CN108908327A - A kind of robot localization error grade compensation method - Google Patents
A kind of robot localization error grade compensation method Download PDFInfo
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Abstract
The present invention discloses a kind of robot localization error grade compensation method, includes the following steps：Calculate compensation front end position and attitude error；Establish kinematics model and kinematic error model；Calculate each kinematic parameter errors optimal solution and revised kinematics model and modified kinematics model lower end pose；The compensation rate inputed to after calculation of position errors compensation；Calculating is actually reached pose, obtains the residual error after parameter calibration；Residual error estimation model is established, the compensation of expectation target point is carried out；Predict position error；The expectation target point residual error of prediction；Calculate the compensation rate inputed to；It calculates end and is actually reached pose, compensation is completed.The present invention can effectively improve the absolute fix precision of industry；Using the residual error model based on spatial simlanty, the anisotropy that position error is shown in space can be embodied.
Description
Technical field
The present invention relates to automatic Drilling/Riveting Technology fields, are a kind of robot localization error grade compensation methodes specifically.
Background technique
The development of emerging robot technology is equipped with end so that robot can be used as a kind of platform of high quality and high efficiency
The subsystems such as actuator, flexible frock, detection senses constitute a variety of different robot flexibility automated systems.In emerging skill
Under art is supported, industrial robot is gradually expanded to high-precision field direction, and job task develops to high-efficiency and precision operation.Therefore it is
Realize the higher quality of aircraft industry, the manufacture assembly technical requirement of higher efficiency, more high flexibility, the absolute of industrial robot is determined
The raising of position precision becomes technical problem urgently to be resolved.In fact, not having for repetitive positioning accuracy in 0.1mm or so
The heavy-load robot system of any accuracy compensation measure, absolute fix precision is generally in 1~2mm or so, it is clear that is not able to satisfy
The required precision of Field of Aviation Manufacturing large component automatic Drilling/Riveting, therefore robot precision's compensation technique is used, improve industrial machine
The absolute fix precision of device people is very necessary in the application of Field of Aviation Manufacturing for industrial robot.
Currently in order to realize robot high-precision control, it is primarily present two methods：Off-line calibration feed forward control method and
On-line checking feedback.Wherein feedback control technology includes joint feedback control technology and end feedback control skill again
Art.Its essence is increase space 6D sensor in robot end and utilize to swash for the end feedback control technology of the propositions such as Qu Weiwei
The control of optical tracker system closed-loop feedback, the end pose of real-time detection robot are realized the high-precision control of robot, are significantly mentioned
The absolute fix precision of the point movement of high robot.But since its method is for the poor occasion of processing opening character, laser with
The easily broken light of track appearance is not easy to implement in industry spot.Electroimpact company of the U.S. is in order to improve the positioning accurate of robot
Degree increases grating scale, whole utilization Siemens 840 D in NC development machines people control system again in each joint.But
This method Overall Reconstruction robot control system task amount is relatively complicated greatly, and this method relies primarily on the calibration of grating scale
Precision.Japan's FA NUC is in order to realize that high-precision drilling rivets, by by machine vision iRVision Integration ofTechnology to robot control
In device processed, using iRVision phase machine testing spatial pose and the movement of robot is adjusted.Above-mentioned on-line checking feedback control
All there is equipment cost valuableness, and the detection device outside height dependence in method, increase end effector or robot
The complexity in joint has higher requirement for industrial environment.Therefore most of robot precision's compensation technique research
Robot kinematics calibration aspect off-line calibration feed forward control method is all concentrated on, the calibration based on kinematics model is broadly divided into
The scaling method of method and without motion model；Specifically include following methods：
1, the working space of robot is divided into grid one by one, robot kinematics' parameter is carried out in each grid
Calibration, obtains one group of parameter error under the grid, the parameter error of grid where then choosing it according to expectation target pose
Carry out feedforward compensation.Although this method can reach preferable compensation effect, there are the robot kinematics of early period ginsengs
The big drawback of number calibration task amount.
2, each joint shaft of robot and required each geometrical characteristic are fitted using laser tracker measurement, and established accordingly
More it is bonded actual robot kinematics' model.This method is big by the influence factor of external environment, thus the pass fitted
Saving shaft, there is a certain error.
