AGV glass handling device

Abstract

The application relates to an AGV glass carrying device and belongs to the technical field of AGV carrying devices. In order to solve the technical problem of how to improve production efficiency according to the distribution of employees, the intelligent allocation of glass transportation is realized. The technical scheme points that a detection device collects thermal imaging data and panoramic image data of a factory, performs data analysis and processing, identifies the profiles and distribution of workers, determines discrete area workstations and distance area workstations, adjusts the number of glasses on the corresponding workstations through the different properties of the workstations, and effectively controls the workloads of the employees. The application has the effects of intelligent adjustment of the transportation quantity, improvement of work rationality and sustainable workability, improvement of employee satisfaction, and effective control of the workloads of the employees.

Description

Technical Field

[0001] This application relates to the technical field of AGV handling devices, and in particular to an AGV glass handling device. Background Technology

[0002] AGV is an abbreviation for Automated Guided Vehicle. Equipped with electromagnetic or optical automatic guidance devices, it can travel along a predetermined guide path and has safety protection and various transfer functions. It is typically used in the automotive, equipment, and other assembly industries to transport materials to assembly areas, replacing manual labor.

[0003] Within the industry, AGVs are widely used to transport materials from storage areas to assembly areas to improve production efficiency and reduce labor costs. This type of glass handling equipment typically includes an AGV cart, a handling device, and a control unit. The AGV cart travels along a preset path within the assembly area, the handling device picks up the glass from its original position and places it onto the AGV cart, and the control unit controls the AGV cart's travel path and the handling device's actions. In this way, fast, accurate, and safe glass handling can be achieved.

[0004] The existing technology still has the following technical problems: it does not take into account the number of employees at each workstation in the workshop. The workload and stress of employees will affect their mood and efficiency. When the workload of employees is too heavy, their work efficiency will continue to decrease. When the workload of employees is too light, human resources will be wasted. Different glass processing procedures at each workstation result in different working environments. The number of people at each workstation also varies. In order to improve production efficiency, it is necessary to effectively and intelligently allocate the transportation of glass. Summary of the Invention

[0005] In view of the shortcomings (problems) of the prior art described above, in order to improve work productivity, taking into account work intensity and work environment, and to increase output and quality, this application provides an AGV glass handling device.

[0006] To achieve the above and other related objectives, this application adopts the following technical solution:

[0007] An AGV glass handling device includes: a glass handling device comprising multiple handling trolleys located within a factory and moving according to a prescribed route, for transporting glass to different workstation areas within the factory;

[0008] The reconnaissance device includes a thermal imaging acquisition unit installed on the transport trolley and an image acquisition unit installed in the factory. The thermal imaging acquisition unit is used to acquire the heat distribution at the workstation, and the image acquisition unit is used to acquire panoramic images of workers at the workstation in the factory.

[0009] The central control unit connects the glass handling device and the detection device. The central control unit includes a facial recognition unit and a control unit. The facial recognition unit analyzes work images acquired by the image acquisition unit and determines the employee distribution status based on human features in the workstation area images. The employee distribution status includes both clustered and discrete states.

[0010] When the central control unit determines that the distribution of employees at the workstation is in a clustered state, it defines this workstation area as a clustered workstation, and the control unit controls the number of glass transported to this clustered workstation by the transport trolley as the cluster number.

[0011] And / or, when the central control unit determines that the distribution of employees at the workstation is discrete, this workstation area is defined as a discrete workstation, the control unit controls the transport trolley to move to the discrete workstation, obtains detailed images of the discrete workstation, and determines the workload of a single person based on human thermal imaging. The control unit controls the transport trolley to transport the number of glass items to this clustered workstation as a discrete number.

