CN113548234B - Method, system and related equipment for selecting fruits - Google Patents
Method, system and related equipment for selecting fruits Download PDFInfo
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- CN113548234B CN113548234B CN202110657345.4A CN202110657345A CN113548234B CN 113548234 B CN113548234 B CN 113548234B CN 202110657345 A CN202110657345 A CN 202110657345A CN 113548234 B CN113548234 B CN 113548234B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B35/00—Supplying, feeding, arranging or orientating articles to be packaged
- B65B35/10—Feeding, e.g. conveying, single articles
- B65B35/16—Feeding, e.g. conveying, single articles by grippers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B35/00—Supplying, feeding, arranging or orientating articles to be packaged
- B65B35/30—Arranging and feeding articles in groups
- B65B35/36—Arranging and feeding articles in groups by grippers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B5/00—Packaging individual articles in containers or receptacles, e.g. bags, sacks, boxes, cartons, cans, jars
- B65B5/08—Packaging groups of articles, the articles being individually gripped or guided for transfer to the containers or receptacles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B57/00—Automatic control, checking, warning, or safety devices
- B65B57/10—Automatic control, checking, warning, or safety devices responsive to absence, presence, abnormal feed, or misplacement of articles or materials to be packaged
- B65B57/14—Automatic control, checking, warning, or safety devices responsive to absence, presence, abnormal feed, or misplacement of articles or materials to be packaged and operating to control, or stop, the feed of articles or material to be packaged
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Abstract
The present invention relates to a method for selecting fruit, said method comprising: s1, detecting fruit groups composed of different types, and identifying target fruits from the fruit groups; s2, grabbing the target fruit; s3, weighing the grabbed target fruits, wherein the weighing of the grabbed target fruits specifically comprises the following steps: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; and S4, packaging the target fruits reaching the preset weight value. But wide application in fruit intelligence selects technical field.
Description
Technical Field
The invention relates to the technical field of intelligent fruit selection. More particularly, the present invention relates to a method, system and related apparatus for selecting fruit.
Background
In the past year, new coronavirus are abused, shopping and traveling are greatly limited. Meanwhile, people are also more and more used to finish shopping online. Along with the popularization of online shopping platforms and online shopping modes and concepts. More and more businesses are beginning to build online stores on the internet. The online merchant can directly deliver goods from the warehouse without creating a physical store. How fast the merchant takes the goods and packs here is directly related to the profit of the merchant.
In particular, it includes: in the purchase transaction of fruits, how to automatically screen target fruits through an intelligent system and replace the original manual integrated flow of grabbing, weighing and packaging.
Disclosure of Invention
The invention aims to provide a method, a system and related equipment for selecting fruits, which can optimize a fruit purchasing process and improve fruit purchasing efficiency.
To achieve these objects and other advantages and in accordance with the purpose of the invention, as embodied and broadly described herein, the present invention provides in a first aspect a method for selecting fruit, the method comprising: s1, detecting fruit groups composed of different types, and identifying target fruits from the fruit groups; s2, grabbing the target fruit; s3, weighing the grabbed target fruits, wherein the weighing of the grabbed target fruits specifically comprises the following steps: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuously grabbing until the weight of the target fruit reaches a preset weight value; and S4, packaging the target fruits reaching the preset weight value.
In a first aspect, the step of identifying a target fruit from a population of fruits is preceded by the method of: establishing a fruit model image database, wherein the fruit model image database stores image collections of different types of fruits, and the image collections comprise the image characteristics: size, color, shape; according to the fruit model image database, image feature extraction is carried out on image data of each fruit in advance, so that the target fruit can be identified from a fruit group based on the image feature of each fruit, the target fruit is grabbed and then weighed, and the target fruit is packed after reaching a preset weight value.
In a first aspect, the identifying a target fruit from a fruit cluster comprises: identifying the image characteristics of the fruits in the fruit group, and judging whether the identified fruits are target fruits or not according to the image characteristics; if yes, selecting the identified fruit as a target fruit; if not, abandoning the selection of the identified fruit; and when the identified fruit is the target fruit, grabbing and weighing the target fruit, and packing when the target fruit reaches a preset weight value.
In a second aspect, the present invention provides a system for selecting fruit, the system comprising: the fruit detection module: the fruit cluster detection device is used for detecting fruit clusters composed of different types and identifying target fruits from the fruit clusters; fruit snatchs module: for grasping the target fruit; fruit weighing module: weighing the grabbed target fruit, wherein weighing the grabbed target fruit specifically comprises: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; fruit packing module: and packaging the target fruits reaching the preset weight value.