3, using radial basis function neural network (Radial Basis Function Network) to DR06 industrial machine
The geometric error of people and non-geometric error are identified, the maximum positioning error of robot is decreased to 1.8mm by 5.8mm.
The shortcomings that carrying out robot kinematics' parameter using neural network is that the optimal solution that it is acquired is often local extremum, causes to know
Other precision is lower.
4, for the node to be compensated in the grid that divides in working space, positioning corresponding to the vertex using grid is missed
Difference carries out inverse distance weighted interpolation, estimates the position error of node to be compensated.This method calculating process is simple, does not need to establish complicated
Error model may be larger using the evaluated error of this method but when the attitudes vibration of node to be compensated is larger.
Summary of the invention
The purpose of the present invention is to provide a kind of robot localization error grade compensation methodes, effectively compensate for robot
Robot inaccuracy is reduced to 0.3mm after grading compensation by residual error, significantly improves the absolute fix precision of robot.
The present invention is achieved through the following technical solutions：A kind of robot localization error grade compensation method, specifically include with
Lower step：
Step S1：The theoretical pose P of m sampled point is randomly selected in region to be compensateds, measured using laser tracker
Robot is actually reached pose Pm, obtain the end position and attitude error Δ P of robot before compensatingm=Pm-Ps；
Step S2：The movement relation between each connecting rod of robot is established, robot kinematics' model is obtained；Establish robot
Kinematic error model；
Step S3：Kinematic error model in solution procedure S2 obtains each kinematic parameter errors optimal solution and amendment
Kinematics model afterwards, and calculate the end pose P of robot under modified kinematics modelk；
Step S4：By the end pose P of robot under revised kinematics modelkPostpositive disposal is carried out, is positioned
The compensation rate P of robot is inputed to after error compensationl=2Ps-Pk；
Step S5：By compensation rate PlRobot is inputted, robot is obtained with laser tracker measurement and is actually reached pose Pln,
It is Δ P that robot, which is obtained, by the residual error after parameter calibrationr=Pln-Ps；
Step S6：By sampled point theory pose PsWith the residual error Δ P after Kinematic CalibrationrIt substitutes into and is based on space
In the residual error modeling method of similitude, residual error estimation model is established, the compensation for carrying out expectation target point is started；
Step S7：By target point theory pose PfIt brings into the revised kinematics model in step S3 and acquires prediction
Pose Pf, the robot localization error delta P that is predictedf=Pf-Pt；
Step S8：By Pt、PsWith Δ PrIt substitutes into step S6 residual error estimation model, the expectation mesh of prediction is calculated
Punctuate residual error Δ Prm；
Step S9：Expectation target point is calculated after position error and residual compensation, inputs to the compensation rate of robot
Pw=Pt-ΔPf-ΔPrm；
Step S10：By the compensation rate P in step S9wRobot is inputted, the robot end obtained by laser tracker measurement
End is actually reached pose Pwa, then expectation target point location error and residual error compensation are completed.
Further, in order to preferably realize the present invention, the step S2 is specifically referred to：It is given according to step S1 random
The attained pose that sampled point theory pose and laser tracker measurement obtain is established between each connecting rod of robot using D-H Mo Xing
Movement relation, establish robot kinematics' error model.
Further, in order to preferably realize the present invention, robot kinematics' model in the step S2 be by pair
Geometrical relationship between robot links carries out parametric description, to input the end for obtaining robot according to the joint of robot
Pose and posture.
Further, in order to preferably realize the present invention, the kinematic error model in the step S2 is in robot
On the basis of kinematics model, the error component of robot is considered, establish each joint input of robot and position with robot end
The mathematical description of relationship between error.
Further, the kinematic error mould in order to preferably realize the present invention, in the step S3 in solution procedure S2
Type；It specifically refers to：The kinematic error in interative least square method solution procedure S2 is damped by Levenberg-Marquardt
Model.
Further, in order to preferably realize the present invention, the Levenberg-Marquardt damping in the step S3 changes
It is a kind of Identification of parameter of fast convergence rate for least square method, adaptive resistance is introduced on the basis of least-squares algorithm
Buddhist nun's coefficient avoids matrix from singularity occur.
