CN202819064U - Grape winter pruning operation device based on machine vision - Google Patents
Grape winter pruning operation device based on machine vision Download PDFInfo
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- CN202819064U CN202819064U CN 201220160040 CN201220160040U CN202819064U CN 202819064 U CN202819064 U CN 202819064U CN 201220160040 CN201220160040 CN 201220160040 CN 201220160040 U CN201220160040 U CN 201220160040U CN 202819064 U CN202819064 U CN 202819064U
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- beta pruning
- mechanical arm
- pruning
- grape
- machine vision
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- 235000009754 Vitis X bourquina Nutrition 0.000 title claims abstract description 34
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- 235000014787 Vitis vinifera Nutrition 0.000 title claims abstract description 34
- 240000006365 Vitis vinifera Species 0.000 title 1
- 241000219095 Vitis Species 0.000 claims abstract description 33
- 210000003857 wrist joint Anatomy 0.000 claims abstract description 11
- 210000002310 elbow joint Anatomy 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims abstract description 6
- 210000000323 shoulder joint Anatomy 0.000 claims abstract description 6
- 210000000245 forearm Anatomy 0.000 claims abstract description 5
- 238000010191 image analysis Methods 0.000 claims abstract description 4
- 238000005520 cutting process Methods 0.000 claims description 34
- 238000012549 training Methods 0.000 claims description 13
- 241001237160 Kallima inachus Species 0.000 claims description 6
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- 238000013459 approach Methods 0.000 claims description 3
- 238000002955 isolation Methods 0.000 claims description 3
- 238000009966 trimming Methods 0.000 abstract 3
- 230000033001 locomotion Effects 0.000 description 10
- 238000000034 method Methods 0.000 description 6
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- 238000011160 research Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
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- 230000000007 visual effect Effects 0.000 description 2
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- 240000008067 Cucumis sativus Species 0.000 description 1
- 235000010799 Cucumis sativus var sativus Nutrition 0.000 description 1
- 235000007688 Lycopersicon esculentum Nutrition 0.000 description 1
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- 235000015103 Malus silvestris Nutrition 0.000 description 1
- 240000008790 Musa x paradisiaca Species 0.000 description 1
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- 240000003768 Solanum lycopersicum Species 0.000 description 1
- 244000237969 Vitis vulpina Species 0.000 description 1
- 235000017242 Vitis vulpina Nutrition 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
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- 238000005094 computer simulation Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
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Abstract
A grape winter pruning operation device based on machine vision comprises an automatic navigation vehicle-mounted platform, an image acquisition box, a trimming module and a pruning module. The image acquisition box is mounted on the automatic navigation vehicle-mounted platform and divided into an operation area and an equipment area; the trimming module is mounted in the operation area; the pruning module is mounted in the equipment area; the automatic navigation vehicle-mounted platform comprises a pan-and-tilt camera, driving wheels and driven wheels; the trimming module comprises a dicing saw and a blower; the pruning module comprises a binocular camera, an agricultural pruning mechanical arm and an industrial personal computer; the agricultural pruning mechanical arm is sequentially connected with a foundation support, a shoulder joint, an upper arm, an elbow joint, a forearm and wrist joints from bottom to top; the wrist joints are connected with tail end pruning shears; the binocular camera is used for acquiring images of grape branches; the agricultural pruning mechanical arm is used for finishing pruning; and the industrial personal computer is used for image analysis processing and mechanical arm track planning. The grape winter pruning operation device based on the machine vision can reduce labor intensity and improve work efficiency.
Description
Technical field
The utility model relates to the Intelligent agricultural machinery field, and especially a kind of grape winter is cut apparatus for work.
Background technology
Pruning viny can growth regulation and result's relation, to increase vintage.Annual wine-growing need to carry out the winter cut, the repeatedly beta pruning training such as renewal pruning, summer are cut.In the vine planting process, beta pruning link workload is large, and task is heavy.At present, the beta pruning link is still take manual work as main, and Mechanization Level is very low, and labour intensity is very large, needs the more equipment of high-effective and labour-saving, and the orchard worker is saved out from heavy hand labour.
