CN212232163U - Self-picking peanut harvester based on image processing - Google Patents
Self-picking peanut harvester based on image processing Download PDFInfo
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- CN212232163U CN212232163U CN202020819287.1U CN202020819287U CN212232163U CN 212232163 U CN212232163 U CN 212232163U CN 202020819287 U CN202020819287 U CN 202020819287U CN 212232163 U CN212232163 U CN 212232163U
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- arm
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- dolly
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- 235000020232 peanut Nutrition 0.000 title claims abstract description 66
- 235000017060 Arachis glabrata Nutrition 0.000 title claims abstract description 54
- 235000010777 Arachis hypogaea Nutrition 0.000 title claims abstract description 54
- 235000018262 Arachis monticola Nutrition 0.000 title claims abstract description 54
- 238000012545 processing Methods 0.000 title claims abstract description 16
- 241001553178 Arachis glabrata Species 0.000 title abstract 7
- 244000105624 Arachis hypogaea Species 0.000 claims description 59
- 230000005540 biological transmission Effects 0.000 claims description 15
- 240000007651 Rubus glaucus Species 0.000 claims description 3
- 235000011034 Rubus glaucus Nutrition 0.000 claims description 3
- 235000009122 Rubus idaeus Nutrition 0.000 claims description 3
- 238000000034 method Methods 0.000 description 5
- 238000013528 artificial neural network Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 229920003023 plastic Polymers 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000003466 welding Methods 0.000 description 1
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Abstract
The utility model relates to a from picking up peanut harvester based on image processing belongs to image recognition and agricultural equipment technical field. The device comprises a trolley body, and a camera, a mechanical arm, a control box, a storage battery, a steering engine, a rotating motor and a peanut storage box which are arranged on the trolley body. The camera is located the foremost of dolly, and the arm is located dolly front end top position, and control box and battery are located the dolly first half, and the peanut containing box is located dolly latter half. Video information collected by the camera is stored in a storage, analyzed and coded and then input into a microcomputer, the computer carries out real-time identification and discrimination on target images of peanuts scattered on the ground, and then the peanuts are accurately picked up by a mechanical arm gripper and put into a peanut storage box of the harvester.
Description
Technical Field
The utility model relates to a from picking up peanut harvester based on image processing belongs to image recognition and agricultural equipment technical field.
Background
When the peanuts are harvested, the peanuts need to be ploughed out of soil and aired, and then the peanuts need to be subjected to picking and shelling treatment after being aired and dried. In view of at present to do not have supplementary pickup attachment in peanut harvester mostly, need consume a large amount of manpowers and pick up the peanut that loses in the field ground, caused the problem that the amount of labour increases and work operating efficiency hangs down. The utility model discloses to supplementary pickup attachment in partial peanut harvesting machine is formed by the tiny even or dislocation arrangement's of a plurality of tubular metal resonator welding combination more, and then picks up the operation to the peanut seedling that scatters, nevertheless picks up the effect relatively poor to the peanut that scatters, and work efficiency is lower.
Disclosure of Invention
The utility model discloses to be difficult to the problem of picking up about the peanut that drops in current device, provide a peanut harvester is picked up from based on image processing, not only avoided a large amount of manual labor to drop into but also improved the peanut and picked up work efficiency certainly.
The utility model adopts the technical proposal that: the utility model provides a from picking up peanut harvester based on image processing, includes the dolly body and installs arm, camera 5, control box 6, peanut containing box 8, storage battery 10 on the dolly body. The rotary camera 5 is installed at the foremost end of the trolley body, the mechanical arm component is located on the upper surface of the top of the front end of the trolley body, the control box 6 is located inside the front half part of the trolley body, the peanut containing box 8 is installed at the rear half part of the trolley body, the rotary motor is installed on the rotary shaft of the rear wheel 7 of the trolley, the steering engine is installed on the rotary shaft of the front wheel of the trolley, the storage battery pack 10 is located between the control box 6 and the peanut containing box 8, the microcomputer processor 9, the memory 11 and the wireless transmission module 13 are installed in the control box 6, the interface end of the integrated circuit of the microcomputer processor 9 is respectively connected with the memory 11, the wireless transmission module 13, the camera 5, the mechanical arm, the steering engine of the front wheel of the trolley, the infrared reflection-type sensor.
Preferably, an infrared reflection sensor 12 is attached to the top end of the peanut bin 8.
Preferably, the control terminal device is a mobile phone or a computer.
Preferably, the camera 5 is a raspberry type camera.
Preferably, the self-picking peanut harvester is constructed by a wheel type trolley.