Further, it in order to preferably realize the present invention, is adopted according to the residual error estimation model in the step S6
The theoretical pose and residual error of sampling point establish the residual error mapping based on spatial simlanty, for estimating expectation target
The residual error of point.
Compared with prior art, the present invention having the following advantages that and beneficial effect：
(1) present invention can effectively improve the absolute fix precision of industrial robot；
(2) of the invention by research grading compensation controlling mechanism, it realizes based on coupling parameter identification and spatial simlanty
Robot is classified error compensation, the residual error of robot can be effectively compensated for after use, by robot after grading compensation
Error is reduced to 0.3mm, significantly improves the absolute fix precision of robot；
(3) present invention employs modified Levenberg-Marquardt to damp interative least square method, can acquire mesh
The global convergence solution of scalar functions, parameter error estimation is more correct, to improve the precision of robot kinematics' parameter calibration；
(4) present invention employs the residual error model based on spatial simlanty, the calculating of best initial weights is sat in Descartes
Marking has different calculated result on the different directions of system, can embody that robot localization error shows in space it is each to
The opposite sex, and best initial weights depend on the pose and posture of node to be compensated and sampled point.
Detailed description of the invention
Fig. 1 is that robot of the present invention completes position error grading compensation control strategy figure.
Specific embodiment
The present invention is described in further detail below with reference to embodiment, embodiments of the present invention are not limited thereto.
Embodiment 1：
The present invention is achieved through the following technical solutions, as shown in Figure 1, a kind of robot localization error grade compensation method,
Specifically include following steps：
Step S1：The theoretical pose P of m sampled point is randomly selected in region to be compensateds, measured using laser tracker
Robot is actually reached pose Pm, obtain the end position and attitude error Δ P of robot before compensatingm=Pm-Ps；
Step S2：The movement relation between each connecting rod of robot is established, robot kinematics' model is obtained；Establish robot
Kinematic error model；
Step S3：Kinematic error model in solution procedure S2 obtains each kinematic parameter errors optimal solution and amendment
Kinematics model afterwards, and calculate the end pose P of robot under modified kinematics modelk；
Step S4：By the end pose P of robot under revised kinematics modelkPostpositive disposal is carried out, is positioned
The compensation rate P of robot is inputed to after error compensationl=2Ps-Pk；
Step S5：By compensation rate PlRobot is inputted, robot is obtained with laser tracker measurement and is actually reached pose Pln,
It is Δ P that robot, which is obtained, by the residual error after parameter calibrationr=Pln-Ps；
Step S6：By sampled point theory pose PsWith the residual error Δ P after Kinematic CalibrationrIt substitutes into and is based on space
In the residual error modeling method of similitude, residual error estimation model is established, the compensation for carrying out expectation target point is started；
Step S7：By target point theory pose PtIt brings into the revised kinematics model in step S3 and acquires prediction
Pose Pf, the robot localization error delta P that is predictedf=Pf-Pt；
Step S8：By Pt、PsWith Δ PrIt substitutes into step S6 residual error estimation model, the expectation mesh of prediction is calculated
Punctuate residual error Δ Prm；
Step S9：Expectation target point is calculated after position error and residual compensation, inputs to the compensation rate P of robotw
=Pt-ΔPf-ΔPrm；
Step S10：By the compensation rate P in step S9wRobot is inputted, the robot end obtained by laser tracker measurement
End is actually reached pose Pwa, then expectation target point location error and residual error compensation are completed.
It should be noted that the residual error of robot can be effectively compensated for after use by above-mentioned improvement, by classification
Robot inaccuracy is reduced to 0.3mm after compensation, significantly improves the absolute fix precision of robot.
Interative least square method is damped using Levenberg-Marquardt, the global convergence of objective function can be acquired
Solution, parameter error estimation is more correct, to improve the precision of robot kinematics' parameter calibration.
Using the residual error model based on spatial simlanty, the not Tongfang of the calculating of best initial weights in cartesian coordinate system
There is different calculated result upwards, the anisotropy that robot localization error is shown in space can be embodied.And most
Excellent weight depends on position and the posture of node to be compensated and sampled point.