Machine vision is the research computer simulation biology Science and Technology of aobvious or macroscopical visual performance outward, relates to artificial intelligence, Neurobiology, computer science, image is processed and the cross discipline in a plurality of fields such as pattern-recognition.To be phase early 1970s in remote sensing image and two application technologies of biomedical picture analyzing obtain machine vision technique begins to rise after fruitful, and its theoretical foundation is the Marr theory of vision computing that forms gradually the middle and later periods seventies.Research and the application of computer vision technique on agricultural machinery, start from phase late 1970s, main research in concentrated and the agricultural product sorting machine utilizes computer vision technique that agricultural product (such as apple, peach, banana, tomato, cucumber etc.) are carried out Quality Detection and classification etc., and some has obtained the practicality achievement.
The algorithm research of processing for grape branch image at present is very few.We can run into following problem during in the beta pruning operation in the applied for machines vision: in view of vine belongs to liane, growth fraction is freer, easily occurs crisscross between branch; Soil colour and winter grape branch color close; Winter, dead leaf blocked branch, affected branch IMAQ etc.This class problem so that when gathering the vine image background complicated, this has increased the algorithm difficulty when giving applied for machines visual identity grape branch.Because image information is redundant, use relatively poor based on the beta pruning operation real-time of machine vision simultaneously.We need to improve vine beta pruning system based on machine vision these problem an urgent demands.
The utility model content
Cut the deficiency that labour intensity is large, operating efficiency is lower of operation in order to overcome the existing grape winter, the utility model provides a kind of grape winter based on machine vision of reducing labour intensity, increasing work efficiency to cut apparatus for work.
The technical scheme that its technical problem that solves the utility model adopts is:
A kind of grape winter based on machine vision is cut apparatus for work, comprise self-navigation vehicular platform, IMAQ case, training module and beta pruning module, described IMAQ case is installed on the self-navigation vehicular platform, described IMAQ case divides operation area and two spaces, battery limits, the training module is installed on the workspace, and the beta pruning module is installed on battery limits;
Described self-navigation vehicular platform comprises monopod video camera, driving wheel and driven pulley, and monopod video camera is installed on self-navigation vehicular platform dead ahead, is used for the acquisition approach image information; Motor driver is installed in the self-navigation vehicular platform, is used for driving running gear; Described motor driver is connected with travel driving motor, described travel driving motor and driving wheel interlock;
Described training module comprises cast-cutting saw and hair-dryer, and cast-cutting saw is used for cutting long branch, and hair-dryer is for the residual dead leaf that blows off before the beta pruning, and cutting machine and hair-dryer all have motor driver control, and motor driver is connected with the motor of being connected with cutting motor;
Described beta pruning module comprises binocular camera, agriculture beta pruning mechanical arm and industrial computer, connect successively pedestal, shoulder joint, large arm, elbow joint, forearm and wrist joint in the agricultural beta pruning mechanical arm from bottom to top, described wrist joint is connected with terminal shrub and hedge trimmer, binocular camera is used for gathering grape branch image, agricultural beta pruning mechanical arm is used for finishing the beta pruning operation, and industrial computer is used for image analysis processing and mechanical arm trajectory planning.
Further, described IMAQ case comprises wall, top cover and equipment room, and described wall is the single pure white vision collecting wall of one side, is used for the isolation complex background; Hair-dryer is arranged at the top cover middle; Two high-frequency florescent lamp pipes are equipped with as the top light source in the hair-dryer both sides; Be provided with two high-frequency florescent lamps in equipment room end face dead ahead as positive light source; Positive front portion, equipment room bottom surface is provided with agriculture beta pruning mechanical arm; Be provided with binocular camera in agriculture beta pruning mechanical arm both sides; Be provided with industrial computer in dead astern, equipment room bottom surface.
Wall, top cover and position, equipment room both sides of the edge are provided with the cast-cutting saw installing space, and described cast-cutting saw installing space is separated by dividing plate.
Two IMAQ casees about loading at least on the self-navigation vehicular platform.
Described top cover adopts bolt to fix with being connected of wall, equipment room.
The beneficial effects of the utility model are mainly manifested in: cut in the operational method in the grape winter based on machine vision, aspect IMAQ, the interference problem in the time of can effectively solving complex background for target branch IMAQ has been simplified image recognition algorithm; Aspect operating efficiency, reduced the image information data amount, the real-time, the accuracy that have strengthened the identification of grape branch and pruned.
