CN106808475A - A kind of excellent intelligent robot of visual performance - Google Patents
A kind of excellent intelligent robot of visual performance Download PDFInfo
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- CN106808475A CN106808475A CN201710184827.6A CN201710184827A CN106808475A CN 106808475 A CN106808475 A CN 106808475A CN 201710184827 A CN201710184827 A CN 201710184827A CN 106808475 A CN106808475 A CN 106808475A
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
- B25J9/1697—Vision controlled systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/008—Manipulators for service tasks
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Abstract
The invention provides a kind of excellent intelligent robot of visual performance, including power module, sighting device, control system and robot body, the power module is used to be powered to the sighting device and control system, the sighting device is used to obtain target image, and recognition result is exported, the control system is used to control robot body to make corresponding actions according to the recognition result.Beneficial effects of the present invention are：Realize the intelligent of robot and effectively control.
Description
Technical field
The present invention relates to robotics, and in particular to a kind of excellent intelligent robot of visual performance.
Background technology
Intelligent robot as a kind of technology comprising quite a lot of scientific knowledge, almost along with produced by artificial intelligence
's.And intelligent robot becomes more and more important in today's society, increasing field and post are required for intelligent robot
Participate in, this causes that the research of intelligent robot is also more and more frequent.In the near future, it is continuous with intelligent robot technology
Development and maturation, with the unremitting effort of numerous scientific research personnel, intelligent robot will come into huge numbers of families, preferably service people
Life, make the life of people more comfortable and health.
However, existing robot is mostly just for specific occasion for the mankind service, and robot lacks sighting device, intelligence
Low degree can be changed, poor controllability is directed to specific occasion for the mankind provide service mostly, there is provided function it is relatively single.
The content of the invention
Regarding to the issue above, the present invention is intended to provide a kind of excellent intelligent robot of visual performance.
The purpose of the present invention is realized using following technical scheme：
There is provided a kind of excellent intelligent robot of visual performance, including power module, sighting device, control system and machine
Device human body, the power module is used to be powered to the sighting device and control system, and the sighting device is used to obtain mesh
Logo image, and recognition result is exported, the control system is used to control robot body to make accordingly according to the recognition result
Action.
Beneficial effects of the present invention are：Realize the intelligent of robot and effectively control.
Brief description of the drawings
Using accompanying drawing, the invention will be further described, but embodiment in accompanying drawing is not constituted to any limit of the invention
System, for one of ordinary skill in the art, on the premise of not paying creative work, can also obtain according to the following drawings
Other accompanying drawings.
Fig. 1 is structure connection diagram of the invention.
Reference：
Power module 1, sighting device 2, control system 3, robot body 4, storage device 5.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of excellent intelligent robot of visual performance of the present embodiment, including power module 1, sighting device
2nd, control system 3 and robot body 4, the power module 1 are used to be powered to the sighting device 2 and control system 3, described
Sighting device 2 is used to obtain target image, and exports recognition result, and the control system 3 is used for according to the recognition result control
Robot body processed 4 makes corresponding actions.
The present embodiment realizes the intelligent of robot and effectively control.
Preferably, also including storage device 5, for storing the target image that the sighting device is obtained.
This preferred embodiment realizes the storage of target image.
Preferably, the power module 1 is battery.
Without wiring, movement is more convenient, improves customer experience for this preferred embodiment robot.
Preferably, the sighting device 2 be used for target is identified, including image capture module, single treatment module,
After-treatment module and visual identity module, described image acquisition module are used to obtain target image, the single treatment module
Color characteristic for extracting target image, the after-treatment module obtains color histogram, institute according to the color characteristic
Visual identity module is stated for carrying out tax power to the color histogram, and according to the entitled color histogram to the mesh
Logo image is identified.
The present embodiment intelligent robot accurately can be identified to the target in image.
Preferably, the single treatment module includes the first conversion unit and the second cutting unit, and first conversion is single
For image to be transformed into CIELab color spaces from RGB color, the conversion formula is for unit：
In above-mentioned formula, EH, EM, CS are respectively RGB face
Red, green, blue color component value in the colour space, L is the brightness in CIELab color spaces, and a is in CIELab color spaces
Green to red relative colorimetric, b is relative colorimetric of the blueness in CIELab color spaces to yellow, wherein, functionSecond cutting unit is used to divide an image into equal-sized rectangle
Sub-block, the image I for dividing sub-block is expressed as：In above-mentioned formula, UiRepresent
Any sub-block of image, ZC represents the image segmentation factor, and ZC ∈ [2,5] and ZC are integer, i according to from left to right, from the top down
Order value is 1 to ZC successively2。
Be transformed into for target image by single treatment module more meet human vision by this preferred embodiment intelligent robot
The CIELab color spaces of feature, can more accurately reflect the vision difference degree between different color, by figure
As being divided and being set the image segmentation factor, image recognition accuracy and recognition efficiency can be taken into account, further increase intelligence
The service level of energy robot.
