CN105025619B - Based on the light-source brightness adjusting method that dark surrounds is tackled in robot kinematics - Google Patents
Based on the light-source brightness adjusting method that dark surrounds is tackled in robot kinematics Download PDFInfo
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Abstract
The invention provides a kind of based on the light-source brightness adjusting method that dark surrounds is tackled in robot kinematics, it carries out calibration experiment by robot vision detecting system, obtain light-source brightness grade, Mathematical Modeling between brightness of image quality and robot observed range three, then this Mathematical Modeling is added in robot motion's trajectory planning optimization process, set up a time and the optimal Optimized model of light intensity, also an optimal light intensity track to ensure picture quality is obtained while obtaining time optimal robot motion's trajectory path by solving-optimizing model, finally while robot is moved according to the track of planning, optimal light intensity track according to obtaining issues light-source brightness control instruction to light source controller.Light-source brightness can be realized being automatically adjusted in robot kinematics come the change of balanced robot's observed range by the inventive method, to ensure the image quality of the camera on end effector of robot.
Description
Technical field
It is specifically a kind of based on robot fortune the present invention relates to robot, industry spot scene visual detection field
The light-source brightness adjusting method of dark surrounds is tackled during dynamic, in the process that robot is moved along the movement locus of planning
In, light-source brightness automatically adjusts to ensure the image quality of robot end's camera, it is to avoid the feelings of image darker or lighter occur
Condition.
Background technology
In some extreme (high temperature, dark etc.) working environments for being not suitable for manual work, usually through in robotic
Arm end fixedly mounts camera and LED light source, and the scene inside monitoring extreme environment is detected using remote operating manipulator motion
Information, for follow-up attended operation provides important information.The camera imaging quality of mechanical arm tail end is to whole vision detection system
It is most important, and in dark environment, due to the motion of mechanical arm, the observation on the surface of camera and light source distance observation thing away from
From not being fixed, but can change, in the case where system is required to figure picking rate, camera exposure parameter is normal
It is often changeless, now, if light-source brightness is constant do not adjusted, imageing sensor just occurs under-exposed or saturation,
Cause image frame darker or lighter, lose the detailed information on detection object surface, therefore in the light durability and of light source
When even property is guaranteed, the brightness regulation of light source turns into the key factor for obtaining high-quality original image.With industrial automatic
The raising of change degree, the control to light source is no longer limited only to manual setting and regulation, in order in robot kinematics
In, the brightness of automatic control and adjustment light source is reached, ensure camera imaging quality, it is necessary to study a kind of based on robot motion's
Vision inspection process always tackles the light-source brightness adjusting method of dark surrounds.
The content of the invention
It is black based on being tackled in robot kinematics it is an object of the invention to provide one kind for defect of the prior art
The light-source brightness adjusting method of dark situation.
During robot is moved under dark surrounds, in order to ensure vision-based detection camera imaging quality and realization
The automation regulation of light-source brightness, the present invention provides a kind of based on the light-source brightness that dark surrounds is tackled in robot kinematics
Adjusting method, the method carries out calibration experiment by robot vision detecting system first, obtains light-source brightness grade, image
Mathematical Modeling between brightness quality and robot observed range three, is then used in robot motion by this Mathematical Modeling
In the optimization process of trajectory planning, so as to obtain the optimal light-source brightness value track corresponding with movement locus, so as in machine
During people moves along the track of optimization, the light-source brightness value track that light-source brightness value is obtained according to optimization adjusts to ensure
Camera imaging quality.
To realize above-mentioned technical purpose, the technical solution adopted in the present invention is：Based on reply in robot kinematics
The light-source brightness adjusting method of dark surrounds.Specifically include following steps：
Step 1：In order to quantify subjective assessment of the people to brightness of image quality, brightness of image quality evaluation index A is set up.
Step 2：In the robot vision detecting system being mainly made up of robot, camera, light source, light source controller,
Camera and light source are installed on the end effector of robot, due to the material properties on examined object surface, light source control
The difference of the brightness degree scope of device and observed range scope is, it is necessary to carry out calibration experiment to robot vision detecting system
Set up light-source brightness grade E, the Mathematical Modeling between brightness of image quality evaluation index A and observed range D three and provide real
Test data.
Step 3：The experimental data provided according to step 2 carries out data fitting to set up light-source brightness grade E, brightness of image
Mathematical Modeling A=F (E, D) between quality evaluation index A and observed range D, wherein, F (E, D) represents the letter on E, D
Number.
