Direct-cooling and quick-sealing electric waxberry picking machine based on machine vision

Abstract

Disclosed in the present invention is a direct-cooling and quick-sealing electric waxberry picking machine based on machine vision. The direct-cooling and quick-sealing electric waxberry picking machine comprises: a mechanical claw, which has at least three flexible claw fingers, a pressure sensor being provided on the surface of each flexible claw finger that comes into contact with waxberries, and a collection tube being provided at the center of an enclosure formed by all the flexible claw fingers; an image recognition device, which is configured to perform positioning and ripeness recognition on the waxberries; a carbon dioxide spraying device, which is configured to spray carbon dioxide onto the stems of the waxberries and around the waxberries so as to freeze the stems of the waxberries and lower the surface temperature of the waxberries; a photoelectric sensor, which is configured to detect whether waxberries are discharged through an outlet of the collection tube; a liquid polyurethane foam spraying device, which is configured to wrap liquid polyurethane foam around the waxberries discharged through the outlet of the collection tube; and a conveying device, which is configured to convey the waxberries wrapped with the liquid polyurethane foam outward. Thus, the damage to fruits during picking can be reduced, and the picking efficiency is improved.

Description

Direct cooling and quick sealing electric bayberry picking machine based on machine vision Technical Field

[0001] The present application relates to the technical field of agricultural pickers, and in particular to a direct-cooling and quick-sealing electric bayberry picker based on machine vision. Background Art

[0002] Fruit picking machines are tools that assist manual fruit picking and improve work efficiency. With the rapid development of society and the economy, the mass production and market release of fruit have enriched people's dietary variety and improved their quality of life. However, in most areas of my country, fruit picking still relies primarily on manual labor. Therefore, fruit picking machines with a reasonable structure, improved picking efficiency, and guaranteed fruit quality have become a primary tool. The current bayberry picking machines on the market are mainly grab-type picking machines, as follows:

[0003] The utility model patent with application number 201720142123.8 is a labor-saving electric bayberry picking machine, which includes multiple soft grippers, a gripper body, a gripper bracket and a bayberry picking machine main bracket; the soft gripper is rotatably installed on the gripper body, and the soft gripper is provided with a reset device for opening the soft gripper and a stretching device for closing the soft gripper for picking, the stretching device includes an upper electromagnetic coil, a lower electromagnetic coil and a control switch, the control switch is used to control the current on and off of the upper electromagnetic coil and the lower electromagnetic coil; the upper electromagnetic coil is connected to the soft gripper and can slide up and down relative to the lower electromagnetic coil. When power is on, the upper electromagnetic coil and the lower electromagnetic coil are attracted to each other, and the multiple soft grippers are in a closed state. When power is off, the upper electromagnetic coil and the lower electromagnetic coil are in a separated state under the action of the reset device, and the multiple soft grippers are in an open state.

[0004] However, the opening and closing degree of the picking claws of this picking machine is constant, and cannot be adjusted according to the size of the bayberry fruit. The gripping force cannot be controlled, which can easily cause mechanical damage to the fruit; there is no image recognition function, etc., and the degree of automation is poor; during the picking process, the bayberries in the conveyor basket are subject to vibration and friction. Summary of the Invention

[0005] The purpose of the embodiment of the present application is to provide a direct cooling and quick-sealing electric bayberry picking machine based on machine vision to solve the problem that the existing bayberry picking machinery cannot guarantee the quality of the fruit during the assisted manual picking process, easily causes damage to the fruit, and has a single picking method and cannot effectively improve the picking efficiency.

[0006] According to an embodiment of the present application, a direct cooling and quick-sealing electric bayberry picking machine based on machine vision is provided, comprising:

[0007] A mechanical claw having at least three flexible claw fingers, wherein a pressure sensor is provided on the side of each flexible claw finger in contact with the bayberry, and a collection tube is provided in the center surrounded by all the flexible claw fingers;

[0008] Image recognition device for locating and identifying the maturity of bayberries;

[0009] A carbon dioxide spraying device is used to spray carbon dioxide toward the bayberry fruit stem and around the bayberry to freeze the bayberry fruit stem and reduce the surface temperature of the bayberry;

[0010] A photoelectric sensor is used to detect whether there are bayberries coming out of the collection tube outlet;

