CN109093600A - Round steel end face labels series parallel robot in five degrees of freedom Dimension Synthesis method - Google Patents
Round steel end face labels series parallel robot in five degrees of freedom Dimension Synthesis method Download PDFInfo
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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
- B25J9/003—Programme-controlled manipulators having parallel kinematics
- B25J9/0072—Programme-controlled manipulators having parallel kinematics of the hybrid type, i.e. having different kinematics chains
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Abstract
Round steel end face labels series parallel robot in five degrees of freedom Dimension Synthesis method, comprises the following steps: determining Optimal Parameters according to mechanism configuration and establish superior vector;By series-parallel robot integrally depending on doing serial mechanism, Jacobian matrix is solved using differential method of changing, parallel institution is considered as a series connection joint, solves its Jacobian matrix using differential transform method, and it is taken to the respective column of hybrid mechanism Jacobian matrix, establish hybrid mechanism Jacobian matrix;Establish hybrid mechanism universe kinematics performance indicator;Establish hybrid mechanism universe rigidity property index;Set up mechanism universe transmission performance index;Using kinematics, rigidity and transmission performance index as optimization object function, and it is using Monte Carlo method that the mechanism position parameter in objective function is unified;Using the forward position pareto method, objective function optimal value is found using the non-dominated sorted genetic algorithm with elite retention strategy, optimum size is obtained, efficiently solves the problems, such as hybrid mechanism Dimension Synthesis.
Description
Technical field
The present invention relates to a kind of round steel end faces to label series parallel robot in five degrees of freedom Dimension Synthesis method, belongs to mixed connection machine
People's technical field.
Background technique
Hybrid mechanism has both the advantages of serial mechanism and parallel institution, leads in aerospace, Medical Devices, industrial production etc.
There is wide application space in domain.Dimension Synthesis is the important content of series-parallel robot design, the mechanism performance of series-parallel robot
Difference is huge under different scales, and good scale parameter can play the performance advantage of hybrid mechanism, therefore to mixed connection machine
It is significant that structure carries out Dimension Synthesis.The common method of Dimension Synthesis has performance Atlas Method and target function method: performance map spectrometry
Principle is to reduce the number of parameter, gives expression to the relationship between performance indicator and parameter, graphically by performance indicator, simple straight
It sees but is difficult to take into account other indexs such as operability of mechanism;Target function method is to establish mesh according to mechanism itself and job requirement
Scalar functions find optimal result using optimization algorithm.
There are a large amount of Dimension Synthesis correlative studys for serial mechanism or parallel institution at present, and for hybrid mechanism scale
Comprehensive study is extremely limited, and is that hybrid mechanism is decomposed into serial mechanism and parallel institution, carries out Dimension Synthesis respectively, such as specially
Sharp CN201710616947.9 is the Dimension Synthesis that the parallel institution in hybrid mechanism carries out, and hybrid mechanism is having both series connection
While mechanism and parallel institution advantage, inevitably includes the Research Challenges of the two, essentially consist in using target function method
The Jacobian matrix of mechanism will be related to by carrying out Dimension Synthesis, and hybrid mechanism Jacobian matrix correlative study is seldom, and Jacobi
Matrix includes hybrid mechanism terminal position information and parallel institution terminal position information, in parallel since serial mechanism instead solves difficulty
The reason of mechanism normal solution difficulty, objective function is difficult to establish by unified parameter, therefore integrally carries out scale to series-parallel robot
It is comprehensive to there is very big difficulty.
Summary of the invention
The round steel end face labeling series parallel robot in five degrees of freedom mechanism that the method for the present invention is directed to is by three translation parallel mechanism string
Two degrees of freedom rotation serial mechanism is connect to constitute.Parallel institution is by the 3 of silent flatform, moving platform and connection silent flatform and moving platform
RRP4RThe closing means that R branch is constituted, 3 RRP4RR branch is by revolute pair R, revolute pair R, parallelogram mechanism
P4RIt is concatenated with revolute pair R, three branches are circumferentially uniformly distributed along silent flatform.Two cradle heads of serial mechanism are sequentially connected in series
On parallel institution moving platform, and two joint axial space is vertical.