Description of drawings
Fig. 1 is the general structure schematic diagram of cutting apparatus for work the grape winter;
Fig. 2 is the wall schematic diagram of cutting apparatus for work the grape winter;
Fig. 3 is the top cover upward view of cutting apparatus for work the grape winter;
Fig. 4 a is the equipment room structural representation of cutting apparatus for work the grape winter;
Fig. 4 b is the end view of Fig. 4 a.
Fig. 5 is the workflow diagram of the grape winter cutting apparatus for work.
Wherein, 1, self-navigation vehicular platform; 2, IMAQ case; 3, training module; 4, beta pruning module; 5, wall; 6, top cover; 7, equipment room; 8, monopod video camera; 9, driving wheel; 10, driven pulley; 11, cast-cutting saw; 12, hair-dryer; 13, binocular camera; 14, agriculture beta pruning mechanical arm; 15, industrial computer; 16, top light source; 17, positive light source; 18, pedestal; 19, shoulder joint; 20, large arm; 21, elbow joint; 22, forearm; 23, wrist joint; 24, terminal shrub and hedge trimmer.
Embodiment
Below in conjunction with accompanying drawing and the present embodiment the utility model is described in further detail.
With reference to Fig. 1 ~ Fig. 5, a kind of grape winter based on machine vision is cut apparatus for work, comprises self-navigation vehicular platform 1, IMAQ case 2, training module 3, beta pruning module 4.IMAQ case described in the utility model is installed on the self-conductance vehicle-mounted navigation platform, and minute operation area and two spaces, battery limits are comprised of wall 5, top cover 6, equipment room 7 three parts.Training module 3 is installed on the workspace, and beta pruning module 4 is installed on battery limits.
Described self-navigation vehicular platform 1 comprises monopod video camera 8, driving wheel 9 and driven pulley 10, and cradle head controllor 8 is installed on self-navigation vehicular platform headstock dead ahead, is used for the acquisition approach image information; Motor driver is installed in the self-navigation vehicular platform, is used for driving running gear; Described motor driver is connected with travel driving motor, described travel driving motor and driving wheel interlock; Described motor driver by industrial computer by the motion control card control.
Described training module 3 comprises cast-cutting saw 11 and hair-dryer 12, cast-cutting saw 11 is used for cutting long branch, hair-dryer 12 is for the residual dead leaf that blows off before the beta pruning, and cutting machine 11 and hair-dryer 12 all have motor driver control, and motor driver is connected with the motor of being connected with cutting motor.Described motor driver by industrial computer by the motion control card control.
Described beta pruning module comprises binocular camera 13, agriculture beta pruning mechanical arm 14 and industrial computer 15, connect successively pedestal 18, shoulder joint 19, large arm 20, elbow joint 21, forearm 22 and wrist joint 23 in the agricultural beta pruning mechanical arm 14 from bottom to top, described wrist joint is connected with terminal shrub and hedge trimmer, the design of employing 5DOF, i.e. pedestal 18 rotations, shoulder joint 19 pitching, elbow joint 21 pitching, wrist joint 23 pitching, wrist joint 23 rotations.Binocular camera 13 is used for gathering grape branch image, and image pick-up card is used for transmitting image information, and agriculture beta pruning mechanical arm 14 is used for finishing the beta pruning operation, and industrial computer 15 is used for image analysis processing and mechanical arm trajectory planning.
Described IMAQ case 2 comprises wall 5, top cover 6 and equipment room 7
Further, described IMAQ case 2 comprises wall 5, top cover 6 and equipment room 7, and described wall 5 is the single pure white vision collecting wall of one side, is used for the isolation complex background; Hair-dryer 12 is arranged at top cover 6 middles; Two high-frequency florescent lamp pipes are equipped with as top light source 17 in hair-dryer 12 both sides; Be provided with two high-frequency florescent lamps in equipment room 7 end face dead aheads as positive light source 16; Positive front portion, equipment room bottom surface is provided with agriculture beta pruning mechanical arm 14; Be provided with binocular camera 13 in agriculture beta pruning mechanical arm 14 both sides; Be provided with industrial computer 15 in dead astern, equipment room bottom surface.
In addition, top cover 6 with adopting the fixing beta pruning operational method described in the utility model of bolt being connected of wall 5, equipment room 7 is:
(1), opens self-navigation and training.Self-navigation vehicular platform 1 moves along vineyard single-pass road, and it is also thereupon mobile that the grape winter is cut apparatus for work 2.The long branch of cast-cutting saw 11 cuttings makes the branch length that enters the workspace reasonable, is convenient to follow-up beta pruning operation; Hair-dryer 12 dead leaf that blows off is eliminated dead leaf and is blocked interference when gathering grape branch image.