In a second aspect, the system further comprises: fruit model image database: the fruit model image database stores image collections of different types of fruit, the image collections including these image features: size, color, shape; according to the fruit model image database, image feature extraction is carried out on image data of each fruit in advance, so that the target fruit can be identified from a fruit group based on the image feature of each fruit, the target fruit is grabbed and then weighed, and the target fruit is packed after reaching a preset weight value.
In a second aspect, the fruit detection module is further configured to: acquiring image characteristics of fruits in the fruit group, and judging whether the identified fruits are target fruits or not according to the image characteristics; if yes, selecting the identified fruit as a target fruit; if not, abandoning the selection of the identified fruit; when the identified fruit is the target fruit, grabbing and weighing the target fruit, and packing when the target fruit reaches a preset weight value.
In the second aspect, fruit detection module is the camera, the camera is used for detecting the fruit crowd that different kind constitutes, discerns target fruit from the fruit crowd to it is right target fruit snatchs then weighs, packs after target fruit reaches predetermined weight value.
In a second aspect, the weighing module is an electronic scale, and is configured to weigh the grabbed target fruit, where the weighing of the grabbed target fruit specifically includes: judging whether the weight of the target fruit reaches a preset weight value or not; if so, stopping grabbing by the grabbing device; if not, enabling the grabbing device to continue grabbing until the weight of the target fruit reaches the preset weight value; and packaging the target fruits reaching the preset weight value.
In a third aspect, the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program stored in the memory: detecting fruit groups composed of different types, and identifying target fruits from the fruit groups; grabbing the target fruit; weighing the grabbed target fruit, wherein weighing the grabbed target fruit specifically comprises: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; and packaging the target fruits reaching the preset weight value.
In a fourth aspect, the invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: detecting fruit groups composed of different types, and identifying target fruits from the fruit groups; the right the target fruit snatchs, to snatching the target fruit is weighed specifically includes: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; and packaging the target fruits reaching the preset weight value.
The invention at least comprises the following beneficial effects:
according to the method for selecting the fruits, disclosed by the invention, the fruit group consisting of various fruits is automatically detected, the target fruits are grabbed, weighed and then packaged after the target fruits are identified, and the detection, grabbing, weighing and packaging processes are automatically completed, so that the technical effects of saving the labor cost and improving the shopping efficiency are achieved.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a flow chart of a method for selecting fruit according to one embodiment of the present invention;
FIG. 2 is a block diagram of a fruit sorting system according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer-readable medium according to a fourth embodiment of the present invention.
Fig. 5 is a structural diagram of a robot according to a fifth embodiment of the present invention;
fig. 6 is a top view of a robot according to a fifth embodiment of the present invention;
description of reference numerals: 1. the cooperation robot, 2, wrist camera, 3, flexible clamping jaw, 4, well accuse machine, 5, fruit place the platform, 6, electronic display screen, 7, the platform of weighing, 8, packing case.
Detailed Description
The present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.
In the description of the present invention, the terms "lateral", "longitudinal", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
As shown in fig. 1 to 4, the method for selecting fruits according to the present invention automatically detects a fruit group consisting of a plurality of fruits, captures, weighs and packages the target fruits after identifying the target fruits, and the above-mentioned detection, capture, weighing and packaging processes are all automatically completed to achieve the technical effects of saving labor cost and improving shopping efficiency, and for the purpose of describing the present invention in detail to support the technical problems to be solved by the present invention, the embodiments of the present invention are further explained below:
the first embodiment is as follows:
an embodiment of the present invention provides a method for selecting fruit, the method comprising: s1, carrying out convolutional neural network deep learning on fruit clusters composed of different types in advance, and then identifying target fruits from the fruit clusters through a trained convolutional neural network model; s2, grabbing the target fruit; s3, weighing the grabbed target fruits, wherein the weighing of the grabbed target fruits specifically comprises the following steps: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; s4, packing the target fruits reaching the preset weight value, automatically identifying, grabbing, weighing and packing the fruits in the fruit group, realizing the full process automation of selling the fruits, further saving the labor cost of selling the fruits, and simultaneously, in a special period, for example, when the Xinguan pneumonia still has the possibility of infection, by the implementation method, the contact between people is greatly reduced when the fruits are purchased by people.