The invention proposes a kind of hybrid mechanism Dimension Synthesis methods, with series-parallel robot kinematics performance, rigidity property
It is lost using the forward position pareto method using the non-dominated ranking with elite retention strategy with transmission performance as optimization object function
Propagation algorithm (NSGA-II) finds objective function optimal value.
By hybrid mechanism integrally depending on doing serial mechanism, wherein parallel institution is considered as a series connection joint, using differential transform
Method solves the Jacobian matrix of parallel institution and wherein one arranges accordingly as hybrid mechanism Jacobian matrix, serial mechanism
Jacobian matrix equally use differential transform method to acquire, obtain the Jacobian matrix of hybrid mechanism entirety, and then obtain target
Function.Parameter in this objective function is not unified, and the terminal position information of parallel institution in this objective function is retained, by mixed connection machine
Structure terminal position information is indicated by position under different joint variables of parallel institution terminal position information and serial mechanism.
The joint variable of serial mechanism is obtained by Monte Carlo method, and then obtains the objective function of hybrid mechanism Dimension Synthesis, to mixed
Online structure integrally carries out Dimension Synthesis, to solve the above problem existing for background technique.
Round steel end face labels series parallel robot in five degrees of freedom Dimension Synthesis method, comprises the following steps:
Step 1 establishes the geometric parameter i.e. optimization aim for needing to optimize, including parallel institution master arml 1, parallel institution is driven
Arml 2, parallel institution sound platform semidiametere, mechanical arm of connectingl 3, mechanical arm of connectingl 4, i.e., optimization problem be find one to
AmountP:P=[l 1 l 2 el 3 l 4]T;
Step 2 establishes hybrid mechanism Jacobian matrixJ, by series-parallel robot integrally depending on doing serial mechanism, wherein parallel institution is regarded
For a series connection joint, the Jacobian matrix of parallel institution is solved using differential transform method and by the Jacobian matrix of parallel institution
As the corresponding column of hybrid mechanism Jacobian matrix, the Jacobian matrix of serial mechanism equally uses differential transform method to acquire,
And then obtain the Jacobian matrix of hybrid mechanism entirety;
Step 3, set up mechanism universe kinematics performance index functionη J , weighed with the conditional number of series-parallel robot Jacobian matrix
The kinematics performance of measuring mechanism, when conditional number is infinitely great, mechanism is singular configuration, and conditional number is smaller, kinematics of mechanism
Can be optimal, therefore optimization aim isη J →min;
Step 4, set up mechanism universe rigidity property target functionη G , with the rigidity property of stiffness matrix outgoing mechanism, by rigidity
The minimum singular value of matrix is as its conditional number, therefore optimization aim isη G →min;
Step 5, set up mechanism universe transmission performance target functionη S , gearing using the inverse of global conditioning index as adjudication organization
The inverse of the index of energy, conditional number is bigger, and the transmission performance of mechanism is better, therefore using the negative of global conditioning index inverse as universe
Transmission performance target function, optimization aim areη S →min;
Step 6, withη J ,η G ,η S As optimization object function, parallel institution terminal position information withx,y,zIt indicates, cascade machine
The joint variable of structure is obtained by Monte Carlo method;
Step 7 finds objective function minimum value: min using the forward position pareto method and optimization algorithmF(P)=min(η J ,η G ,η S )T,
And obtain corresponding design variable.
The beneficial effects of the present invention are:
The present invention has carried out Dimension Synthesis to round steel end face labeling series parallel robot in five degrees of freedom, by integrally regarding hybrid mechanism
Make serial mechanism, the method that parallel institution is regarded as one of series connection joint has obtained the Jacobian matrix of hybrid mechanism, according to
Hybrid mechanism Jacobian matrix obtains the optimization object function of Dimension Synthesis, is instead solved by parallel institution and Monte Carlo method obtains
Series connection joint variable carry out the parameter in unified target function, using the forward position pareto method, NSGA-II is utilized to find multiple target letter
Several optimal values.This method efficiently solves the problems, such as hybrid mechanism Dimension Synthesis.
Detailed description of the invention
Attached drawing 1 is the schematic diagram of mechanism of the series-parallel robot of the method for the present invention;
Attached drawing 2 is the coordinate system of the series-parallel robot of the method for the present invention;
Attached drawing 3 is the parallel institution pedestal of the series-parallel robot of the method for the present invention.