Preferably, the after-treatment module, specially：The first step：CIELab color spaces are divided, using such as
Lower division methods：When L * component is more than threshold value T1When or less than threshold value T2When, a components and b components are not considered further that, obtain 2 face
Color is interval, when L * component is between threshold value T1And T2Between when, a components and b components are divided into four intervals respectively, obtain 16 face
Color is interval, so as to CIELab color spaces have been divided into 18 color intervals；Wherein, T1∈ [90,100], T2∈[0,10]；
Second step：Define membership function σj,k=1；3rd step：Ask for the color histogram of image, the color histogram of image subblock
It is represented by：MX(Ui)={ z1,z2,…,z18, in above-mentioned formula, MX (Ui) represent image subblock color histogram, zj(j
=1,2 ..., 18) the pixel distribution situation in any color interval is represented,σj,kRepresent k-th pixel category
In j-th degree of membership of color interval, NiRepresent the number of pixels that sub-block is included；The color histogram of image is represented by：In above-mentioned formula, δiThe inverse of sub-block locations weights is represented, wherein,MX (I) represents the color histogram of image subblock.
This preferred embodiment intelligent robot is believed by the spatial distribution that after-treatment module has incorporated pixel color feature
Sub-block locations weights are ceased and set, histogram that is more accurate and meeting Human Visual System is obtained, is further increased and is regarded
Feel the expressive faculty of feature.
Preferably, the visual identity module, including the first computing unit, the second computing unit and image comparison unit,
First computing unit is used to calculate the color distortion between pixel, calculates central pixel point pAWith 3 × 3 neighborhoodsInterior
Meaning neighbor pixel pBAberration RU：Above-mentioned formula
In son, RU (pA,pB) represent pixel pAAnd pBBetween aberration, μ is normalization factor；Second computing unit is used to calculate
The color weight of each sub-block；Described image comparison unit is used to realize image recognition according to image similarity contrast；It is described
The color weight of each sub-block is calculated, following steps are specifically included：The first step, calculates the color complexity of each pixel, meter
Center pixel is calculated relative to 3 × 3 neighborhoodsInterior other 8 color changes of adjacent pixel, obtain central pixel point pAColor answer
Miscellaneous degree FA：In above-mentioned formula, FARepresent pixel pAColor complexity；Second step, calculates every
The color weight of individual sub-block, in any sub-block, by calculating each pixel color weights, obtains the color weight Q of sub-blocki：In above-mentioned formula, UiRepresent any sub-block of image, ZXiRepresent the color weight of sub-block, Ni
The number of pixels that sub-block is included is represented, γ represents the color complexity standard deviation of all pixels point in sub-block, FAAnd FkIt is sub-block
In pixel；It is described that image recognition is realized according to image similarity contrast, specifically, color weight according to sub-block and straight
Side's figure defines two images I1And I2Similarity MH：
In above-mentioned formula, MH (I1,I2) represent two images I1And I2Similarity,WithImage I is represented respectively1
And I2I-th pixel distribution situation of j-th color interval of sub-block, calculates images to be recognized and sample image similarity, choosing
Similarity sample image high is taken as recognition result.
The visual identity module of this preferred embodiment intelligent robot is described to color complexity, reflects vision system
Togetherness knows the sensitivity characteristic of different colours change, color weight and histogram calculation recognisable image and sample image according to sub-block
Between similarity, improve identification precision of the intelligent robot to image.
Target is identified using intelligent robot of the present invention, it is when the image segmentation factor takes different value, identification is accurate
, used as evaluation criterion, compared with ordinary robot, generation is had the beneficial effect that shown in table for true rate and recognition time：
| ZC | Recognition accuracy is improved | Recognition time shortens |
| 2 | 20% | 31% |
| 3 | 25% | 25% |
| 4 | 30% | 20% |
| 5 | 32% | 18% |
| 6 | 36% | 12% |
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of scope is protected, although being explained to the present invention with reference to preferred embodiment, one of ordinary skill in the art should
Work as understanding, technical scheme can be modified or equivalent, without deviating from the reality of technical solution of the present invention
Matter and scope.
Claims (7)
1. the excellent intelligent robot of a kind of visual performance, it is characterized in that, including power module, sighting device, control system and
Robot body, the power module is used to be powered to the sighting device and control system, and the sighting device is used to obtain
Target image, and recognition result is exported, the control system is used to control robot body to make phase according to the recognition result
Should act.
2. the excellent intelligent robot of a kind of visual performance according to claim 1, it is characterized in that, also filled including storage
Put, for storing the target image that the sighting device is obtained.
3. the excellent intelligent robot of a kind of visual performance according to claim 2, it is characterized in that, the power module is
Battery.