The other parts of the present embodiment are same as the previously described embodiments, and so it will not be repeated.
Embodiment 2：
A kind of robot localization error grade compensation method, the analysis robot position error regularity of distribution and error source are made
With mechanism, the major influence factors of position error are divided into two class of geometric parameter error and non-geometric parameter error.For geometry
Parameter error factor proposes a kind of coupling parameter for comprehensively considering robot base establishment of coordinate system error and geometric parameter error
Error model.For non-geometric parameter error factor, a kind of residual error model based on spatial simlanty is proposed.Pass through research
Grading compensation controlling mechanism realizes that the robot based on coupling parameter identification and spatial simlanty is classified error compensation, further
Improve the absolute fix precision of robot.
Specifically include following steps：
Step S1：The theoretical pose P of m sampled point is randomly selected in region to be compensateds, measured using laser tracker
Robot is actually reached pose Pm, obtain the end position and attitude error Δ P of robot before compensatingm=Pm-Ps；
Step S2：The movement relation between each connecting rod of robot is established using D-H Mo Xing, obtains robot kinematics' mould
Type；It specifically refers to：The stochastical sampling point theory pose P given according to step S1sThe actual bit obtained with laser tracker measurement
Appearance Pm, establish robot kinematics' error model；
Robot kinematics' model is by carrying out parametric description to the geometrical relationship between robot links, with basis
The joint input of robot obtains the end pose and posture of robot；
Kinematic error model is to consider the error component of robot on the basis of robot kinematics' model, is established
The mathematical description of relationship between each joint input of robot and robot end's position error；
Step S3：The kinematics in interative least square method solution procedure S2 is damped by Levenberg-Marquardt
Error model obtains each kinematic parameter errors optimal solution and revised kinematics model, and calculates modified kinematics mould
The end pose P of Xing Xia robotk；It is a kind of fast convergence rate that Levenberg-Marquardt, which damps interative least square method,
Identification of parameter, on the basis of least-squares algorithm introduce self-adaptive damping coefficient avoid matrix from singularity occur；
Step S4：By the end pose P of robot under revised kinematics modelkPostpositive disposal is carried out, is positioned
The compensation rate P of robot is inputed to after error compensationl=2Ps-Pk；
Step S5：By compensation rate PlRobot is inputted, robot is obtained with laser tracker measurement and is actually reached pose Pln,
It is Δ P that robot, which is obtained, by the residual error after parameter calibrationr=Pln-Ps；
Step S6：By sampled point theory pose PsWith the residual error Δ P after Kinematic CalibrationrIt substitutes into and is based on space
In the residual error modeling method of similitude, residual error estimation model is established, the compensation for carrying out expectation target point is started；
Residual error estimates that model is the theoretical pose and residual error according to sampled point, establishes based on spatial simlanty
Residual error mapping, for estimating the residual error of expectation target point；
Step S7：By target point theory pose PtIt brings into the revised kinematics model in step S3 and acquires prediction
Pose Pf, the robot localization error delta P that is predictedf=Pf-Pt；
Step S8：By Pt、PsWith Δ PγIt substitutes into step S6 residual error estimation model, the expectation mesh of prediction is calculated
Punctuate residual error Δ Prm；
Step S9：Expectation target point is calculated after position error and residual compensation, inputs to the compensation rate of robot
Pw=Pt-ΔPf-ΔPrm；
Step S10：By the compensation rate P in step S9wRobot is inputted, the robot end obtained by laser tracker measurement
End is actually reached pose Pwa, then expectation target point location error and residual error compensation are completed.