[0012] As can be seen from the above technical solution, by acquiring panoramic images of the factory and analyzing and processing the image data, the distribution of workers' work can be identified, the nature of work at each workstation can be defined, and it can be determined which workstation areas have a large number of workers and which areas have more dispersed workers. In this way, the spatial layout of different workers can be adjusted to intelligently configure the control and dispatching of transport vehicles and adjust the amount of glass transported. This allows for a comprehensive consideration of employee work efficiency, work mood, and workload, thereby improving the overall sustainability of the factory's work mode and contributing to long-term work efficiency improvement.

[0013] Optionally, the human face recognition unit acquires the number of human body contours in the factory panoramic image, the distance between each human body contour and the remaining human body contours, then calculates the average distance between each human body contour and the remaining human body contours, and finally calculates the overall average of the average distances of all human body contours.

[0014] As can be seen from the above technical solution, in actual practice, the smaller the average distance between each worker and the outlines of the remaining workers, the denser the distribution of workers in the factory. Therefore, the average distance between each worker's outline and the outlines of the remaining workers can reliably reflect the distribution of workers in the factory, which is convenient for controlling the number of transport vehicles of each handling trolley according to the distribution status of workers at different workstations.

[0015] Optionally, the facial recognition unit determines the worker distribution status based on the human contours in the panoramic image of the factory, wherein,

[0016] The facial recognition unit compares the currently acquired overall average value in the factory with a preset distance comparison threshold.

[0017] If the comparison result meets the first condition, the facial recognition unit determines that the distribution state is a clustered state.

[0018] If the comparison result meets the second condition, the facial recognition unit determines that the distribution state is discrete.

[0019] The first condition is that the currently acquired overall mean is less than the distance comparison threshold, and the second condition is that the currently acquired overall mean is greater than or equal to the distance comparison threshold.

[0020] As can be seen from the above technical solutions, it is possible to distinguish between clustered and discrete states by comparing data. This comparison method is highly efficient, less prone to errors, and the data processing is simple and efficient.

[0021] Optionally, the control unit determines the aggregation station, wherein,

[0022] The control unit establishes a Cartesian coordinate system with the center of the factory as the origin, determines the coordinates corresponding to the center point of each worker's profile, determines the maximum horizontal coordinate, minimum horizontal coordinate, maximum vertical coordinate, and minimum vertical coordinate, constructs a rectangular area with the distance between the lines connecting the maximum and minimum horizontal coordinates as the width, and the distance between the lines connecting the maximum and minimum vertical coordinates as the length, and defines the rectangular area as the clustered workstation.

[0023] As can be seen from the above technical solutions, data processing efficiency can be further improved, thereby enhancing the reliability of model construction.

[0024] Optionally, the control unit determines discrete workstations, wherein,

[0025] The control unit constructs several circular regions with the center of each human body outline in the factory panoramic image as the origin and a preset length threshold as the radius, and defines the circular regions as discrete regions.

[0026] Optionally, the control unit controls the mobile carts to move to discrete workstations one by one, so that only a single mobile cart exists in each discrete workstation.

[0027] Optionally, based on human thermal imaging, the workload of a single person can be determined, wherein the human thermal imaging temperature is directly proportional to the workload and inversely proportional to the glass transport volume, and the glass transport volume of the transport trolley can be controlled.

[0028] Optionally, the control unit uses human thermal imaging to assist in determining the human body contour and employee workload, identifying and calibrating feature points of the head, arms, waist, and leg joints of the human figure, and judging the amount of exercise based on the amount and amplitude of movement changes.

[0029] As can be seen from the above technical solutions, thermal imaging technology is very mature. This method can further assist in judging employees, and the data collected in this way can improve the data collected on human body contours. Moreover, it can reveal the thermal distribution of employees, which is directly proportional to their workload. This can further accurately judge the employees' working conditions and adjust their workload appropriately.

[0030] Optionally, the transport trolley includes a glass mother frame, a glass sub-frame, and an intelligent forklift. The glass mother frame includes a base frame, two side frames, and a top frame. The two side frames respectively fix and support the sides of the base frame and the top frame. The middle part of the two side frames is a folding structure. Reinforcing rods are provided at the diagonal of the side frames. An entrance is formed on the front side of the mother frame. The diagonal of the back of the mother frame is reinforced by another reinforcing rod. The base frame has multiple rail sections for sliding connection of the glass sub-frame.