Based on the step of identifying the target fruit from the fruit group after detecting the fruit group in the above embodiment, the present embodiment further proposes a method further comprising, before the step of identifying the target fruit from the fruit group: establishing a fruit model image database, wherein the fruit model image database is an image set for storing different types of fruits, and the image set comprises the respective fruit image characteristics: size, color, shape; according to the fruit model image database, deep learning training of a convolutional neural network related to fruit image data composed of different types is carried out, the target fruit is identified from a fruit group through a trained convolutional neural network model, the target fruit is grabbed and then weighed, and the target fruit is packed after reaching a preset weight value.
Based on the method for identifying a target fruit from a fruit group in the above embodiment, this embodiment further explains the method, and the method further includes: carrying out deep learning training on a related convolutional neural network by using the image data set of the fruits in the fruit group, and judging whether the identified fruits are target fruits or not through a trained convolutional neural network model; if yes, selecting the identified fruit as a target fruit; if not, abandoning the selection of the identified fruit; when the identified fruit is the target fruit, grabbing and weighing the target fruit, and packing when the target fruit reaches a preset weight value.
In summary, according to the method for selecting fruits, provided by the invention, the fruit group consisting of a plurality of fruits is automatically detected, the target fruit is grabbed, weighed and then packaged after the target fruit is identified, and the detection, grabbing, weighing and packaging processes are automatically completed, so that the technical effects of saving labor cost and improving shopping efficiency are achieved.
Example two:
an embodiment two of the present invention provides a system for selecting fruit, the system comprising: fruit detection module 300, fruit snatch module 301, fruit weighing module 302 and fruit packing module 303, fruit detection module 300: the fruit group detection system is used for detecting fruit groups composed of different types and identifying target fruits from the fruit groups; the fruit grabbing module 301: for grasping the target fruit; the fruit weighing module 302: weighing the grabbed target fruit, wherein the weighing the grabbed target fruit specifically comprises: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; the fruit packing module 303: and packaging the target fruits reaching the preset weight value.
The above embodiment describes a system for selecting fruit, which is used to identify, grab, weigh and pack the fruit, and this embodiment further provides a device based on the above embodiment, and the device includes: fruit model image database: the fruit model image database is an image collection for storing different types of fruits, and the image collection comprises the respective fruit image characteristics: size, color, shape; according to the fruit model image database, deep learning training of a convolutional neural network related to fruit image data composed of different types is carried out, the target fruit is identified from a fruit group through a trained convolutional neural network model, the target fruit is grabbed and then weighed, and the target fruit is packed after reaching a preset weight value.
The above embodiment replaces the fruit detecting module 300 to detect the fruit group and detect the target fruit, and the embodiment further explains the steps on the basis that: the fruit detection module 300 is further configured to: carrying out deep learning training on fruit image data composed of different types and related convolutional neural networks in advance, and identifying the target fruit from a fruit group through a trained convolutional neural network model; if yes, selecting the identified fruit as a target fruit; if not, abandoning the selection of the identified fruit; and when the identified fruit is the target fruit, grabbing the target fruit and then weighing, and packing after the target fruit reaches a preset weight value.
The fruit detecting module 300 is used for detecting a fruit group and identifying a target fruit from the fruit group, and essentially performs the above steps by using an image capturing device, and the fruit detecting module 300 includes: the camera, the camera is used for detecting the fruit crowd that different kind constitutes, discerns target fruit from the fruit crowd, and right target fruit snatchs then weighs, packs after target fruit reaches predetermined weight value.
Based on the fruit weighing module 302 provided in the above embodiment, the embodiment further explains the fruit weighing module 302, where the fruit weighing module 302 is an electronic scale, and the weighing the grabbed target fruit specifically includes: judging whether the weight of the target fruit reaches a preset weight value or not; if so, stopping grabbing by the grabbing device; if not, enabling the grabbing device to continue grabbing until the weight of the target fruit reaches the preset weight value; and packaging the target fruits reaching the preset weight value.
Example three:
as shown in fig. 3, a third embodiment of the present invention provides an electronic device 100, including: a memory 101, a processor 103 and a computer program 102 stored in the memory 101 and operable on the processor 103, the processor 103 being configured to perform the following steps when executing the computer program 102 stored in the memory 101: detecting fruit groups composed of different types, and identifying target fruits from the fruit groups; grabbing the target fruit; weighing the grabbed target fruit, wherein weighing the grabbed target fruit specifically comprises: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuously grabbing until the weight of the target fruit reaches a preset weight value; and packaging the target fruits reaching the preset weight value.