Embodiment 3：
As shown in Figure 1, a kind of robot localization error grade compensation method, specifically includes following steps：
Step S1：The theoretical pose P of m sampled point is randomly selected in region to be compensateds, with laser tracker measuring machine
Device people is actually reached pose Pm, obtain the end position and attitude error Δ P of robot before compensatingm=Pm-Ps。
Step S2：The movement relation between each connecting rod of robot is established using D-H Mo Xing, obtains robot kinematics' mould
Type；The stochastical sampling point theory pose P given according to step S1sThe attained pose P obtained with laser tracker measurementm, establish machine
Device people's kinematic error model, model foundation are as follows：
The movement relation between each connecting rod of robot is established using D-H Mo Xing, in order to avoid mutually flat between adjacent two axis
It is capable or close to it is parallel when the singular problem that generates, movement relation increase on the basis of theoretical D-H Mo Xing, between adjacent links
One corner β around coordinate system y-axis becomes the connecting rod transformation for mula of robot：
In formula：sθi=sin θi；cθi=cos θi；sαi=sin αi；cαi=cos αi；sβi=sin βi；cβi=cos βi。
Robot concatenated for N number of joint, by the available Robot kinematics equations of the transformation of adjacent links, machine
People end module and carriage transformation matrix0TnFor：
The stochastical sampling point theory pose P given according to step S1sWith the end position and attitude error Δ P for compensating preceding robotm,
Since there are error, robot end's position and attitude error and each link parameters to miss for each parameter in kinematics model established above
Linear transformation relationship between difference is：
If measuring the position error of m group robot, can obtain：
Then for m sampled point, robot kinematics' error model is：ΔPm=Jm·ΔX
Step S3：The kinematics in interative least square method solution procedure S2 is damped by Levenberg-Marquardt
Error model obtains each kinematic parameter errors optimal solution and revised kinematics model, and calculates modified kinematics mould
The end pose P of Xing Xia robotk.It is as follows that Levenberg-Marquardt damps interative least square method iterative process：
(1) the robot Jacobian matrix J (X of kth time iteration is calculatedk)。
(2) the kinematic parameter errors change value Δ X of kth time iteration is solvedk, i.e.,：
ΔXk=-[JT(Xk)J(Xk)+μkI]-1JT(Xk)ΔP(Xk)
In formula：I is unit matrix；XkKinematic parameter errors when iteration secondary for kth；μkFor kth time iteration damping because
Son；ΔP(Xk) be kth time iteration position and attitude error.
(3) kinematic parameter errors X when+1 iteration of kth is updatedk+1It is with the number of iterations k：
Xk+1=Xk+ΔXk
K=k+1
(4) damped coefficient μ when+1 iteration of kth is updatedk+1For：
(5) as ‖ Δ P (Xk+1)‖-‖ΔP(Xk) ‖≤ε when, generally take ε=0.0001, the pose of iteration twice adjacent at this time
The difference of two norm of error levels off to zero, it was demonstrated that has restrained.
Step S4：By the end pose P of robot under revised kinematics modelkPostpositive disposal is carried out, is positioned
The compensation rate P of robot is inputed to after error compensationl=2Ps-Pk。
Step S5：By compensation rate PlRobot is inputted, robot is obtained with laser tracker measurement and is actually reached pose Pln,
It is Δ P that robot, which is obtained, by the residual error after parameter calibrationr=Pln-Ps。
Step S6：By sampled point theory pose PsWith the residual error Δ P after Kinematic CalibrationrIt substitutes into and is based on space
In the residual error modeling method of similitude, residual error estimation model is established.Model foundation process is as follows：
An error map function is constructed, to describe the relationship of end residual error and joint rotation angle, and establishes sampling
Correlation matrix between point and sampled point.According to target point and sampled point correlation matrix quantitative description, using gram in gold it is poor
The method of value estimates the residual error of target point.
The error at space any point is divided into ascertainment error and random error, and error map function is described as：
el(θ)=ρ (βl, θ) and+gl(θ) l=x, y, z
Wherein, θ=[θ1, θ2…θn]TFor the joint rotation angle value at n degree of freedom robot space any point；L is that work is empty
Between coordinate direction, by the residual error in the direction x modeling for discuss.