[0031] The glass sub-frame includes a frame, front wheels, and rear wheels. A front wheel is fixedly installed at the bottom front end of the frame, and a rear wheel is installed at the bottom rear end of the frame. The rear wheel is slidably connected to the rail section. A support rod is provided on the bottom of the frame for placing the glass. The glass rests against the side of the frame, and the top of the frame is fitted into the limiting strip of the glass mother frame. The intelligent forklift transports the glass mother frame and / or the glass sub-frame.

[0032] Optionally, the glass mother frame and the glass daughter frame are provided with a locking structure that locks them together, and the glass daughter frame is provided with a handle.

[0033] As can be seen from the above technical solutions, the intelligent forklift can move intelligently and collect data, as well as transport glass quantities. The combined structure of the glass mother frame and glass daughter frames can rationally allocate and control the quantity of glass being handled. Furthermore, this structure can improve the efficiency of glass handling and effectively protect the glass, reducing the likelihood of breakage during transportation.

[0034] In summary, this application includes at least one of the following beneficial technical effects:

[0035] 1. In terms of intelligence, it can collect environmental data from the factory, analyze and process image data after collection using image technology, obtain the distribution of employees, classify the distribution of personnel at different workstations, and effectively control the transportation volume of the handling carts based on the distribution of personnel in the factory. It can change the transportation volume in a more reasonable way to adapt to the transportation volume under different employee working conditions, thereby improving employee job satisfaction, rationally allocating resources to reduce workload, and carrying out sustainable planning for employee work to improve the rationality and sustainability of work.

[0036] 2. In terms of structure, it can effectively handle multiple pieces of glass of various specifications and can transport glass with great reliability, which is convenient to operate and improves the convenience and labor saving of the work.

[0037] 3. In terms of data acquisition and analysis, improving the efficiency of data judgment and processing output can enhance operational reliability, reduce the likelihood of system downtime, and facilitate glass handling under different factory conditions. Attached Figure Description

[0038] Figure 1 This is a structural schematic diagram of an embodiment of this application;

[0039] Figure 2 This is a block diagram illustrating an embodiment of this application;

[0040] Figure 3 This is an assembled side view of the glass mother frame and glass daughter frame according to an embodiment of this application;

[0041] Figure 4 This is an assembled rear view of the glass mother frame and glass daughter frame according to an embodiment of this application.

[0042] Explanation of key component reference numerals:

[0043] 100. Glass handling device; 110. Handling trolley; 200. Detection device; 210. Thermal imaging acquisition unit; 220. Image acquisition unit; 300. Central control unit; 310. Facial recognition unit; 320. Control unit; 4. Main glass frame; 41. Base frame; 42. Side frame; 43. Top frame; 44. Folding structure; 45. Reinforcing rod; 46. Rail section; 47. Limiting strip; 5. Sub-glass frame; 51. Frame body; 52. Front wheel; 53. Rear wheel; 54. Locking structure; 55. Handle; 6. Intelligent forklift; 7. Glass plate. Detailed Implementation

[0044] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0045] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be changed at will, and the layout of the components may also be more complex.

[0046] The specific embodiments of this application will be further described below with reference to the accompanying drawings.

[0047] Example:

[0048] This application discloses an AGV glass handling device, with reference to... Figure 1 and Figure 2 As shown, it includes the following structure:

[0049] The glass handling unit 100 includes multiple handling trolleys 110 located within the factory and moving along predetermined routes to transport glass to different workstation areas within the factory. (Reference) Figure 1 As shown, the transport trolley 110 has an automatic walking function and moves according to the prescribed route based on the factory map to realize the transport of goods. This has already been achieved on general AGV trolleys, so it will not be elaborated on in detail. The following only elaborates on the technical solutions related to this application.