Step 4：To be obtained in step 3 on A, E, the Mathematical Modeling between D is used in the excellent of robot trajectory planning
During change, a time and the optimal robot motion's track optimizing model of light-source brightness are set up
Step 5：By the Optimized model in solution procedure 4, obtain time most short robot motion track and with motion
The corresponding optimal light-source brightness value track in track.In the case of observed range change in the motion process of robot, the light
Source brightness value track can guarantee that the image quality of the camera installed in robot end, be not in the feelings of image darker or lighter
Condition.
Step 6：While robot is moved according to the time that step 5 is obtained most short robot motion track, to light source
The optimal light intensity brightness value track corresponding with movement locus that controller is also obtained according to step 5 issues brightness regulation control and refers to
Order is with accordance with track such that it is able to solve the problems, such as the image darker or lighter that observed range change brings, it is ensured that camera is in machine
Image quality in device people's motion process.
In the above-mentioned technical solutions, step 1 is specifically included：To realize becoming by brightness of image quality accurate evaluation light intensity
Change, selection carries out graphical analysis with the HSV color spaces that human vision is close, original image is changed by RGB color space
Behind HSV color spaces, the average gray value of image V component (luminance component) is calculated as brightness of image quality evaluation index A,
Computing formula isWherein, the size of image is M*N, and I (u, v) represents the gray value of V component in image
The distribution of plane, u represents the lateral coordinates under image plane pixel coordinate system, and v represents the longitudinal direction seat under plane of delineation coordinate system
Mark.
In the above-mentioned technical solutions, step 2 is specifically included：Calibration experiment is carried out to robot vision detecting system, specifically
Process is：
Step 2.1：First fixed camera apart from examined object observed range D, then by the brightness degree model of light source
Enclose and be divided into K parts (such as 250 parts), change light-source brightness grade and obtain corresponding image, calculate brightness of image quality evaluation
Index A.
Step 2.2：Certain light-source brightness grade (such as 130) is fixed, then changes observed range D, obtain correspondence image
And calculate brightness of image quality evaluation index A.
In the above-mentioned technical solutions, step 3 is specifically included：Set up brightness of image quality evaluation index A, light-source brightness grade
The triangular Mathematical Modeling A=F (E, D) of E, observed range D, detailed process is：
Step 3.1：It is the convenience and accuracy of fitting, to A because A=F (E, D) is a nonlinear complex relationship
Take the logarithm lnA=lnF (E, D) on=F (E, D) formulas both sides, is designated as：
A=lnA, e=lnE, d=lnD,
Obtain：A=f (e, d).
Step 3.2：By the experimental data obtained in step 2 (1), to each variable E, after A takes the logarithm, multinomial is carried out linear
Fitting, obtains linear fit result a=f1(e)=P1e3+P2e2+P3e+P4；Wherein, f1E () represents the result that linear fit is obtained
That is the functional relation expression formula between a and e, P1, P2, P3, P4Polynomial constant coefficient in representative function expression formula.
Step 3.3：Similarly, by the experimental data obtained in step 2 (2), to each variables D, after A takes the logarithm, carry out multinomial
Formula linear fit is obtainedWherein, f2D () represents that linear fit result is the function of a and d
Relational expression,Polynomial constant coefficient in representative function relational expression
Step 3.4：Comprehensive (2) and (3) fitting result is by following equation
The expression of a=f (e, d) can be obtained：
Wherein, a0Represent brightness of image matter
Measure the value after evaluation index A initial values are taken the logarithm, e0Represent light-source brightness E initial values take the logarithm after value, d0At the beginning of representing observed range D
Value take the logarithm after value, C represents the constant entry value in the specific function expressions of a=f (e, d).
Step 3.5：A=lnA, e=lnE, d=lnD substitutes into the specific of the a=f (e, d) that is obtained in step 3.4
A=F (E, D) expression formula is can obtain in expression formula.