[0011] a liquid polyurethane foam spraying device, used for coating the waxberries coming out of the collection pipe outlet with liquid polyurethane foam;

[0012] A transport device for transporting the bayberries wrapped in liquid polyurethane foam, the transport device comprising a conveyor belt mechanism and a fruit carrier fixed to the conveyor belt mechanism, the fruit carrier moving along with the conveyor belt of the conveyor belt mechanism;

[0013] The control processing device is used to control the carbon dioxide spraying device to spray carbon dioxide toward the bayberry stalk and around the bayberry according to the positioning and recognition results of the image recognition device, and then control the mechanical claw to grab the bayberry, and control the gripping force of the mechanical claw according to the pressure signal collected by the pressure sensor. When the bayberry is dragged and picked, the mechanical claw is controlled to release so that the bayberry automatically falls into the collection tube. After the photoelectric sensor detects that the bayberry comes out of the collection tube outlet, the liquid polyurethane foam spraying device is controlled to spray liquid polyurethane foam toward the bayberry. The bayberry wrapped in liquid polyurethane foam then falls onto the fruit tray, and the bayberry is transported out by controlling the transportation device. Beneficial effects

[0014] Existing bayberry picking machines cannot guarantee the quality of the fruit during the assisted manual picking process and are prone to damage. Furthermore, the picking method is limited and cannot effectively improve picking efficiency. The present invention uses carbon dioxide injection to cool the fruit surface and freeze the fruit stem before picking, thereby improving the surface quality of the picked fruit and making it easier to preserve. By utilizing flexible picking claws and integrated thin film pressure sensors on the claws, and cleverly utilizing a deformable multi-rod mechanism, the portable bayberry picking robot's fingers can deform appropriately according to the fruit's shape and control the gripping force according to the size of the bayberry, thereby achieving low-damage fruit grabbing. The picked fruit passes through a collection tube, is wrapped in liquid polyurethane foam, and then falls onto a belt conveyor with a flexible buffer bracket, and is finally transported to a collection device. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG1 is a schematic diagram of a direct-cooling and quick-sealing electric bayberry picking machine based on machine vision according to an exemplary embodiment.

[0016] Fig. 2 is a schematic diagram of a mechanical claw according to an exemplary embodiment.

[0017] FIG3 is a schematic diagram of a second driving mechanism according to an exemplary embodiment.

[0018] Fig. 4 is a schematic diagram of a fruit tray according to an exemplary embodiment.

[0019] FIG5 is a schematic diagram of a liquid polyurethane foam spraying device according to an exemplary embodiment.

[0020] FIG6 is a simplified circuit connection diagram according to an exemplary embodiment.

[0021] FIG7 is a control logic diagram according to an exemplary embodiment.

[0022] The reference numerals in the figures are:

[0023] 1. Mechanical claw; 11. Flexible claw finger; 12. Pressure sensor; 13. First drive mechanism; 131. First motor; 132. Crank; 133. Slider; 134. Connecting rod; 135. Upper fixing plate; 136. Lower fixing plate; 137. Guide rod; 14. Collection tube;

[0024] 2. Image recognition device;

[0025] 3. Carbon dioxide ejection device; 31. First nozzle; 32. First pipeline;

[0026] 4. Photoelectric sensor;

[0027] 5. Liquid polyurethane foam spraying device; 51. Second nozzle; 52. Second pipeline;

[0028] 6. Transport device; 61. Conveyor belt mechanism; 611. Body; 612. Driving pulley; 613. Driven pulley; 614. Second driving mechanism; 615. Belt; 616. Second motor; 617. Coupling; 62. Fruit holder. DETAILED DESCRIPTION

[0029] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings.