ρ (β, θ) is the linear segment of error map function, and form is as follows：
ρ (β, θ), β1+β2θ1+…+βn+lθn
=[1 θ1 … θn]β
=f (θ)Tβ
G (θ) indicates the random partial of error map function, and satisfaction is desired for 0, and any two groups of joint rotation angles input g (θ
)(i)With g (θ)(j)Corresponding covariance is：
Cov(g(θ)(i), g (θ)(j))=σ2S (ξ, θ(i), θ(j))
σ in formula2Variance for sampled point in the direction x, S (ξ, θi, θj) it is correlation models using ξ as parameter：
ξ in formulak∈ ξ is the identification factor of k-th of joint rotation angle, is acquired by Maximum-likelihood estimation：
In formulaFor correlation matrix, RI, j=S (ξ, θ(i), θ(j)〕。
Step S7：The compensation for starting progress expectation target point, by target point theory pose PtBring the amendment in step S3 into
The pose P of prediction is acquired in kinematics model afterwardsf, the robot localization error delta P that is predictedf=Pf-Pt。
Step S8：By Pt、PsWith Δ PrIt substitutes into step S6 residual error estimation model, the expectation mesh of prediction is calculated
Punctuate residual error Δ Prm, residual error estimation method is as follows：
By gram in golden difference it is found that any one target point can be expressed as in x, the evaluated error of y, the direction z in space：
In formula：w∈RmFor the weighted vector of target point and sampled point；e∈RmFor the error vector in sampled point direction.
Building matrix F describes sampled point joint input F=[f (θ(1))…f(θ(m))]T, construct correlation vector r ∈ RmIt retouches
State correlation of the target point with sampled point, r (θ)=[S (ξ, θ(1), θ) ... S (ξ, θ(m), θ)]T。
The method utilized find out weight w should be ensured that the estimated value of target point and the difference of actual value be it is unbiased, i.e.,：
In formula：G=[g (θ(1))…g(θ(m))]T。
Guarantee above formula be it is unbiased, then need to make FTW=f (θ), weight is optimal in order to guarantee to acquire, and need to make the side of following formula
It is poor minimum, then：
The problem of above problem can be converted into conditional extremum is solved, can be solved by lagrange's method of multipliers, i.e.,：
L (w, λ)=δ2(1+wTRw-2wTr)-λT(FTw-f(θ))
Wherein λ is Lagrange multiplier；
Enable L 'w=0：L′w(w, λ)=2 δ2(Rw-r) λ=0-F；
Optimal w can be solved by solving above-mentioned formula, bring formula intoThe evaluated error of target point can be found out.
Step S9：Expectation target point is calculated after position error and residual compensation, inputs to the compensation rate P of robotw
=Pt-ΔPf-ΔPrm
Step S10：By the compensation rate P in step S9wRobot is inputted, the robot end obtained by laser tracker measurement
End is actually reached pose Pwa, then expectation target point location error and residual error compensation are completed.
It should be noted that by above-mentioned improvement,
The other parts of the present embodiment are same as the previously described embodiments, and so it will not be repeated.
The above is only presently preferred embodiments of the present invention, not does limitation in any form to the present invention, it is all according to
According to technical spirit any simple modification to the above embodiments of the invention, equivalent variations, protection of the invention is each fallen within
Within the scope of.
Claims (7)
1. a kind of robot localization error grade compensation method, it is characterised in that：Specifically include following steps：
Step S1：The theoretical pose P of m sampled point is randomly selected in region to be compensateds, machine is measured using laser tracker
People is actually reached pose Pm, obtain the end position and attitude error Δ P of robot before compensatingm=Pm-Ps；
Step S2：The movement relation between each connecting rod of robot is established, robot kinematics' model is obtained；Establish robot motion
Learn error model；
Step S3：Kinematic error model in solution procedure S2 obtains each kinematic parameter errors optimal solution and revised
Kinematics model, and calculate the end pose P of robot under modified kinematics modelk；
Step S4：By the end pose P of robot under revised kinematics modelkPostpositive disposal is carried out, position error benefit is obtained
The compensation rate P of robot is inputed to after repayingl=2Ps-Pk；
Step S5：By compensation rate PlRobot is inputted, robot is obtained with laser tracker measurement and is actually reached pose Pln, obtain
Robot is Δ P by the residual error after parameter calibrationr=Pln-Ps；
Step S6：By sampled point theory pose PsWith the residual error Δ P after Kinematic CalibrationrIt substitutes into similar based on space
Property residual error modeling method in, establish residual error estimation model, start carry out expectation target point compensation；
Step S7：By target point theory pose PtIt brings into the revised kinematics model in step S3 and acquires the pose of prediction
Pf, the robot localization error delta P that is predictedf=Pf-Pt；
Step S8：By Pt、PsWith Δ PrIt substitutes into step S6 residual error estimation model, the expectation target point of prediction is calculated
Residual error Δ Prm；
Step S9：Expectation target point is calculated after position error and residual compensation, inputs to the compensation rate P of robotw=Pt-
ΔPf-ΔPrm；
Step S10：By the compensation rate P in step S9wRobot is inputted, the robot end obtained by laser tracker measurement is real
Border reaches pose Pwa, then expectation target point location error and residual error compensation are completed.