In the above-mentioned technical solutions, step 4 is specifically included：Setup time and the optimal robot motion track of light-source brightness
Optimized model, detailed process is：
Step 4.1：If Q1,Q2,……,QnIt is point sequence that trajectory planning passes through in operating space, provides each accordingly
The perfect light source brightness degree E of point1,E2,……,En, by the point sequence Q in operating space1~QnBe converted to by inverse kinematics
After joint variable in joint of mechanical arm space, in adjacent given point sequence QiWith Qi+1According to three between corresponding joint variable
Secondary spline interpolation obtains the cubic polynomial function expression s that joint variable is changed over timei(t)=ci4t3+ci3t2+ci2t+
ci1, wherein, i=1,2 ... ..., n；ci4, ci3, ci2, ci1The constant coefficient of representative polynomial function expression, t is represented by phase
The given point sequence Q of neighbouriWith Qi+1Time interval；
Similarly, in adjacent given point sequence QiWith Qi+1Corresponding EiWith Ei+1Between obtain light using cubic spline interpolation
The cubic polynomial function expression E that source brightness degree is changed over timei(t)=λi4t3+λi3t2+λi2t+λi1, wherein i=1,
2,……,n；λi4, λi3, λi2, λi1The constant coefficient of representative polynomial function expression, t is represented by adjacent given point sequence Qi
With Qi+1Time interval.
Step 4.2：Two object functions of Optimized model are set,
hiRepresent that, by the time interval of adjacent given point sequence, Δ A represents that brightness of image quality refers in sampling time T
Mark the knots modification of A.minTExpression is minimized oeprator, and E (t+T) represents the light-source brightness value at t+T moment, and D (t+T) is represented
The observed range at t+T moment, E (t) represents the light-source brightness value of t, and D (t) represents the observed range of t；
Step 4.3：The constraints of given optimization object function：
Wherein, sup (Vcj) and sup (Acj) it is j-th kinematic constraint upper limit of joint of mechanical arm in joint space, respectively
Represent higher limit, the higher limit of acceleration of speed.AL,AHRepresent that the artificial suitable image of subjective judgement brightness of image quality is bright
Degree quality evaluation index higher limit, lower limit, EHThe higher limit of light-source brightness grade is represented, ζ is then light-source brightness change of rank
The higher limit of amount.J-th speed of joint of mechanical arm in t joint space is represented,Represent t joint space
In j-th acceleration of joint of mechanical arm, A (t) represent t brightness of image quality evaluation index,Represent t light source
Rate of change of brightness；J is positive integer.
In the above-mentioned technical solutions, step 5 is specifically included：Model for Multi-Objective Optimization in solution procedure 4, obtains the time most
Short robot motion track and the optimal light-source brightness value track of the guarantee brightness of image quality corresponding with movement locus.
In the above-mentioned technical solutions, step 6 is specifically included：According to obtaining time most short movement locus and most in step 5
Excellent light-source brightness value track issues control and regulation instruction to Robot Motion Controller and light source controller, so as to ensure robot
Image quality of the end camera in robot kinematics.
Compared with prior art, the present invention has following beneficial effect：
The novel part of the inventive method be by set up light-source brightness grade E, camera distance determinand observation away from
Mathematical Modeling between D and brightness of image quality evaluation index A three, and this Mathematical Modeling is added into robot motion's rail
During mark optimizes, compared to the kinematical constraint that traditional track optimizing model only considers joint space, the inventive method
In Optimized model also contemplate the i.e. high-quality original image of vision-based detection demand in task space, it is bright by adjusting light source
The angle value situation excessively bright or excessively dark to eliminate observed range change brings in motion process image, so as to ensure camera imaging matter
Amount.
Brief description of the drawings
The detailed description made to non-limiting example with reference to the following drawings by reading, further feature of the invention,
Objects and advantages will become more apparent upon：
Fig. 1 is the inventive method flow chart.
Fig. 2 is embodiment of the present invention robot vision detecting system structural representation.
In figure：The cross section of the closed devices to be detected of 1-, 2- mechanical arms, 3- cameras and LED light source
Specific embodiment
With reference to specific embodiment, the present invention is described in detail.Following examples will be helpful to the technology of this area
Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that to the ordinary skill of this area
For personnel, without departing from the inventive concept of the premise, some changes and improvements can also be made.These belong to the present invention
Protection domain.
The present disclosure provides a kind of based on the light-source brightness regulation side that dark surrounds is tackled in robot kinematics
Method.Specifically, the method carries out calibration experiment by robot vision detecting system, obtains light-source brightness grade, image
Mathematical Modeling between brightness quality and robot observed range three, then in robot motion's trajectory planning optimization process
Middle this Mathematical Modeling of addition, sets up a time and the optimal Optimized model of light intensity, when obtaining one by solving-optimizing model
Between optimal robot motion's trajectory path while also obtain an optimal light intensity track to ensure picture quality, finally existing
While robot is moved according to the track of planning, light-source brightness is issued to light source controller according to the optimal light intensity track for obtaining
Control instruction.Can realize being automatically adjusted in robot kinematics light-source brightness come balanced robot by the inventive method
The change of observed range, to ensure the image quality of the camera on end effector of robot.