[0030] 1 to 5 , an embodiment of the present invention provides a direct cooling and quick-sealing electric bayberry picking machine based on machine vision, comprising: a mechanical claw 1, an image recognition device 2, a carbon dioxide spraying device 3, a photoelectric sensor 4, a liquid polyurethane foam spraying device 5, a transport device 6, and a control and processing device. The mechanical claw 1 has at least three flexible claw fingers 11, and each flexible claw finger 11 is provided with a pressure sensor 12 on the side in contact with the bayberry, and a collection tube 14 is provided around the center of all the flexible claw fingers 11; the image recognition device 2 is used to locate and identify the maturity of the bayberry; the carbon dioxide spraying device 3 is used to spray carbon dioxide onto and around the bayberry stalk to freeze the bayberry stalk and reduce the surface temperature of the bayberry; the photoelectric sensor 4 is used to detect whether there is bayberry coming out of the outlet of the collection tube 14; the liquid polyurethane foam spraying device 5 is used to wrap the bayberry coming out of the outlet of the collection tube 14 with liquid polyurethane foam; the transport device 6 is used to wrap the bayberry wrapped with liquid polyurethane foam The bayberries are transported out, and the transportation device 6 includes a conveyor belt mechanism 61 and a fruit bracket 62 fixed on the conveyor belt mechanism 61, and the fruit bracket 62 moves together with the conveyor belt on the conveyor belt mechanism 61; the control processing device is used to control the carbon dioxide spraying device 3 to spray carbon dioxide toward the bayberry stalk and around the bayberry according to the positioning and recognition results of the image recognition device 2, and then control the mechanical claw 1 to grab the bayberry, and control the gripping force of the mechanical claw 1 according to the pressure signal collected by the pressure sensor 12. When the bayberry is dragged and picked, the mechanical claw 1 is controlled to release so that the bayberry automatically falls into the collection tube 14. After the photoelectric sensor 4 detects that the bayberry comes out of the outlet of the collection tube 14, the liquid polyurethane foam spraying device 5 is controlled to spray liquid polyurethane foam toward the bayberry. The bayberry wrapped in liquid polyurethane foam then falls onto the fruit bracket 62, and the bayberry is transported out by controlling the transportation device 6.

[0031] Existing bayberry picking machines cannot guarantee the quality of the fruit during the auxiliary manual picking process and are prone to damage to the fruit. In addition, the picking method is single and cannot effectively improve the picking efficiency. The present invention uses carbon dioxide to cool the fruit surface and freeze the fruit stem before picking, thereby improving the surface quality of the picked fruit and making it easier to preserve. Because flexible picking claws are used and the thin film pressure sensor 12 integrated on the claws cleverly utilizes a deformable multi-rod mechanism, the fingers of the portable bayberry picking robot can reasonably deform according to the shape of the fruit and can control the gripping force according to the size of the bayberry, thereby achieving low-damage gripping of the fruit. The picked fruit passes through the collection tube 14, is wrapped in liquid polyurethane foam, and then falls into the belt 615 transport device 6 with a flexible buffer bracket, and is finally transported to the collection device.

[0032] In one embodiment, the mechanical claw 1 includes at least three flexible claw fingers 11, a pressure sensor 12, a first drive mechanism 13, and a collection tube 14. The first drive mechanism 13 drives all the flexible claw fingers 11 to close or open simultaneously. A pressure sensor 12 is provided on the side of each flexible claw finger 11 that contacts the bayberry. The entrance of the collection tube 14 is located in the area enclosed by all the flexible claw fingers 11. When the flexible claw fingers perform the picking action, the three evenly distributed claw fingers can evenly transfer pressure to the surface of the bayberry under the control of the pressure sensor, thereby effectively reducing fruit damage. The collection tube is set at the geometric center of the three flexible claw fingers to facilitate the picking of the bayberry into the collection tube.

[0033] In one embodiment, the first drive mechanism 13 includes a crank 132-slider 133 mechanism and a first motor 131. The base end of the flexible claw finger 11 is mounted on the crank 132 of the crank 132-slider 133 mechanism. The first motor 131 drives the slider 133 of the crank 132-slider 133 mechanism to perform telescopic linear motion. When performing a picking operation, the first drive mechanism 13 provides power for the flexible claw finger to perform the picking operation. This drive mechanism has a simple and reliable structure.