[0050] The reconnaissance device 200 includes a thermal imaging acquisition unit 210 mounted on a transport trolley 110 and an image acquisition unit 220 installed within the factory. The thermal imaging acquisition unit 210 is used to acquire thermal distribution data at workstations, and the image acquisition unit 220 is used to acquire panoramic images of workers at the factory workstations. The image acquisition unit 220 can specifically be implemented using a camera. The thermal imaging acquisition unit 210 can specifically be implemented using a thermal imaging camera to acquire data. The installation location of the thermal imaging acquisition unit 210 is not specifically limited; in one embodiment, reference can be made to... Figure 1 It is installed on the top of the transport trolley 110 shown.

[0051] The central control unit 300 connects the glass handling device 100 and the detection device 200. The central control unit 300 includes a facial recognition unit 310 and a control unit 320. The facial recognition unit 310 analyzes the work images acquired by the image acquisition unit 220 and determines the employee distribution status based on the human characteristics in the workstation area image. The employee distribution status includes clustered and discrete states.

[0052] When the central control unit 300 determines that the distribution of employees at the workstation is in a clustered state, it defines this workstation area as a clustered workstation. The control unit 320 controls the transport trolley 110 to transport the number of glass pieces to this clustered workstation as the cluster number. The cluster number is the workload of employees at a workstation for glass production after calculation, and can be set according to the actual situation.

[0053] Other solutions can be derived from the above scheme.

[0054] In the above scheme, derivative scheme one can further add judgment conditions, namely:

[0055] When the central control unit 300 determines that the distribution of employees at the workstation is discrete, it defines this workstation area as a discrete workstation. The control unit 320 controls the transport trolley 110 to move to the discrete workstation, acquires detailed images of the discrete workstation, and determines the workload of a single person based on human thermal imaging. The control unit 320 controls the transport trolley 110 to transport the number of glass pieces to this clustered workstation as a discrete number. The discrete number is the workload of an employee at a workstation for glass, which can be set according to the actual situation.

[0056] It should be noted that the clustering number is always greater than the discrete number. Furthermore, both the clustering number and the discrete number can be adjusted appropriately for each iteration.

[0057] Derivative Option Two

[0058] An AGV glass handling device includes: a glass handling device 100, which includes multiple handling trolleys 110 located within the factory and moving according to a prescribed route to transport glass to different work areas within the factory.

[0059] The detection device 200 includes a thermal imaging acquisition unit 210 installed on the transport trolley 110 and an image acquisition unit 220 installed in the factory. The thermal imaging acquisition unit 210 is used to collect the heat distribution on the workstation, and the image acquisition unit 220 is used to collect images of workers working in the panoramic workstation of the factory.

[0060] The central control unit 300 connects the glass handling device 100 and the detection device 200. The central control unit 300 includes a facial recognition unit 310 and a control unit 320. The facial recognition unit 310 analyzes work images acquired by the image acquisition unit 220 and determines the employee distribution status based on human features in the workstation area images. The employee distribution status includes both clustered and discrete states.

[0061] When the central control unit 300 determines that the distribution of employees at the workstation is discrete, it defines this workstation area as a discrete workstation. The control unit 320 controls the transport trolley 110 to move to the discrete workstation, obtains detailed images of the discrete workstation, and determines the workload of a single person based on human thermal imaging. The control unit 320 controls the transport trolley 110 to transport the number of glass items to this clustered workstation as a discrete number.

[0062] As can be seen from the above technical solution analysis, by acquiring panoramic images of the factory and analyzing and processing the image data, the distribution of workers' work can be identified, the nature of work at each workstation can be defined, and it can be determined which workstation areas have a large number of workers and which areas have more dispersed workers. In this way, the spatial layout of different workers can be adjusted, and the control and dispatching trolleys 110 can be intelligently configured to adjust the amount of glass transported. This allows for a comprehensive consideration of employee work efficiency, work mood, and workload, thereby improving the overall sustainability of the factory's work mode and contributing to long-term work efficiency improvement.