4. the excellent intelligent robot of a kind of visual performance according to claim 3, it is characterized in that, the sighting device is used
It is identified in target, including image capture module, single treatment module, after-treatment module and visual identity module, institute
State image capture module is used to extract the color characteristic of target image, institute for obtaining target image, the single treatment module
State after-treatment module and color histogram is obtained according to the color characteristic, the visual identity module is used for straight to the color
Square figure carries out tax power, and the target image is identified according to the entitled color histogram.
5. the excellent intelligent robot of a kind of visual performance according to claim 4, it is characterized in that, the single treatment mould
Block includes the first conversion unit and the second cutting unit, and first conversion unit is used to change image from RGB color
To CIELab color spaces, the conversion formula is： In above-mentioned formula, EH, EM, CS are respectively RGB face
Red, green, blue color component value in the colour space, L is the brightness in CIELab color spaces, and a is in CIELab color spaces
Green to red relative colorimetric, b is relative colorimetric of the blueness in CIELab color spaces to yellow, wherein, functionSecond cutting unit is used to divide an image into equal-sized rectangle
Sub-block, the image I for dividing sub-block is expressed as：In above-mentioned formula, UiRepresent
Any sub-block of image, ZC represents the image segmentation factor, and ZC ∈ [2,5] and ZC are integer, i according to from left to right, from the top down
Order value is 1 to ZC successively2。
6. the excellent intelligent robot of a kind of visual performance according to claim 5, it is characterized in that, the after-treatment mould
Block, specially：The first step：CIELab color spaces are divided, using following division methods：When L * component is more than threshold value T1
When or less than threshold value T2When, a components and b components are not considered further that, 2 color intervals are obtained, when L * component is between threshold value T1And T2
Between when, a components and b components are divided into four intervals respectively, 16 color intervals are obtained, so as to by CIELab color spaces
It has been divided into 18 color intervals；Wherein, T1∈ [90,100], T2∈[0,10]；Second step：Define membership function σj,k=
1；3rd step：The color histogram of image is asked for, the color histogram of image subblock is represented by：MX(Ui)={ z1,z2,…,
z18, in above-mentioned formula, MX (Ui) represent image subblock color histogram, zj(j=1,2 ..., 18) represent any chromatic zones
Between on pixel distribution situation,σj,kRepresent k-th pixel and belong to j-th degree of membership of color interval, Ni
Represent the number of pixels that sub-block is included；The color histogram of image is represented by：
In above-mentioned formula, δiThe inverse of sub-block locations weights is represented, wherein, MX (I) represents that the color of image subblock is straight
Fang Tu.
7. the excellent intelligent robot of a kind of visual performance according to claim 6, it is characterized in that, the visual identity mould
Block, including the first computing unit, the second computing unit and image comparison unit, first computing unit are used to calculate pixel
Between color distortion, calculate central pixel point pAWith 3 × 3 neighborhoodsInterior arbitrary neighborhood pixel pBAberration RU：In above-mentioned formula, RU (pA,pB) represent pixel
pAAnd pBBetween aberration, μ is normalization factor；Second computing unit is used to calculate the color weight of each sub-block；The figure
As comparison unit is used to realize image recognition according to image similarity contrast；The color weight for calculating each sub-block, tool
Body is comprised the following steps：The first step, calculates the color complexity of each pixel, calculates center pixel relative to 3 × 3 neighborhoods
Interior other 8 color changes of adjacent pixel, obtain central pixel point pAColor complexity FA：In above-mentioned formula, FARepresent pixel pAColor complexity；Second step, calculates each sub-block
Color weight, in any sub-block, by calculating each pixel color weights, obtain the color weight Q of sub-blocki：In above-mentioned formula, UiRepresent any sub-block of image, ZXiRepresent the color weight of sub-block, Ni
The number of pixels that sub-block is included is represented, γ represents the color complexity standard deviation of all pixels point in sub-block, FAAnd FkIt is sub-block
In pixel；It is described that image recognition is realized according to image similarity contrast, specifically, color weight according to sub-block and straight
Side's figure defines two images I1And I2Similarity MH：
In above-mentioned formula, MH (I1,I2) represent two images I1And I2Similarity,WithImage is represented respectively
I1And I2I-th pixel distribution situation of j-th color interval of sub-block, calculates images to be recognized and sample image similarity, choosing
Similarity sample image high is taken as recognition result.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109079825A (en) * | 2017-06-14 | 2018-12-25 | 天津玛斯特车身装备技术有限公司 | Robot automation's visual grasping system |
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| CN101947788A (en) * | 2010-06-23 | 2011-01-19 | 焦利民 | Intelligent robot |
| US20170074724A1 (en) * | 2011-06-21 | 2017-03-16 | Sony Corporation | Unevenness inspection apparatus and unevenness inspection method |
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