[0034] Furthermore, the crank 132 slider 133 mechanism includes a bracket, a crank 132, a slider 133, and a connecting rod 134. The bracket includes an upper fixed plate 135, a lower fixed plate 136, and a plurality of guide rods 137 fixedly connecting the upper fixed plate 135 and the lower fixed plate 136. The flexible claw finger 11 is fixed to the crank 132, one end of the crank 132 is hinged to the upper fixed plate 135, the upper end of the collection tube 14 can be fixed to the upper fixed plate, the other end of the crank 132 is hinged to one end of the connecting rod 134, the other end of the connecting rod 134 is hinged to the slider 133, and the slider 133 is slidably arranged on On the guide rod 137, the first motor 131 is fixed on the lower fixed plate 136, and the middle part of the slider 133 is also provided with an internal thread (a nut can also be installed), and the output shaft of the first motor 131 can be provided with an external thread (or a screw can be fixedly connected to the output shaft of the first motor 131). The internal thread and the external thread are rotationally matched (or the transmission match of the nut and the screw can be achieved). Through the rotation of the first motor 131, the slider 133 is driven to slide up and down along the guide rod 137, and then the connecting rod 134, the crank 132 and the flexible claw finger 11 are driven to move in turn, so that the three flexible claw fingers 11 can grasp and release the action. When the picking action is performed, the first drive mechanism 13 provides power for the flexible claw fingers to perform the picking action. A stepper motor is selected as the power source, and the rotation of the screw is converted into movement of the slider 133, so that the flexible claw fingers are controlled to have a high precision when grasping, thereby reducing fruit damage.

[0035] In one embodiment, the image recognition device 2 includes a camera, which transmits captured images to the control processing device. During the picking process, the processor analyzes the camera image and automatically controls the carbon dioxide spraying device, mechanical gripper, and other devices to perform actions, thereby achieving semi-automated picking and reducing complex control steps. The image recognition device can also determine the maturity of the fruit, thereby reducing the probability of mistaken fruit picking and alleviating the labor intensity of the picker.

[0036] In one embodiment, the carbon dioxide spraying device 3 includes a first nozzle 31, a first pipeline 32, a valve, and a gas cylinder filled with carbon dioxide. The first nozzle 31 is connected to the gas cylinder via the first pipeline 32. The valve is provided on the first pipeline 32 to control the opening and closing of the first pipeline 32. The valve is controlled by the control processing device. When picking, three evenly distributed carbon dioxide nozzles focus carbon dioxide gas directly in front of the bayberry fruit, thereby lowering the fruit surface temperature, freezing the fruit stem, reducing the difficulty of picking, and making the picked fruit easier to preserve.

[0037] In one embodiment, the liquid polyurethane foam spraying device 5 includes a second nozzle 51, a second pipeline 52, a solenoid valve, and a liquid polyurethane tank. The second nozzle 51 is connected to the liquid polyurethane tank via the second pipeline 52. The solenoid valve is disposed on the second pipeline 52 to control the on / off state of the second pipeline 52. The solenoid valve is controlled by the control processing device. During the picking process, a photoelectric sensor located below the picking tube detects falling bayberries, and the liquid polyurethane foam spraying device sprays foam onto the bayberry fruits, covering their surface and thereby reducing collision and friction during transportation.

[0038] In one embodiment, the conveyor belt mechanism 61 includes a body 611, a driving pulley 612, a driven pulley 613, a second drive mechanism 614, and a belt 615. The belt 615 is disposed between the driving pulley 612 and the driven pulley 613, and the second drive mechanism 614 drives the driving pulley 612 to rotate. The driving pulley 612 and the driven pulley 613 are mounted on the body 611 via bearing blocks. During the picking process, the bayberries falling from the collection tube are transported by the conveyor belt mechanism to a collection device. The use of a synchronous belt as a transport carrier offers advantages such as light weight, smooth transmission, a constant transmission ratio, and the ability to withstand certain impact loads.

[0039] Furthermore, the second driving mechanism 614 includes a second motor 616 and a coupling 617, and the second motor 616 and the driving pulley 612 are connected via the coupling 617. A plum blossom coupling can be used to provide power to the driving pulley, which has the advantages of low cost and reliable operation.

[0040] For easy holding, handles are installed on both sides of the body 611.

[0041] In order to reduce the weight of the harvester, main components such as the fuselage 611 can be made of carbon fiber, so that the whole machine is light in weight, high in strength, light and durable.

