present invention. Detailed Implementation

[0039] The present invention will be further described in detail below with reference to embodiments, but this is not intended to limit the invention. Any modifications or improvements made based on the teachings of the present invention fall within the protection scope of the present invention. Where specific techniques or conditions are not specified in the embodiments, they shall be performed in accordance with the techniques or conditions described in the literature in the art or in accordance with the product manual.

[0040] Example 1

[0041] This embodiment provides an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves. The unmanned AGV has a camera installed at the base of its forks, which can identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame.

[0042] Preferably, there are two cameras, which are symmetrically installed at both ends of the fork root of the AGV trolley.

[0043] Preferably, the unmanned AGV also includes a vision-assisted detection mechanism.

[0044] Preferably, the visual assistance detection mechanism is an auxiliary detection camera, which is installed above the manual processing area.

[0045] The camera is installed at a height of 5-12 meters above the manual processing area.

[0046] The AGV is also equipped with a laser detector at the base of its forks. The laser detector is located between the two cameras and is used to detect whether the smoke frame is in the correct position.

[0047] The unmanned AGV also includes at least a drive unit, a control motherboard, a fork lifting mechanism, a fork angle adjustment mechanism, and an RFID reader; the drive unit is used to drive the unmanned AGV to move; the control motherboard is used to process the signals fed back by the camera at the fork end of the unmanned AGV and its auxiliary detection camera, and accordingly control the unmanned AGV to complete the corresponding actions; the fork lifting mechanism can lift or lower the frame placed on the fork in a direction perpendicular to the horizontal plane; the fork angle adjustment mechanism can adjust the angle of the frame by adjusting the fork angle; the RFID reader is used to read the RFID information of the cigarette frame.

[0048] The unmanned AGV also includes a 3D laser positioning and navigation mechanism.

[0049] The method for using the unmanned AGV (Automated Guided Vehicle) for raw tobacco stacking and preparation includes the following steps:

[0050] The stacking process includes the following steps:

[0051] Step (1): The unmanned AGV identifies the position of the empty pallet using the vision-assisted detection mechanism and sends the signal back to the control motherboard;

[0052] Step (2): The control motherboard controls the unmanned AGV to travel to the empty pallet position according to the pre-stored map coordinates based on the signal from the vision-assisted detection mechanism.

[0053] Step (3): After the unmanned AGV moves to the empty pallet position, the control motherboard controls the unmanned AGV forks to place the first frame according to the map coordinates.

[0054] Starting from the second box, such as Figure 1 As shown, two cameras at the base of the forks of the unmanned AGV (Automated Guided Vehicle) identify the relative positions of the four feet of the upper frame and / or the four uprights of the lower frame, and adjust the frame posture according to the identified positions to place it in the corresponding placement area; for example... Figure 2 As shown, if the frame posture is adjusted twice in a row and the foot cup and / or the lower frame still cannot be aligned, the control board will determine that the frame to be placed is an abnormal smoke frame, and then control the unmanned AGV to transport the abnormal smoke frame to the abnormal smoke frame placement area.

[0055] The preparation of materials includes the following steps:

[0056] Step (1): Control the main board to prepare the preset target, plan the route for the unmanned AGV according to the pre-stored map coordinates, and control the unmanned AGV to move to the pallet position where the waiting frame is located.

[0057] Step (2): The mainboard controls the unmanned AGV trolley to insert its forks into the bottom of the frame according to the predetermined scheduling plan;

[0058] Step (3): The laser detector at the root of the fork of the unmanned AGV detects the crossbeam and the upright of the smoke frame.

[0059] When the frame is in the correct position, the machine-optical detector will send a signal to the control motherboard, and the control motherboard will control the unmanned AGV forks to remove the goods.

[0060] When the frame is shifted or tilted, the machine-optical detector will send a signal to the control board. The control board will then control the unmanned AGV forks to automatically correct the frame. Once the frame is in the correct position, the control board will control the unmanned AGV forks to remove the goods.

[0061] Step (4): Control the mainboard to move the unmanned AGV and place the frame according to the preset position.

[0062] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made to it in form and detail without departing from the scope defined by the claims of this application; the dimensions described in the drawings and embodiments are not related to the specific physical object and are not used to limit the protection scope of this application. The physical dimensions can be selected and changed according to actual needs.