(2), the grape winter cuts apparatus for work 2 and moves to proportional space position (general displacement is the width of a wall), and cast-cutting saw 11 stops, and hair-dryer 12 stops.
(3), gather grape branch image.Top light source 16 and positive light source 17 provide active light source (positive light source 17 can manually be realized angle, position adjustment), eliminate the shade on the wall, open binocular camera 13.
(4), analyzing and processing grape branch image.The image information that binocular camera 13 collects is sent to industrial computer 15 by image pick-up card.
15 pairs of image informations of industrial computer are carried out the treatment steps such as image preliminary treatment, figure image intensifying, image segmentation, image recognition.Identify target with trunk in morphologic difference according to the vine lopwood is dried, analyze and definite beta pruning point, extract beta pruning point three-dimensional coordinate information.
(5), plan agriculture beta pruning mechanical arm 14 movement locus.According to beta pruning point three-dimensional coordinate information, 15 pairs of agriculture beta pruning mechanical arms 14 of industrial computer carry out movement locus planning, calculate each joint optimal movement parameter.
(6), finish the beta pruning operation.Industrial computer 15 sending controling instructions by the action control of motion control card realization to agriculture beta pruning mechanical arm 14 each joint, are finally realized the beta pruning operation.
(7), agriculture beta pruning mechanical arm 14 recovers original pose.After the beta pruning operation was complete, agriculture beta pruning mechanical arm 14 was retracted to equipment room 7, recovers original pose, and sent the beta pruning END instruction to industrial computer 15.
(8), start cast-cutting saw 11 and hair-dryer 12.After receiving the beta pruning END instruction, industrial computer 15 sends instruction to motion control card, starts cast-cutting saw 11 and hair-dryer 12, begins the training work of next operating position.
(9), start self-navigation vehicular platform 1.Industrial computer 15 sends the enabled instruction of self-navigation vehicular platform, and self-navigation vehicular platform 1 begins to move to next operating position and beta pruning.So analogize, repeat operation.
(10), the beta pruning end of job.After single vine is all finished the beta pruning operation, shut down.
In the present embodiment, cast-cutting saw 11 adopts the timber cast-cutting saw of 1380W.
The high-frequency florescent lamp pipe that top light source 16 is 30kHz by two 20W stroboscopics forms, and is distributed in side by side on the top cover 6.Two high-frequency florescent lamps bubbles of positive light source 17 main employings, two lamp light angles can manually be adjusted, and in conjunction with actual photoenvironment, eliminate shadow interference.
Image pick-up card adopts the Morphis image pick-up card, and binocular camera 13 adopts the CCD industrial camera of 44W pixel.It is anterior that binocular camera 13 is fixed on the equipment room bottom surface, and image pick-up card inserts the PCI groove in the industrial computer 15, and industrial computer 15 is fixed on rear portion, equipment room 7 bottom surface.
Motion control card adopts the general motion control card of PCI bus based on TMS320F2812.Motion control card inserts the PCI groove in the industrial computer 14.
Interference problem when a kind of grape winter based on machine vision that the utility model relates to cuts apparatus for work and can effectively solve complex background and gather for the target branch, simplified image recognition algorithm, improve operating efficiency, strengthened real-time, the accuracy of the identification of grape branch and beta pruning.
Embodiment recited above is described preferred embodiment of the present utility model; be not that design of the present utility model and scope limit; for those skilled in the art; under the prerequisite that does not break away from the utility model design concept; various modification and the improvement that can make the technical solution of the utility model all fall into protection domain of the present utility model.