The present embodiment provides a kind of based on the light-source brightness adjusting method that dark surrounds is tackled in robot kinematics.Figure
2 is embodiment of the present invention robot vision detecting system structural representation, and our purpose is using remote operating mechanical arm tail end
On camera remove the inner surface of the closed cavity of detection, be without illumination dark surrounds in chamber.The inventive method flow chart such as Fig. 1 institutes
Show, the method includes the steps of：
Step 1：In order to quantify subjective assessment of the people to brightness of image quality, brightness of image quality evaluation index A is set up.
Step 2：Calibration experiment is carried out to robot vision detecting system, to set up light-source brightness grade E, brightness of image matter
Mathematical Modeling between amount evaluation index A and observed range D three provides experimental data and prepares.
Step 3：The experimental data provided according to step 2 carries out data fitting to set up light-source brightness grade E, brightness of image
Mathematical Modeling between quality evaluation index A and observed range D, A=F (E, D).
Step 4：To be obtained in step 3 on A, E, the Mathematical Modeling between D is used in the excellent of robot trajectory planning
During change, a time and the optimal robot motion's track optimizing model of light-source brightness are set up.
Step 5：By the Optimized model in solution procedure 4, obtain time optimal robot motion track and with motion
The track of the corresponding optimal light-source brightness value in track.
Step 6：While robot is moved according to the time optimal movement locus that step 5 is obtained, to light source controller
Also the optimal light intensity brightness value track for being obtained according to step 5 issues brightness regulation control instruction such that it is able to solve observed range
The problem of the image darker or lighter that change brings, it is ensured that image quality of the camera in robot kinematics.
It is below detailed implementation steps：
Step 1 specific implementation includes：To realize changing by brightness of image quality accurate evaluation light intensity, selection is regarded with the mankind
The HSV color spaces that feel is close carry out graphical analysis, after original image is converted into HSV color spaces by RGB color space,
The average gray value of image V component (luminance component) is calculated as brightness of image quality evaluation index A, computing formula isWherein, the size of image be M*N, I (u, v) represent V component gray value the plane of delineation point
Cloth.U represents the lateral coordinates under image plane pixel coordinate system, and v represents the longitudinal coordinate under plane of delineation coordinate system.
Step 2 specific implementation includes：
Step 2.1：First fixed camera apart from examined object observed range D, then according to the bright of light source controller
Degree rate range is divided into K parts (such as 250 parts), changes light-source brightness grade and obtains corresponding image, calculates brightness of image
Quality evaluation index A.
Step 2.2：Certain light-source brightness grade (such as 130 parts) is fixed, then changes observed range D, obtain corresponding diagram
Picture simultaneously calculates brightness of image quality evaluation index A.
Step 3 specific implementation includes：Set up brightness of image quality evaluation index A, light-source brightness grade E and observed range
The triangular Mathematical Modeling A=F (E, D) of D, detailed process is：
Step 3.1：It is the convenience and accuracy of fitting, to A because A=F (E, D) is a nonlinear complex relationship
Take the logarithm lnA=lnF (E, D) on=F (E, D) formulas both sides, is designated as：
A=lnA, e=lnE, d=lnD
Obtain：A=f (e, d), wherein, f (e, d) is represented on e, the function of d.
Step 3.2：By the experimental data obtained in step 2 (1), to each variable E, after A takes the logarithm, multinomial is carried out linear
Fitting, obtains linear fit result a=f1(e)=P1e3+P2e2+P3e+P4；Wherein, f1E () represents the result that linear fit is obtained
That is the functional relation expression formula between a and e, P1, P2, P3, P4Polynomial constant coefficient in representative function expression formula.
Step 3.3：Similarly, by the experimental data obtained in step 2 (2), to each variables D, after A takes the logarithm, carry out multinomial
Formula linear fit is obtainedWherein, f2D () represents that linear fit result is the function of a and d
Relational expression,Polynomial constant coefficient in representative function relational expression.
Step 3.4：Combining step 3.2 and step 3.3：Fitting result is by following equation
The expression of a=f (e, d) can be obtainedIts
In, a0Represent brightness of image quality evaluation index initial value A take the logarithm after value, e0After representing that light-source brightness initial value E takes the logarithm
Value, d0Represent observed range initial value D take the logarithm after value, C represents the constant entry value in the specific function expressions of a=f (e, d).
Step 3.5：A=lnA, e=lnE, d=lnD can obtain A=in substituting into result a=f (e, d) obtained in (4)
F (E, D) expression formula.