[0063] Alternatively, based on the above scheme, it can also be implemented as follows:

[0064] The facial recognition unit 310 acquires the number of human silhouettes in the panoramic image of the factory, the distance between each human silhouette and the remaining human silhouettes, and then calculates the average distance between each human silhouette and the remaining human silhouettes. Finally, it calculates the overall average of the average distances of all human silhouettes. In practice, the smaller the average distance between each worker and the remaining worker silhouettes, the denser the distribution of workers in the factory. Therefore, the average distance between each worker silhouette and the remaining worker silhouettes can reliably reflect the distribution of workers in the factory, facilitating subsequent control of the transport quantity of each handling cart 110 based on the distribution of workers at different workstations or work positions.

[0065] The facial recognition unit 310 determines the worker distribution status based on human contours in a panoramic factory image. Specifically, the facial recognition unit 310 compares the currently acquired overall average value in the factory with a preset distance comparison threshold. If the comparison result meets a first condition, the facial recognition unit 310 determines the distribution status to be clustered; if the comparison result meets a second condition, the facial recognition unit 310 determines the distribution status to be discrete. The first condition is that the currently acquired overall average value is less than the distance comparison threshold, and the second condition is that the currently acquired overall average value is greater than or equal to the distance comparison threshold. This method of distinguishing between clustered and discrete states by comparing data is highly efficient, less prone to errors, and involves simple and efficient data processing.

[0066] The above scheme is further implemented as follows: Control unit 320 determines the clustering workstations. Specifically, control unit 320 establishes a Cartesian coordinate system with the factory center as the origin, and determines the coordinates corresponding to the center points of each worker's profile. It also determines the maximum and minimum abscissas, maximum and minimum ordinates, and constructs a rectangular area with the distance between the lines connecting the maximum and minimum abscissas as the width and the distance between the lines connecting the maximum and minimum ordinates as the length. This rectangular area is then designated as the clustering workstation. This further improves data processing efficiency and enhances the reliability of the model construction.

[0067] The control unit 320 determines discrete workstations. Specifically, it constructs several circular regions with the center of each human figure's outline in the factory panoramic image as the origin and a preset length threshold as the radius, defining these circular regions as discrete regions. The control unit 320 controls the mobile carts to move to the discrete workstations one by one, ensuring that only a single mobile cart exists within each workstation. Based on human thermal imaging, the workload of a single person is determined, with the human thermal imaging temperature being directly proportional to the workload and the glass transport volume inversely proportional, controlling the glass transport volume of the transport cart 110. The control unit 320 uses human thermal imaging to assist in determining the human figure outline and employee workload, identifying and calibrating feature points of the head, arms, waist, and leg joints, and judging the magnitude of movement based on the amount and amplitude of motion changes. Thermal imaging technology is very mature; this method further assists in judging employees, and the data collected in this way can improve the data collected on the human figure outline. Furthermore, it can reveal the employee's thermal distribution, which is directly proportional to their workload, thus enabling more accurate judgment of the employee's working condition and appropriate adjustment of workload.

[0068] On the other hand, it can be combined Figure 1 , Figure 3 and Figure 4The transport trolley 110 includes a glass mother frame 4, glass sub-frames 5, and an intelligent forklift 6. The glass mother frame 4 includes a base frame 41, two side frames 42, and a top frame 43. The two side frames 42 respectively fix and support the sides of the base frame 41 and the top frame 43. The middle part of the two side frames 42 is a folding structure 44. Reinforcing rods 45 are provided at opposite corners of the side frames 42. An entrance is formed on the front side of the mother frame, and the opposite corners of the back of the mother frame are reinforced by another reinforcing rod 45. The base frame 41 has multiple rail sections 46 for sliding connection of the glass sub-frames 5. Various hinge structures can be used to realize the folding structure 44. In this way, it has convenient functions for disassembly, assembly, and transportation of the glass mother frame 4.