Claims

1. An unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves, characterized in that, The unmanned AGV is equipped with a camera at the base of its forks. The camera can identify the relative positions of the four feet of the upper frame and the four uprights of the lower frame.

2. The use of an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves according to claim 1, characterized in that, The number of cameras is two, and the two cameras are symmetrically installed at both ends of the fork root of the AGV trolley.

3. The use of an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves according to claim 1, characterized in that, The unmanned AGV also includes a vision-assisted inspection mechanism.

4. The use of the unmanned AGV trolley according to claim 1 for stacking and preparing raw tobacco leaves, characterized in that, The visual assistance detection mechanism is an auxiliary detection camera, which is installed above the manual processing area.

5. The use of an unmanned AGV (Automated Guided Vehicle) as described in claim 1 for stacking and preparing raw tobacco leaves, characterized in that, The camera is installed at a height of 5-12 meters above the manual processing area.

6. The use of an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves according to claim 1, characterized in that, The AGV is also equipped with a laser detector at the base of its forks. The laser detector is located between the two cameras and is used to detect whether the smoke frame is in the correct position.

7. The use of an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves according to claim 1, characterized in that, The unmanned AGV also includes at least a drive unit, a control motherboard, a fork lifting mechanism, a fork angle adjustment mechanism, and an RFID reader; the drive unit is used to drive the unmanned AGV to move; the control motherboard is used to process the signals fed back by the camera at the fork end of the unmanned AGV and its auxiliary detection camera, and accordingly control the unmanned AGV to complete the corresponding actions; the fork lifting mechanism can lift or lower the frame placed on the fork in a direction perpendicular to the horizontal plane; the fork angle adjustment mechanism can adjust the angle of the frame by adjusting the fork angle; the RFID reader is used to read the RFID information of the cigarette frame.

8. The use of an unmanned AGV (Automated Guided Vehicle) for stacking and preparing raw tobacco leaves according to claim 1, characterized in that, The unmanned AGV also includes a 3D laser positioning and navigation mechanism.

9. The use of an unmanned AGV (Automated Guided Vehicle) as described in claim 1 for stacking and preparing raw tobacco leaves, characterized in that, The method for using the unmanned AGV (Automated Guided Vehicle) for raw tobacco stacking and preparation includes the following steps: The stacking process includes the following steps: Step (1): The unmanned AGV identifies the position of the empty pallet using the vision-assisted detection mechanism and sends the signal back to the control motherboard; Step (2): The control motherboard controls the unmanned AGV to travel to the empty pallet position according to the pre-stored map coordinates based on the signal from the vision-assisted detection mechanism. Step (3): After the unmanned AGV moves to the empty pallet position, the control motherboard controls the unmanned AGV forks to place the first frame according to the map coordinates. Starting from the second frame, two cameras at the base of the forks of the unmanned AGV identify the relative positions of the four feet of the upper frame and / or the four uprights of the lower frame. Based on the identified positions, the frame posture is adjusted and placed in the corresponding placement area. If the frame posture is adjusted twice consecutively and the feet and / or the uprights of the lower frame are still not aligned, the control board will determine that the frame to be placed is an abnormal smoke frame, and then control the unmanned AGV to transport the abnormal smoke frame to the abnormal smoke frame placement area. The preparation of materials includes the following steps: Step (1): Control the main board to prepare the preset target, plan the route for the unmanned AGV according to the pre-stored map coordinates, and control the unmanned AGV to move to the pallet position where the waiting frame is located. Step (2): The mainboard controls the unmanned AGV trolley to insert its forks into the bottom of the frame according to the predetermined scheduling plan; Step (3): The laser detector at the root of the fork of the unmanned AGV detects the crossbeam and the upright of the smoke frame. When the frame is in the correct position, the machine-optical detector will send a signal to the control motherboard, and the control motherboard will control the unmanned AGV forks to remove the goods. When the frame is shifted or tilted, the machine-optical detector will send a signal to the control board. The control board will then control the unmanned AGV forks to automatically correct the frame. Once the frame is in the correct position, the control board will control the unmanned AGV forks to remove the goods. Step (4): Control the mainboard to move the unmanned AGV and place the frame according to the preset position.

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