Example four:
as shown in fig. 4, a fourth embodiment of the present invention provides a computer-readable storage medium 200, on which a computer program 201 is stored, where the computer program 201, when executed by a processor, implements the following steps: detecting fruit groups composed of different types, and identifying target fruits from the fruit groups; grabbing the target fruit; weighing the grabbed target fruit, wherein weighing the grabbed target fruit specifically comprises: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuously grabbing until the weight of the target fruit reaches a preset weight value; and packaging the target fruits reaching the preset weight value.
Example five:
a cooperative robot 1 of the present invention includes: the fruit placing platform 5 is used for placing different kinds of fruits; one side of fruit place the platform is provided with flexible clamping jaw 3: for grasping the target fruit; fruit place the platform's top still is provided with wrist camera 2: the fruit cluster detection device is used for detecting fruit clusters composed of different types and identifying target fruits from the fruit clusters; still be provided with electronic display screen 6 on the fruit place the platform: displaying the weight of the grabbed target fruit; the weighing platform 7: weighing the grabbed target fruit; the weighing of the grabbed target fruit specifically comprises: judging whether the weight of the target fruit reaches a preset weight value or not; if yes, stopping grabbing; if not, continuing to grab until the weight of the target fruit reaches the preset weight value; and (3) packing box 8: packing the target fruits reaching the preset weight value; well control machine 4, well control machine 4 with fruit place the platform 5 the wrist camera 2 flexible clamping jaw 3 the platform of weighing 7 the 8 communication connection of packing case, well control case is used for control fruit place the platform 5 the wrist camera 2 flexible clamping jaw 3 the platform of weighing 7 the packing case 8 carries out foretell action. Wherein, flexible clamping jaw 3 with well accuse machine 4 is connected.
Secondly, the cooperation robot with the flexible clamping jaws 3 is a six-axis UR3 cooperation robot, and the robot is flexible in movement, convenient to grab, moderate in size and easy to install. The flexible clamping jaw 3 is a three-finger soft clamping jaw, is convenient for grabbing fruits, does not damage the surfaces of the fruits, and does not fall off after grabbing. Wrist camera 2 follows the discernment of flexible clamping jaw 3 and snatchs fruit, and the recognition efficiency is high, snatch the convenience, even also can ensure stable discernment and snatch the effect under various different backgrounds and lighting condition.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
For another example, the division of the above-mentioned units is only one logical function division, and there may be other division manners in actual implementation, and for another example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments provided by the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The above functions, if implemented in the form of software functional units and sold or used as a separate product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a portable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other media capable of storing program codes.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the following descriptions are only illustrative and not restrictive, and that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention. Are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
While embodiments of the invention have been described above, it is not intended to be limited to the details shown, described and illustrated herein, but is to be accorded the widest scope consistent with the principles and novel features herein disclosed, and to such extent that such modifications are readily available to those skilled in the art, and it is not intended to be limited to the details shown and described herein without departing from the general concept as defined by the appended claims and their equivalents.
Claims (8)
1. Method for selecting fruit, characterized in that it comprises:
s1, detecting fruit groups composed of different types, and identifying target fruits from the fruit groups;
s2, grabbing the target fruit;
s3, weighing the grabbed target fruits, wherein the weighing of the grabbed target fruits specifically comprises the following steps:
judging whether the weight of the target fruit reaches a preset weight value or not;
if yes, stopping grabbing;
if not, continuously grabbing until the weight of the target fruit reaches a preset weight value;
s4, packaging the target fruits reaching the preset weight value;
the step of identifying a target fruit from a population of fruits further comprises the following method:
establishing a fruit model image database, wherein the fruit model image database is an image set for storing different types of fruits, and the image set comprises the fruit image characteristics: size, color, shape;
according to the fruit model image database, image feature extraction is carried out on image data of each fruit in advance, so that the target fruit can be identified from a fruit group based on the image feature of each fruit, the target fruit is grabbed and then weighed, and the target fruit is packed after reaching a preset weight value;
the identifying the target fruit from the fruit group comprises:
identifying the image characteristics of the fruits in the fruit group, and judging whether the identified fruits are target fruits or not according to the image characteristics;
if yes, selecting the identified fruit as a target fruit;
if not, abandoning the selection of the identified fruit;
and when the identified fruit is the target fruit, grabbing and weighing the target fruit, and packing when the target fruit reaches a preset weight value.