Claims (5)
1. the grape winter based on machine vision is cut apparatus for work, it is characterized in that: comprise self-navigation vehicular platform, IMAQ case, training module and beta pruning module, described IMAQ case is installed on the self-navigation vehicular platform, described IMAQ case divides operation area and two spaces, battery limits, the training module is installed on the workspace, and the beta pruning module is installed on battery limits;
Described self-navigation vehicular platform comprises monopod video camera, driving wheel and driven pulley, and monopod video camera is installed on self-navigation vehicular platform dead ahead, is used for the acquisition approach image information; Motor driver is installed in the self-navigation vehicular platform, is used for driving running gear; Described motor driver is connected with travel driving motor, described travel driving motor and driving wheel interlock;
Described training module comprises cast-cutting saw and hair-dryer, and cast-cutting saw is used for cutting long branch; Hair-dryer is for the residual dead leaf that blows off before the beta pruning, and cutting machine and hair-dryer all have motor driver control, and motor driver is connected with the motor of being connected with cutting motor;
Described beta pruning module comprises binocular camera, agriculture beta pruning mechanical arm and industrial computer, connect successively pedestal, shoulder joint, large arm, elbow joint, forearm and wrist joint in the agricultural beta pruning mechanical arm from bottom to top, described wrist joint is connected with terminal shrub and hedge trimmer, binocular camera is used for gathering grape branch image, agricultural beta pruning mechanical arm is used for finishing the beta pruning operation, and industrial computer is used for image analysis processing and mechanical arm trajectory planning.
2. the grape winter based on machine vision as claimed in claim 1 is cut apparatus for work, it is characterized in that: described IMAQ case comprises wall, top cover and equipment room, described wall is the single pure white vision collecting wall of one side, is used for the complicated back of the body of isolation; Hair-dryer is arranged at the top cover middle; Two high-frequency florescent lamp pipes are equipped with as the top light source in the hair-dryer both sides; Be provided with two high-frequency florescent lamps in equipment room end face dead ahead as positive light source; Positive front portion, equipment room bottom surface is provided with agriculture beta pruning mechanical arm; Be provided with binocular camera in agriculture beta pruning mechanical arm both sides; Be provided with industrial computer in dead astern, equipment room bottom surface.
3. the grape winter based on machine vision as claimed in claim 2 is cut apparatus for work, it is characterized in that: wall, top cover and position, equipment room both sides of the edge are provided with the cast-cutting saw installing space, and described cast-cutting saw installing space is separated by dividing plate.
4. cut apparatus for work based on the grape winter of machine vision as claimed in claim 2 or claim 3, it is characterized in that: two IMAQ casees about loading at least on the self-navigation vehicular platform.
5. cut apparatus for work based on the grape winter of machine vision as claimed in claim 2 or claim 3, it is characterized in that: described top cover adopts bolt to fix with being connected of wall, equipment room.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201220160040 CN202819064U (en) | 2012-04-13 | 2012-04-13 | Grape winter pruning operation device based on machine vision |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201220160040 CN202819064U (en) | 2012-04-13 | 2012-04-13 | Grape winter pruning operation device based on machine vision |
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| CN202819064U true CN202819064U (en) | 2013-03-27 |
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| CN 201220160040 Expired - Lifetime CN202819064U (en) | 2012-04-13 | 2012-04-13 | Grape winter pruning operation device based on machine vision |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102696411A (en) * | 2012-04-13 | 2012-10-03 | 浙江工业大学 | Grape winter-pruning operation device based on machine vision |
| CN105052570A (en) * | 2015-07-09 | 2015-11-18 | 青岛大学 | 3D vegetation trimming device |
| CN106493429A (en) * | 2016-12-13 | 2017-03-15 | 北京小米移动软件有限公司 | Cutting equipment and its control method, control device |
| CN114102591A (en) * | 2021-11-24 | 2022-03-01 | 北京市农林科学院智能装备技术研究中心 | Operation method and device for agricultural robot mechanical arm |
-
2012
- 2012-04-13 CN CN 201220160040 patent/CN202819064U/en not_active Expired - Lifetime
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102696411A (en) * | 2012-04-13 | 2012-10-03 | 浙江工业大学 | Grape winter-pruning operation device based on machine vision |
| CN105052570A (en) * | 2015-07-09 | 2015-11-18 | 青岛大学 | 3D vegetation trimming device |
| CN106493429A (en) * | 2016-12-13 | 2017-03-15 | 北京小米移动软件有限公司 | Cutting equipment and its control method, control device |
| CN114102591A (en) * | 2021-11-24 | 2022-03-01 | 北京市农林科学院智能装备技术研究中心 | Operation method and device for agricultural robot mechanical arm |
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| C14 | Grant of patent or utility model | ||
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| AV01 | Patent right actively abandoned |
Granted publication date: 20130327 Effective date of abandoning: 20131113 |
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| AV01 | Patent right actively abandoned |
Granted publication date: 20130327 Effective date of abandoning: 20131113 |
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| RGAV | Abandon patent right to avoid regrant |