Specifically, the type of arm be 6 degrees of freedom arms, including arm base 4, arm rotation joint (steering wheel) 3, arm connecting rod 2 and arm tong 1. The upper surface at dolly body front end top is installed to 4 rotating device of arm base, and arm base 4 is connected with the one end of arm revolute joint 3 through arm connecting rod 2, and the other end of arm revolute joint 3 is connected with one section arm connecting rod 2 again, and the end and the arm tong 1 of second section arm connecting rod 2 are connected. Wherein, the integrated circuit interfaces of the mechanical arm base 4, the mechanical arm rotating joint 3, the mechanical arm connecting rod 2 and the mechanical arm clamping hand 1 are connected with the interface at the end of the microcomputer processor 9.
The utility model has the advantages that: the utility model can transmit the image shot by the camera to the computer in real time, and then realize the real-time discrimination of the peanuts scattered on the ground by the computer, and finally realize the final self-picking operation of the peanuts through the mechanical arm; the remote control of the trolley can be realized by an operator through the wireless transmission control terminal equipment so as to complete the self-picking operation of the peanuts scattered on the ground. The utility model discloses not only can avoid a large amount of manual labor to drop into, can show the self-picking work efficiency who improves the peanut moreover.
Drawings
Fig. 1 is a schematic structural view of the present invention;
fig. 2 is a schematic structural view of the mechanical arm of the present invention.
The reference numbers in the drawings are as follows: the peanut harvester comprises a mechanical arm clamp, a mechanical arm connecting rod, a mechanical arm rotating joint, a mechanical arm base, a camera, a control box, a trolley rear wheel, a peanut storage box, a microcomputer processor, a storage battery pack, a storage 11, an infrared reflection type sensor and a wireless transmission module 13, wherein the mechanical arm clamp is arranged on the mechanical arm connecting rod, the mechanical arm rotating joint is arranged on the mechanical arm base, the camera is 5, the control box is 6, the trolley rear wheel is 7, the peanut storage box is 8, the microcomputer.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific embodiments, it being understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1: as shown in fig. 1-2, the self-picking peanut harvester based on image processing comprises a trolley body, and a mechanical arm, a camera 5, a control box 6, a peanut storage box 8 and a storage battery pack 10 which are arranged on the trolley body. The rotary camera 5 is arranged at the foremost end of the trolley body, the mechanical arm component is positioned on the upper surface of the top of the front end of the trolley body, the control box 6 is positioned on the front half part of the inside of the trolley body, the peanut containing box 8 is arranged on the rear half part of the trolley body, the rotary motor is arranged on the rotary shaft of the rear wheel 7 of the trolley, the steering engine is arranged on the rotary shaft of the front wheel of the trolley, the storage battery pack 10 is positioned between the control box 6 and the peanut containing box 8, the microcomputer processor 9, the memory 11 and the wireless transmission module 13 are arranged in the control box 6 (as shown in figure 1, the three are integrated together), the interface of the integrated circuit of the microcomputer processor 9 is respectively connected with the interfaces of the memory 11, the wireless transmission module 13, the camera 5, the mechanical arm, the steering engine of the front wheel of the trolley, the infrared reflection sensor 12 and the storage battery pack 10.
The trolley body main body framework adopts a wheel type structure, a rotating motor provides driving force for the trolley body, and the front wheel steering engine is used for controlling steering of the trolley. The camera 5 is responsible for collecting image information; the memory 11 is connected with the image transmission interface of the camera 5 and stores the image information collected by the camera 5; the microcomputer processor 9 is connected with the memory 11, reads image information stored in the memory 11 and analyzes image characteristic information, so that real-time discrimination of peanuts scattered on the ground is realized; the integrated circuit interface at the end of the mechanical arm is connected with the interface at the end of a microcomputer processor 9 in the control box 6, the microcomputer processor 9 sends an instruction to the mechanical arm, and finally the mechanical arm gripper 1 finishes the final peanut self-picking operation through the integral linkage of the mechanical arm; the peanut storage box 8 is used for storing peanuts; each module in the trolley control box 6 is powered by a storage battery pack 10; in the wireless transmission module, an operator can control the running track of the trolley or control the rotation angle of the camera and directly control the mechanical arm by using control terminal equipment (a mobile phone or a computer).
Furthermore, an infrared reflection type sensor 12 connected with the end of the microcomputer processor 9 is installed at the top end of the peanut containing box 8. The device utilizes the principle of infrared reflection to judge whether the front obstacle exists or not according to the intensity of reflection, so that the device judges whether the peanut storage box needs to be replaced or not by the sensor.
Furthermore, the control terminal device is a mobile phone or a computer of a user.