2. a kind of robot localization error grade compensation method according to claim 1, it is characterised in that：The step S2
It specifically refers to：According to the attained pose that the given stochastical sampling point theory pose of step S1 and laser tracker measurement obtain, make
The movement relation between each connecting rod of robot is established with D-H Mo Xing, establishes robot kinematics' error model.
3. a kind of robot localization error grade compensation method according to claim 2, it is characterised in that：The step S2
In robot kinematics' model be by between robot links geometrical relationship carry out parametric description, according to machine
The joint input of people obtains the end pose and posture of robot.
4. a kind of robot localization error grade compensation method according to claim 2, it is characterised in that：The step S2
In kinematic error model be on the basis of robot kinematics' model, consider the error component of robot, establish machine
The mathematical description of relationship between each joint input of people and robot end's position error.
5. a kind of robot localization error grade compensation method according to claim 1-4, it is characterised in that：Institute
State kinematic error model in step S3 in solution procedure S2, in particular to：It is changed by Levenberg-Marquardt damping
For the kinematic error model in least square method solution procedure S2.
6. a kind of robot localization error grade compensation method according to claim 5, it is characterised in that：The step S3
In Levenberg-Marquardt damping interative least square method be a kind of fast convergence rate Identification of parameter, most
Self-adaptive damping coefficient is introduced on the basis of small two multiplication algorithm avoids matrix from singularity occur.
7. a kind of robot localization error grade compensation method according to claim 6, it is characterised in that：The step S6
In residual error estimation model be that the remnants based on spatial simlanty are established according to the theoretical pose and residual error of sampled point
Error map, for estimating the residual error of expectation target point.
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Cited By (18)
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| CN109924984A (en) * | 2019-03-22 | 2019-06-25 | 上海电气集团股份有限公司 | It is intended to the motion planning and robot control method and system of detection based on human motion |
| CN109924984B (en) * | 2019-03-22 | 2022-01-21 | 上海电气集团股份有限公司 | Robot motion control method and system based on human motion intention detection |
| CN110161850A (en) * | 2019-04-24 | 2019-08-23 | 南京航空航天大学 | A kind of identification of industrial robot variable element rigidity and modeling method |
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| CN110161850B (en) * | 2019-04-24 | 2020-04-07 | 南京航空航天大学 | Variable parameter rigidity identification and modeling method for industrial robot |
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| CN111055273A (en) * | 2019-05-16 | 2020-04-24 | 广西大学 | Two-step error compensation method for robot |
| CN110385720A (en) * | 2019-07-26 | 2019-10-29 | 南京航空航天大学 | A kind of robot localization error compensating method based on deep neural network |
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| CN110967042A (en) * | 2019-12-23 | 2020-04-07 | 襄阳华中科技大学先进制造工程研究院 | Industrial robot positioning precision calibration method, device and system |
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| CN111650881A (en) * | 2020-05-12 | 2020-09-11 | 武汉理工大学 | Method, system and storage medium for predicting and compensating positioning error of numerical control machine |
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| CN114131607B (en) * | 2021-12-08 | 2022-07-12 | 北京工业大学 | Kinematic calibration method and system for generalized kinematic errors of industrial robot |
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| CN114161425A (en) * | 2021-12-28 | 2022-03-11 | 中国人民解放军战略支援部队信息工程大学 | Error compensation method of industrial robot |
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| CN114474004A (en) * | 2022-03-18 | 2022-05-13 | 河北工业大学 | Multi-factor coupling vehicle-mounted construction robot error compensation planning control strategy |
| CN114474004B (en) * | 2022-03-18 | 2023-10-03 | 河北工业大学 | Error compensation planning control strategy for multi-factor coupling vehicle-mounted building robot |
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