Step 4 specific implementation includes：Setup time and the optimal robot motion's track optimizing model of light-source brightness, specifically
Process is：
(1) Q is set1,Q2,……,QnIt is point sequence that trajectory planning passes through in operating space, each point reason is given accordingly
Think light-source brightness grade E1,E2,……,En, by the point sequence Q in operating space1~QnMechanical arm is converted to by inverse kinematics
After joint variable in joint space, in adjacent given point sequence QiWith Qi+1Between according to cubic spline interpolation obtain joint become
The cubic polynomial function expression s that amount is changed over timei(t)=ci4t2+ci3t3+ci2t+ci1, similarly, in adjacent set point sequence
Row EiWith Ei+1Between obtain the cubic polynomial function expression that light-source brightness grade is changed over time using cubic spline interpolation
Ei(t)=λi4t3+λi3t2+λi2t+λi1, wherein i=1,2 ... ..., n, ci4, ci3, ci2, ci1, λi4, λi3, λi2, λi1Represent multinomial
The constant coefficient of formula function expression.
(2) two object functions of Optimized model are set,
hiThe time interval of adjacent given point sequence is represented, Δ A represents the brightness of image quality index in sampling time T
Knots modification；minTExpression is minimized oeprator, and E (t+T) represents the light-source brightness value at t+T moment, when D (t+T) represents t+T
The observed range at quarter, E (t) represents the light-source brightness value of t, and D (t) represents the observed range of t.
(3) constraints of optimization object function is given：
Wherein, sup (Vcj) and sup (Acj) it is j-th kinematic constraint upper limit in joint in joint space, speed is represented respectively
Degree, the higher limit of acceleration.AL,AHRepresent the suitable brightness of image quality evaluation index of artificial subjective judgement brightness of image quality
Upper lower limit value, EHThe higher limit of light-source brightness grade is represented, ζ is then the higher limit of light-source brightness change of rank amount,Represent t
J-th speed in joint in moment joint space,Represent j-th acceleration in joint, A (t) tables in t joint space
Show t brightness of image quality evaluation index,Represent t light-source brightness rate of change.
Step 5 specific implementation includes：Model for Multi-Objective Optimization in solution procedure 4, obtain the time it is most short robot fortune
The optimal light-source brightness value track of dynamic rail mark and the guarantee brightness of image quality corresponding with movement locus.
Step 6 specific implementation includes：According to obtaining time most short movement locus and optimal light-source brightness value rail in step 5
Mark issues control and regulation instruction to Robot Motion Controller and light source controller, so as to ensure robot end's camera in machine
Image quality in people's motion process.
Specific embodiment of the invention is described above.It is to be appreciated that the invention is not limited in above-mentioned
Particular implementation, those skilled in the art can within the scope of the claims make a variety of changes or change, this not shadow
Sound substance of the invention.
Claims (2)
1. a kind of based on the light-source brightness adjusting method that dark surrounds is tackled in robot kinematics, it is characterised in that including
Following steps：
Step 1：Set up brightness of image quality evaluation index A；
Step 2：Calibration experiment is carried out to robot vision detecting system, is commented to set up light-source brightness grade E, brightness of image quality
Mathematical Modeling between valency index A and observed range D three provides experimental data；
Step 3：The experimental data provided according to step 2 carries out data fitting to set up light-source brightness grade E, brightness of image quality
Mathematical Modeling A=F (E, D) between evaluation index A and observed range D, wherein, F (E, D) represents the function on E, D；
Step 4：According to being obtained in step 3 on the Mathematical Models robot motion's track optimizing model between A, E, D；
Step 5：By the Optimized model in solution procedure 4, obtain time most short robot motion track and the time is most short
The track of the corresponding optimal light-source brightness value in robot motion track；
Step 6：Time for being obtained according to Optimization Solution in step 5 most short robot motion track and time most short machine
The corresponding optimal light-source brightness value track of people's movement locus, issues control and adjusts to Robot Motion Controller and light source controller
Section instruction；
The step 2 is specifically included：
Step 2.1：The observed range D of the camera distance examined object of stationary machines people vision detection system first, then will
The brightness degree scope of light source is divided into K parts, changes light-source brightness grade and obtains corresponding original image, calculates original image
Brightness of image quality evaluation index A；