Furthermore, the type of arm be 6 degrees of freedom arms, but self-programming arm program instruction, this arm tong can promote to the maximize degree through the self-adaptation cooperation of rotating joint (steering wheel) and connecting rod and pick up the precision. The 6-degree-of-freedom mechanical arm comprises a mechanical arm base 4, a mechanical arm rotating joint 3 (steering engine), a mechanical arm connecting rod 2 and a mechanical arm clamping hand 1, wherein a rotating device of the mechanical arm base 4 is installed on the upper surface of the top of the front end of the trolley body, the mechanical arm base 4 is connected with one end of the mechanical arm rotating joint 3 through the mechanical arm connecting rod 2, the other end of the mechanical arm rotating joint 3 is connected with one section of mechanical arm connecting rod 2, and the tail end of the second section of mechanical arm connecting rod 2 is connected with the mechanical arm. The integrated circuit interfaces of the mechanical arm base 4, the mechanical arm rotating joint 3, the mechanical arm connecting rod 2 and the mechanical arm clamping hand 1 are connected with the end 9 of the microcomputer processor.
Furthermore, the camera 5 adopts a high-definition mini camera, and has higher frame number and definition. The utility model discloses a raspberry group camera is used for carrying out camera angle modulation to it to target image real-time identification, accessible control terminal equipment (cell-phone or computer) moreover.
Furthermore, peanut containing box 8 adopt transparent plastic material to make, lightly durable.
Further, an LED lamp is added beside the camera 5 to enhance the influence of factors such as illumination and light intensity on the image resolution.
Alternatively, the microcomputer processor 9 may be an intel-series processor.
Alternatively, the steering engine is referenced to a model such as an MG995 steering engine.
Optionally, the peanut self-picking harvester is powered by the storage battery pack 10, and the storage battery model can be selected from 6-DZM-12, 6-DZM-17, 6-DZM-20, 8-DZM-20 and the like.
The utility model discloses a theory of operation: video information that the camera 5 of dolly body front end gathered is preserved in memory 11 and is converted analog signal into digital signal and real-time microcomputer processor 9 who transmits to in control box 6 through video decoder, carry out real-time discernment to the target image by microcomputer processor 9, then assign the instruction by microcomputer processor 9 and give the arm, through the whole linkage of arm, then at last accomplish final peanut from picking up the operation by robotic arm tong 1, and put in peanut containing box 8.
The microcomputer processor 9 processes among the images: firstly, collecting a large number of peanut images and constructing a peanut image data set for training a certain neural network, wherein the trained neural network has a high recognition rate on peanuts scattered on the surface of a stratum; then, various parameters are migrated to a neural network of a microcomputer processor 9 of the device by adopting a migration learning method; finally, the utility model discloses the image data that the camera 5 of dolly was gathered is stored to memory 11 in, and the image data in the memory 11 is in the real-time microcomputer processor 9 of transmission after analysis and the code again, carries out image processing through the neural network procedure and can realize the real-time identification to the target image. These are image processing procedures commonly used in the art and will not be described in detail here.
In the self-picking module process: firstly, the microcomputer processor 9 identifies the target image in real time; then, the microcomputer processor 9 sends out an instruction to the mechanical arm; and finally, the mechanical arm clamp 1 completes the final peanut self-picking operation through the integral linkage of the mechanical arm. The mechanical arm with 6 degrees of freedom is taken as an example, the mechanical arm is strong in expansibility, program instructions can be added according to specific requirements, and codes are open. The rotating device of the mechanical arm base 4 is installed on the upper surface of the top of the front end of the peanut self-picking trolley body, the base is rotatable in the horizontal direction, one section of mechanical arm connecting rod 2 is connected with the mechanical arm base 4 (the connecting rod can swing in the vertical direction under the control of a steering engine), the tail end of the mechanical arm connecting rod 2 is connected with a mechanical arm rotating joint 3 (namely a steering engine), the mechanical arm rotating joint 3 is connected with one section of mechanical arm connecting rod 2, the tail end of the second section of mechanical arm connecting rod 2 is connected with a mechanical arm clamping hand 1, and the clamping angle of the mechanical arm clamping hand 1 is controlled by the steering engine so as to finish accurate clamping of peanuts.
In the control box 6, there are wiring interfaces between the microcomputer processor 9 and the memory 11 and between the microcomputer processor 9 and the wireless transmission module 13, the video information recorded by the camera 5 is stored in the memory 11, the video information in the memory 11 is called by the microcomputer processor 9 immediately, and the real-time target identification of the target image is realized through the operation of the neural network program in the microcomputer processor 9. The wireless transmission module 13 in the control box 6 module is used for establishing connection (such as Bluetooth connection) with external control terminal equipment (such as a mobile phone and a computer). The control box 6 is the core part of the whole trolley, wherein an integrated circuit interface is arranged at the end of the microcomputer processor 9 and is respectively connected with the interfaces of the ends of the memory 11, the wireless transmission module 13, the camera 5, the mechanical arm, the steering engine of the front wheel of the trolley, the infrared reflection sensor 12 and the storage battery pack 10.