[0069] The glass sub-rack 5 includes a frame 51, a front wheel 52, and a rear wheel 53. A front wheel 52 is fixedly installed at the front bottom of the frame 51, and a rear wheel 53 is installed at the rear bottom of the frame 51. The rear wheel 53 is slidably connected to the rail section 46. A support rod is provided at the bottom of the frame 51 for placing the glass. The glass rests against the side of the frame 51. The top of the frame 51 is fitted into the limiting strip 47 of the glass mother frame 4. The intelligent forklift 6 transports the glass mother frame 4 and / or the glass sub-rack 5. The glass mother frame 4 and the glass sub-rack 5 are equipped with interlocking locking structures 54, and the glass sub-rack 5 is equipped with a handle 55. The locking structure 54 can be implemented using bolt fastening or other locking methods to fix and assemble the glass mother frame 4 and the glass sub-rack 5. This modular assembly structure can adapt to the handling of glass of different quantities and specifications, improving the reliability and stability of glass transportation. During the glass transport process, it is always tilted to reduce the probability of the glass plate 7 shaking.

[0070] Therefore, the solution proposed in this application utilizes an intelligent forklift 6 for intelligent movement, data collection, and glass quantity transportation. The combined structure of the glass mother frame 4 and glass daughter frame 5 enables reasonable allocation and control of the glass handling quantity. Furthermore, this structure improves the efficiency of glass handling and effectively protects the glass, reducing the likelihood of breakage during transportation.

[0071] In summary, the analysis shows that, in terms of intelligence, the system can collect environmental data from the factory, analyze and process image data to obtain employee distribution information, categorizing the distribution of personnel at different workstations. Based on this distribution, the system effectively controls the transport trolley 110 to manage transport volume, adjusting it in a reasonable way to adapt to different employee work conditions, thereby improving employee satisfaction, rationally allocating resources to reduce workload, and enabling sustainable planning for employee work, thus enhancing the rationality and sustainability of work. Structurally, the system can effectively transport multiple glass items of various specifications with high reliability, facilitating operation and improving work convenience and labor-saving. Regarding data acquisition and analysis, the system improves the efficiency of data processing output, enhancing operational reliability, reducing downtime, and adapting to different factory conditions for glass handling.

[0072] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent changes made to the structure, shape, and principle of this application should be covered within the protection scope of this application.

Claims

1. An AGV glass handling device, characterized in that, include: The glass handling device (100) includes multiple handling trolleys (110) located within the factory and moving according to a prescribed route to transport glass to different work areas within the factory; The detection device (200) includes a thermal imaging acquisition unit (210) installed on the transport trolley (110) and an image acquisition unit (220) installed in the factory. The thermal imaging acquisition unit (210) is used to collect the heat distribution on the workstation, and the image acquisition unit (220) is used to collect images of workers working in the panoramic workstation of the factory. The central control unit (300) is connected to the glass handling device (100) and the detection device (200). The central control unit (300) includes a human face recognition unit (310) and a control unit (320). The human face recognition unit (310) analyzes the working images acquired by the image acquisition unit (220) and determines the employee distribution status based on the human body characteristics in the workstation area image. The employee distribution status includes a clustered state and a discrete state. When the central control unit (300) determines that the distribution of employees at the workstation is in a clustered state, it defines this workstation area as a clustered workstation, and the control unit (320) controls the transport trolley (110) to transport the number of glass pieces to this clustered workstation as the cluster number; And / or, when the central control unit (300) determines that the distribution of employees on the workstation is in a discrete state, the workstation area is defined as a discrete workstation, the control unit (320) controls the transport trolley (110) to move to the discrete workstation, obtains detailed images on the discrete workstation, and determines the workload of a single person based on human thermal imaging, the control unit (320) controls the transport trolley (110) to transport the number of glass items to this clustered workstation as a discrete number; The human face recognition unit (310) acquires the number of human body contours in the factory panoramic image, the distance between each human body contour and the remaining human body contours, and then calculates the average distance between each human body contour and the remaining human body contours. Finally, it calculates the overall average of the average distance between all human body contours. The human face recognition unit (310) determines the worker distribution status based on the human body contours in the factory panoramic image, wherein, The facial recognition unit (310) compares the currently acquired overall average value in the factory with a preset distance comparison threshold. If the comparison result meets the first condition, the human face recognition unit (310) determines that the distribution state is a clustered state; If the comparison result meets the second condition, the human face recognition unit (310) determines that the distribution state is discrete. The first condition is that the currently acquired overall mean is less than the distance comparison threshold, and the second condition is that the currently acquired overall mean is greater than or equal to the distance comparison threshold.