[0042] In one embodiment, referring to Figure 6 , the control device includes an Arduino 2560 development board, a stepper motor driver board, a voltage-stepping module, and a battery. The stepper motor driver board is connected to the first motor 131 and the second motor 616, respectively. The battery, via the voltage-stepping module, supplies power to the Arduino 2560 development board, the pressure sensor 12, the camera, the photoelectric sensor 4, the air valve, and the solenoid valve. The battery also supplies power to the first motor 131 and the second motor 616. The control device is integrated on a single circuit board using a micro-stepper motor driver board, resulting in a more integrated circuit board and a smaller size. The wiring between the control device and the harvester utilizes highly integrated aviation connectors, making assembly more convenient and reliable.

[0043] In one embodiment, positioning and maturity identification of bayberries include:

[0044] Preprocessing: The collected images are uniformly cropped to 512x512 pixels, and the bilateral filtering algorithm is used to remove image noise;

[0045] Image segmentation and binary image acquisition: Perform color space conversion on the filtered image, select the a component of the Lab color space and the U and V components of the YUV space, and use the histogram global threshold method to obtain binary images. Then perform morphological filtering to obtain binary images of overlapping and occluded fruit targets.

[0046] Extracting single targets from fruit images: Applying Hough transform to segment the binary images of the overlapping and occluded fruit targets, proposing circle center restriction conditions, removing centers that do not meet the requirements, and ultimately identifying the centers, pixel sizes, and number of overlapping and occluded fruits;

[0047] Maturity identification: The maximum inter-class variance method (Otsu) was used for image segmentation. The segmented bayberry image was converted from RGB color space to Lab color space, and the values ​​of the three Lab channels were extracted. Data analysis showed that maturity was only related to the ratio of a value to b value. a / b was set as the maturity classification threshold. When a / b was less than 1, it was classified as immature bayberry. When a / b was greater than 1 and less than 1.2, it was classified as almost mature. When a / b was greater than 1.2, it was classified as mature.

[0048] In one embodiment, the portion of the fruit holder 62 that contacts the bayberries is made of silicone, and a columnar flexible buffer structure is integrated within the fruit holder 62. When the bayberries fall into the fruit holder during picking, the columnar flexible buffer structure deforms under pressure, conforming to the shape of the bayberries. This effectively offsets impact and reduces rolling friction within the holder, thereby minimizing damage to the fruit during transportation.

[0049] The method of use of the present invention is as follows:

[0050] Referring to FIG7 , first turn on the power switch located at the handle at the end of the machine body to power on the picking machine; and use the image recognition device to locate and identify the maturity of the bayberries. When there are bayberries within the picking range and their maturity reaches the preset standard, the Arduino 2560 development board controls the carbon dioxide valve to open, and the carbon dioxide nozzle sprays carbon dioxide gas. The spraying stops after 2 seconds, and the first motor controls the mechanical claw 1 to automatically close and grab the fruit. The gripping force is controlled by the thin film pressure sensor 12 integrated on the flexible picking claw finger. The flexible picking claw finger will elastically deform according to the actual contour of the fruit, increasing the contact area and reducing damage to the fruit. After picking the fruit, by pressing the reset button on the handle at the end of the fuselage, the first motor controls the mechanical claw 1 to release. In the process of the fruit falling through the collection tube 14, the photoelectric sensor 4 integrated under the collection tube captures the bayberry and sends a signal to the Arduino 2560 development board. The development board controls the solenoid valve to open and spray liquid polyurethane foam. The bayberry wrapped in foam falls onto the fruit bracket 62 in the belt 615 transport device 6, and finally the second motor drives the conveyor belt to make the fruit fall into the fruit collection device.