The foregoing description and drawings represent specific embodiments of the present invention in a manner that enables the technical solutions of the present invention to be fully practiced. In the description of the present invention, unless otherwise specified and limited, the terms "connected" and "connecting" are to be construed broadly, and may be mechanical or electrical, or may be internal to two elements, or may be directly connected or indirectly connected through an intermediate medium. The above-mentioned embodiments are merely preferred embodiments of the present invention, and not intended to limit the scope of the present invention, so that equivalent changes or modifications made by the structure, features and principles of the present invention should be included in the claims of the present invention. The present invention is not limited to the structures that have been described above and shown in the drawings, and various modifications and changes can be made without departing from the working principle thereof. The scope of the present invention is limited only by the appended claims.
Claims (7)
1. The utility model provides a from picking up peanut harvester based on image processing which characterized in that: including the dolly body and install the arm on the dolly body, camera (5), control box (6), peanut containing box (8), storage battery (10), install rotation camera (5) at the foremost upper portion of dolly body, the arm subassembly is located the upper surface at dolly body front end top, control box (6) are located the first half of dolly body inside, the latter half at the dolly body is installed in peanut containing box (8), install the rotation motor in the axis of rotation of dolly rear wheel (7), install the steering wheel that turns to in the axis of rotation of dolly front wheel, storage battery (10) are located the position between control box (6) and peanut containing box (8), infrared reflection-type sensor (12) are installed to the top of peanut containing box (8), be equipped with microcomputer processor (9) in control box (6), memory (11), The wireless transmission module (13), the integrated circuit interface end of microcomputer processor (9) is connected with the interface of memory (11), wireless transmission module (13), camera (5), arm, dolly front wheel steering wheel, infrared reflection sensor (12) and storage battery (10) end respectively.
2. The image processing based self-picking peanut harvester of claim 1, wherein: an infrared reflection type sensor (12) connected with a microcomputer processor (9) is installed at the top end of the peanut storage box (8).
3. The image processing-based self-picking peanut harvester of claim 1, wherein: the wireless transmission control terminal equipment is a mobile phone or a computer of a user.
4. The image processing based self-picking peanut harvester of claim 1, wherein: the model of arm be 6 degrees of freedom arms, including arm base (4), the arm rotates joint (3), arm connecting rod (2) and arm tong (1), the rotating device of arm base (4) installs the upper surface at dolly body front end top, arm base (4) are connected with the one end that the arm rotated joint (3) through arm connecting rod (2), the other end that the arm rotated joint (3) is connected with one section arm connecting rod (2) again, and the end and the arm tong (1) of second section arm connecting rod (2) are connected, arm base (4), the arm rotates joint (3), arm connecting rod (2), the integrated circuit interface end of arm tong (1) is connected with the interface of microcomputer processor (9) end.
5. The image processing based self-picking peanut harvester of claim 1, wherein: the camera (5) is a raspberry type camera.
6. The image processing based self-picking peanut harvester of claim 1, wherein: the peanut self-picking harvester takes a wheel type trolley structure as a main body.
7. The image processing based self-picking peanut harvester of claim 1, wherein: an LED lamp is assisted beside the camera (5).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202020819287.1U CN212232163U (en) | 2020-05-15 | 2020-05-15 | Self-picking peanut harvester based on image processing |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202020819287.1U CN212232163U (en) | 2020-05-15 | 2020-05-15 | Self-picking peanut harvester based on image processing |
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| Publication Number | Publication Date |
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| CN212232163U true CN212232163U (en) | 2020-12-29 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202020819287.1U Expired - Fee Related CN212232163U (en) | 2020-05-15 | 2020-05-15 | Self-picking peanut harvester based on image processing |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113875400A (en) * | 2021-08-31 | 2022-01-04 | 高志 | Pickup device suitable for ridge culture plant straw |
| CN115088862A (en) * | 2022-06-14 | 2022-09-23 | 河南中烟工业有限责任公司 | Intelligent picking and detecting device and method for tobacco stems in cigarettes |
-
2020
- 2020-05-15 CN CN202020819287.1U patent/CN212232163U/en not_active Expired - Fee Related
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113875400A (en) * | 2021-08-31 | 2022-01-04 | 高志 | Pickup device suitable for ridge culture plant straw |
| CN115088862A (en) * | 2022-06-14 | 2022-09-23 | 河南中烟工业有限责任公司 | Intelligent picking and detecting device and method for tobacco stems in cigarettes |
| CN115088862B (en) * | 2022-06-14 | 2023-07-18 | 河南中烟工业有限责任公司 | Intelligent picking and detecting device and method for tobacco stems in cigarettes |
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| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20201229 |
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| CF01 | Termination of patent right due to non-payment of annual fee |