2. The AGV glass handling device according to claim 1, characterized in that: The control unit (320) determines the aggregation station, wherein, The control unit (320) establishes a plane rectangular coordinate system with the center of the factory as the origin, and determines the coordinates corresponding to the center point of each worker's outline. It determines the maximum horizontal coordinate, minimum horizontal coordinate, maximum vertical coordinate, and minimum vertical coordinate, constructs a rectangular area with the distance between the line connecting the maximum horizontal coordinate and the minimum horizontal coordinate as the width, and the distance between the line connecting the maximum vertical coordinate and the minimum vertical coordinate as the length, and determines the rectangular area as the gathering work station.

3. The AGV glass handling device according to claim 2, characterized in that: The control unit (320) determines the discrete workstations, wherein, The control unit (320) constructs several circular regions with the center of each human body outline in the factory panoramic image as the origin and a preset length threshold as the radius, and determines the circular regions as discrete regions.

4. The AGV glass handling device according to claim 3, characterized in that: The control unit (320) controls the mobile carts to move to discrete workstations one by one, so that only a single mobile cart exists in each discrete workstation.

5. An AGV glass handling device according to claim 4, characterized in that: Based on human thermal imaging, the workload of a single person is determined, wherein the human thermal imaging temperature is directly proportional to the workload and the glass transport volume is inversely proportional, and the glass transport volume of the transport trolley (110) is controlled.

6. The AGV glass handling device according to claim 5, characterized in that: The control unit (320) uses human thermal imaging to assist in the human body contour and employee workload, identifies and marks the feature points of the head, arms, waist, and leg joints of the human figure, and judges the amount of exercise based on the amount and amplitude of movement changes.

7. The AGV glass handling device according to claim 1, characterized in that: The transport trolley (110) includes a glass mother frame (4), a glass sub-frame (5), and an intelligent forklift (6). The glass mother frame (4) includes a base frame (41), two side frames (42), and a top frame (43). The two side frames (42) respectively fix and support the sides of the base frame (41) and the top frame (43). The middle part of the two side frames (42) is a folding structure (44). A reinforcing rod (45) is provided on the diagonal of the side frame (42). An entrance is formed on the front side of the mother frame. The diagonal of the back of the mother frame is reinforced by another reinforcing rod (45). The base frame (41) has multiple rail sections (46) for the glass sub-frame (5) to slide and connect. The glass sub-frame (5) includes a frame (51), a front wheel (52), and a rear wheel (53). A front wheel (52) is fixedly installed at the bottom front end of the frame (51), and a rear wheel (53) is installed at the bottom rear end of the frame (51). The rear wheel (53) is slidably connected to the rail section (46). A support rod is provided on the bottom of the frame (51) for placing the glass. The glass rests against the side of the frame (51), and the top of the frame (51) is fitted in the limiting strip (47) of the glass mother frame (4). The intelligent forklift (6) transports the glass mother frame (4) and / or the glass sub-frame (5).

8. An AGV glass handling device according to claim 7, characterized in that: The glass mother frame (4) and the glass sub-frame (5) are provided with locking structures (54) that lock together, and the glass sub-frame (5) is provided with handles (55).

Images