Claims

1. A direct cooling and quick sealing electric bayberry picking machine based on machine vision, characterized in that: include: A mechanical claw, having at least three flexible claw fingers, a pressure sensor is arranged on the side of each flexible claw finger in contact with the bayberry, and a collection tube is arranged in the center surrounded by all the flexible claw fingers; An image recognition device for locating and identifying the maturity of bayberries; A carbon dioxide spraying device is used to spray carbon dioxide toward the bayberry stalk and around the bayberry to freeze the bayberry stalk and reduce the surface temperature of the bayberry; A photoelectric sensor, used for detecting whether waxberries come out of the outlet of the collection tube; A liquid polyurethane foam spraying device is used to coat the waxberries coming out of the collection pipe outlet with liquid polyurethane foam; A transport device, used for transporting the bayberries wrapped with liquid polyurethane foam, the transport device comprising a conveyor belt mechanism and a fruit support fixed on the conveyor belt mechanism, the fruit support moving together with the conveyor belt on the conveyor belt mechanism; The control processing device is used to control the carbon dioxide spraying device to spray carbon dioxide onto the bayberry stalk and around the bayberry according to the positioning and recognition results of the image recognition device, and then control the mechanical claw to grab the bayberry, and control the gripping force of the mechanical claw according to the pressure signal collected by the pressure sensor. When the bayberry is dragged and picked, the mechanical claw is controlled to be released so that the bayberry automatically falls into the collection tube. After the photoelectric sensor detects that the bayberry comes out of the collection tube outlet, the liquid polyurethane foam spraying device is controlled to spray liquid polyurethane foam onto the bayberry. The bayberry wrapped in the liquid polyurethane foam then falls into the fruit tray, and the bayberry is transported out by controlling the transportation device.

2. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1 is characterized in that: The mechanical claw includes at least three flexible claw fingers, a pressure sensor, a first driving mechanism, and a collection tube. The first driving mechanism drives all the flexible claw fingers to close or open at the same time. A pressure sensor is set on the side of each flexible claw finger that contacts the bayberry. The entrance of the collection tube is located in the area enclosed by all the flexible claw fingers.

3. A direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 2, characterized in that: The first driving mechanism includes a crank slider mechanism and a first motor. The root end of the flexible claw finger is installed on the crank of the crank slider mechanism. The first motor drives the slider of the crank slider mechanism to perform telescopic linear motion.

4. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1 is characterized in that: The image recognition device includes a camera, and the camera transmits the collected pictures to the control processing device.

5. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1, characterized in that: The carbon dioxide spraying device includes a first nozzle, a first pipeline, an air valve and a gas cylinder filled with carbon dioxide. The first nozzle is connected to the gas cylinder through the first pipeline. The air valve is arranged on the first pipeline to control the opening and closing of the first pipeline. The air valve is controlled by the control processing device.

6. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1, characterized in that: The liquid polyurethane foam spraying device includes a second nozzle, a second pipeline, a solenoid valve and a liquid polyurethane tank. The second nozzle is connected to the liquid polyurethane tank via the second pipeline. The solenoid valve is arranged on the second pipeline to control the on and off of the second pipeline. The solenoid valve is controlled by the control processing device.

7. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1 is characterized in that: The conveyor belt mechanism comprises a driving pulley, a driven pulley, a second driving mechanism, and a belt. The belt is sleeved between the driving pulley and the driven pulley, and the second driving mechanism drives the driving pulley to rotate.

8. A machine vision-based direct cooling and quick-sealing electric bayberry picking machine according to claim 7, characterized in that: The second driving mechanism includes a second motor and a coupling, and the second motor and the driving pulley are connected via the coupling.

9. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1, characterized in that: Locate and identify the maturity of bayberry, including: Preprocessing: The collected images are uniformly cropped into a size of 512x512 pixels, and the bilateral filtering algorithm is used to remove image noise; Image segmentation and binary image acquisition: Perform color space conversion on the filtered image, select the a component of the lab color space, the U and V components of the YUV space, and use the histogram global threshold method to obtain binary images, and then perform morphological filtering operations to obtain binary images of overlapping and occluded fruit targets; Extracting a single target from the fruit image: applying Hough transform to segment the binary image of the overlapping and occluded fruit targets, proposing circle center restriction conditions, removing the circle centers that do not meet the requirements, and finally identifying the circle centers, pixel sizes and numbers of the overlapping and occluded fruits; Maturity identification: The maximum inter-class variance method is used for image segmentation. The segmented bayberry image is converted from RGB color space to Lab color space, and the values ​​of the three Lab channels are extracted. Data analysis shows that maturity is only related to the ratio of a value to b value. a / b is set as the maturity threshold. When a / b is less than 1, it is classified as immature bayberry. When a / b is greater than 1 and less than 1.2, it is classified as almost mature. When a / b is greater than 1.2, it is classified as mature.

10. The direct cooling and quick sealing electric bayberry picking machine based on machine vision according to claim 1, characterized in that: The portion of the fruit support that contacts the bayberry is made of silica gel, and a columnar flexible buffer structure is integrated inside the fruit support.

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