2. System for selecting fruit, characterized in that it comprises:
fruit detection module: the fruit group detection system is used for detecting fruit groups composed of different types and identifying target fruits from the fruit groups;
fruit snatchs module: for grasping the target fruit;
fruit weighing module: weighing the grabbed target fruit, wherein the weighing the grabbed target fruit specifically comprises:
judging whether the weight of the target fruit reaches a preset weight value or not;
if yes, stopping grabbing;
if not, continuously grabbing until the weight of the target fruit reaches a preset weight value;
fruit packing module: and packaging the target fruits reaching the preset weight value.
3. The system for selecting fruit according to claim 2, further comprising:
fruit model image database: the fruit model image database stores image collections of different types of fruit, the image collections including these image features: size, color, shape;
according to the fruit model image database, image feature extraction is carried out on image data of each fruit in advance, so that the target fruit can be identified from a fruit group based on the image feature of each fruit, the target fruit is grabbed and then weighed, and the target fruit is packed after reaching a preset weight value.
4. The system for selecting fruit of claim 3, wherein the fruit detection module is further configured to:
acquiring image characteristics of fruits in the fruit group, and judging whether the identified fruits are target fruits or not according to the image characteristics;
if yes, selecting the identified fruit as a target fruit;
if not, abandoning the selection of the identified fruit;
when the identified fruit is the target fruit, grabbing and weighing the target fruit, and packing when the target fruit reaches a preset weight value.
5. A system for selecting fruit according to claim 4, wherein: the fruit detection module is a camera, the camera is used for detecting fruit groups composed of different types, identifying target fruits from the fruit groups, grabbing and weighing the target fruits, and packing the target fruits after the target fruits reach preset weight values.
6. A system for selecting fruit according to claim 4, wherein: the fruit weighing module is an electronic scale, and is used for weighing the grabbed target fruit, wherein the step of weighing the grabbed target fruit specifically comprises the following steps:
judging whether the weight of the target fruit reaches a preset weight value or not;
if so, stopping grabbing by the fruit grabbing module;
if not, the fruit grabbing module continues to grab the target fruit until the weight of the target fruit reaches the preset weight value; and packaging the target fruits reaching the preset weight value.
7. An electronic device, comprising: memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor is configured to perform the following steps when executing the computer program stored in the memory:
detecting fruit groups composed of different types, and identifying target fruits from the fruit groups;
grabbing the target fruit;
weighing the grabbed target fruit, wherein the weighing the grabbed target fruit specifically comprises:
judging whether the weight of the target fruit reaches a preset weight value or not;
if yes, stopping grabbing;
if not, continuing to grab until the weight of the target fruit reaches the preset weight value;
and packaging the target fruits reaching the preset weight value.
8. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program when executed by a processor implements the steps of:
detecting fruit groups composed of different types, and identifying target fruits from the fruit groups;
grabbing the target fruit;
weighing the grabbed target fruit, wherein the weighing the grabbed target fruit specifically comprises:
judging whether the weight of the target fruit reaches a preset weight value or not;
if yes, stopping grabbing;
if not, continuously grabbing until the weight of the target fruit reaches a preset weight value;
and packaging the target fruits reaching the preset weight value.
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| JP4812083B2 (en) * | 2005-11-22 | 2011-11-09 | 公立大学法人高知工科大学 | Sorting method and apparatus for iriko etc. |
| CN108686978B (en) * | 2018-05-02 | 2020-12-29 | 广州慧睿思通信息科技有限公司 | ARM-based fruit category and color sorting method and system |
| CN109397313A (en) * | 2018-12-14 | 2019-03-01 | 温州翰轩林工业设计有限公司 | A kind of fruit sorting vanning robot |
| CN210761487U (en) * | 2019-08-27 | 2020-06-16 | 杭州魔象智能科技有限公司 | Fruit pile up neatly vanning platform |
| CN110816943A (en) * | 2019-12-04 | 2020-02-21 | 北京云杉信息技术有限公司 | Quantitative fruit and vegetable packaging device and packaging method |
| CN112478254A (en) * | 2020-12-25 | 2021-03-12 | 南京爱昵熊贸易有限公司 | Bagging device capable of scanning and identifying fruit types |
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