Step 2.2：Fixed light source brightness degree, then changes observed range D, obtains correspondence original image and calculates original image
Brightness of image quality evaluation index A；
The step 3 is specifically included：
Step 3.1：Take the logarithm lnA=lnF (E, D) to A=F (E, D) formulas both sides, is designated as：
A=lnA, e=lnE, d=lnD,
A=f (e, d) is obtained, wherein, f (e, d) is represented on e, the function of d；
Step 3.2：By the experimental data obtained in step 2.1, to each variable E, after A takes the logarithm, multinomial linear fit is carried out,
Obtain linear fit result a=f1(e)=P1e3+P2e2+P3e+P4；Wherein, f1E () represents the result that linear fit is obtained, i.e. a
Functional relation expression formula between e, P1, P2, P3, P4Polynomial constant coefficient in representative function expression formula；
Step 3.3：By the experimental data obtained in step 2.2, to each variables D, after A takes the logarithm, multinomial linear fit is carried out,
Obtain linear fit resultWherein, f2D () represents linear fit result, i.e. a and d's
Functional relation expression formula,Polynomial constant coefficient in representative function relational expression；
Step 3.4：Combining step 3.2 and step 3.3 fitting result are by following equation：
The expression of a=f (e, d) can be obtained：
Wherein, a0Represent brightness of image quality evaluation index A initial values take the logarithm after value, e0Represent that light-source brightness E initial values are taken the logarithm
Value afterwards, d0Represent observed range D initial values take the logarithm after value, C represents the constant entry value in a=f (e, d)；
Step 3.5：A=lnA, e=lnE, d=lnD substitutes into embodying for the a=f (e, d) that is obtained in step 3.4
A=F (E, D) expression formula is obtained in formula；
The step 4 is specifically included：
Step 4.1：If Q1,Q2,……,QnIt is the n point sequence of point that trajectory planning passes through in operating space, provides difference
Perfect light source brightness degree E corresponding with the n point1,E2,……,En, by the point sequence Q in operating space1~QnBe converted to
After joint variable in joint of mechanical arm space, according to three between adjacent given point sequence Qi joint variables corresponding with Qi+1
Secondary spline interpolation obtains the cubic polynomial function expression s that joint variable changes with time ti(t)：
si(t)=ci4t3+ci3t2+ci2t+ci1, i=1,2 ... ..., n-1
Wherein, ci4, ci3, ci2, ci1The constant coefficient of representative polynomial function expression, t is represented by adjacent given point sequence Qi
With the time interval of Qi+1；
Between the Ei and Ei+1 corresponding to adjacent given point sequence Qi and Qi+1 light-source brightness is obtained using cubic spline interpolation
The cubic polynomial function expression E that grade changes with time ti(t)：
Ei(t)=λi4t3+λi3t2+λi2t+λi1, i=1,2 ... ..., n-1
Wherein, λi4, λi3, λi2, λi1The constant coefficient of representative polynomial function expression, t is represented by adjacent given point sequence Qi
With the time interval of Qi+1；
Step 4.2：Set two object functions of the Optimized model：
Wherein, hiRepresent by adjacent given point sequence Qi and Qi+1Time interval, Δ A represents that image is bright in sampling time T
The knots modification of degree quality index A；minTExpression is minimized oeprator, and E (t+T) represents the light-source brightness value at t+T moment, D
(t+T) observed range at t+T moment is represented, E (t) represents the light-source brightness value of t, and D (t) represents the observed range of t；
Step 4.3：Give the bound for objective function：
Wherein, sup (Vcj) and sup (Acj) it is j-th kinematic constraint upper limit of joint of mechanical arm in joint space, represent respectively
The higher limit of speed, the higher limit of acceleration；AL,AHRepresent higher limit, the lower limit of brightness of image quality evaluation index；EHTable
Show the higher limit of light-source brightness grade；ζ is then the higher limit of light-source brightness change of rank amount；Represent t joint space
In j-th speed of joint of mechanical arm,Represent j-th acceleration of joint of mechanical arm, A (t) in t joint space
T brightness of image quality evaluation index is represented,Represent t light-source brightness rate of change；J is positive integer.
2. according to claim 1 based on the light-source brightness adjusting method that dark surrounds is tackled in robot kinematics,
Characterized in that, the step 1 is specifically included：
After original image is converted into HSV color spaces by RGB color space, the average gray value of luminance component image V is calculated
Used as brightness of image quality evaluation index A, computing formula is：
Wherein, the size of original image is M*N, and I (u, v) represents the distribution of the gray value in the plane of delineation of V component, and u represents figure
Lateral coordinates under image plane pixel coordinate system, v represents the longitudinal coordinate under plane of delineation coordinate system.
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