Specific embodiment
Illustrate round steel end face labeling series parallel robot in five degrees of freedom mechanism of the present invention and Dimension Synthesis side in conjunction with attached drawing 1-3
Method.
The round steel end face labeling series parallel robot in five degrees of freedom mechanism that the method for the present invention is directed to is by three translation parallel mechanism string
Two degrees of freedom rotation serial mechanism is connect to constitute.Parallel institution is by the 3 of silent flatform, moving platform and connection silent flatform and moving platform
RRP4RThe closing means that R branch is constituted, 3 RRP4RR branch is by revolute pair R, revolute pair R, parallelogram mechanism
P4RIt is concatenated with revolute pair R, three branches are circumferentially uniformly distributed along silent flatform.Two cradle heads of serial mechanism are sequentially connected in series
On parallel institution moving platform, and two joint axial space is vertical.
Round steel end face labels series parallel robot in five degrees of freedom Dimension Synthesis method, comprises the following steps:
Step 1 establishes the geometric parameter i.e. optimization aim for needing to optimize, including parallel institution master arml 1, parallel institution is driven
Arml 2, parallel institution sound platform semidiametere, mechanical arm of connectingl 3, mechanical arm of connectingl 4, i.e., optimization problem be find one to
AmountP:P=[l 1 l 2 el 3 l 4]T;
Step 2 establishes hybrid mechanism Jacobian matrixJ, by series-parallel robot integrally depending on doing serial mechanism, wherein parallel institution is regarded
For a series connection joint, the Jacobian matrix of parallel institution is solved using differential transform method and as hybrid mechanism Jacobi
Matrix wherein one arranges accordingly, and the Jacobian matrix of serial mechanism equally uses differential transform method to acquire, and then obtains mixed connection machine
The Jacobian matrix of structure entirety;
Step 3, set up mechanism universe kinematics performance index functionη J , weighed with the conditional number of series-parallel robot Jacobian matrix
The kinematics performance of measuring mechanism, when conditional number is infinitely great, mechanism is singular configuration, and conditional number is smaller, kinematics of mechanism
Can be optimal, therefore optimization aim isη J →min;
Step 4, set up mechanism universe rigidity property target functionη G , with the rigidity property of stiffness matrix outgoing mechanism, by rigidity
The minimum singular value of matrix is as its conditional number, therefore optimization aim isη G →min;
Step 5, set up mechanism universe transmission performance target functionη S , gearing using the inverse of global conditioning index as adjudication organization
The inverse of the index of energy, conditional number is bigger, and the transmission performance of mechanism is better, therefore using the negative of global conditioning index inverse as universe
Transmission performance target function, optimization aim areη S →min;
Step 6, withη J ,η G ,η S As optimization object function, wherein parallel institution terminal position information withx,y,zIt indicates,
The joint variable of middle serial mechanism is obtained by Monte Carlo method;
Step 7 uses the forward position pareto method by Matlab, utilizes the non-dominated sorted genetic algorithm with elite retention strategy
(NSGA-II) objective function minimum value: min is foundF(P)=min(η J ,η G ,η S )T, and obtain corresponding design variable.
It is as follows that this implementation round steel end face labels the step of series parallel robot in five degrees of freedom Dimension Synthesis:
Step 1 establishes the geometric parameter i.e. optimization aim for needing to optimize, including parallel institution master arml 1, parallel institution is driven
Arml 2, parallel institution sound platform semidiametere, mechanical arm of connectingl 3, mechanical arm of connectingl 4, i.e., optimization problem be find one to
AmountP:P=[l 1 l 2 el 3 l 4]T;
Step 2 establishes hybrid mechanism Jacobian matrixJ, with reference to the accompanying drawings 2 and attached drawing 3 known toB i WithC i Position in a coordinate system
Vector can indicate are as follows:
In formula,φ i For parallel institution master arm branch and silent flatform coordinate systemXThe angle of axis,θ i For master arm subtended angle.
Pass through geometrical relationship, single branch constraint equation of parallel institution can be obtained:
Parallel institution Jacobian matrix are as follows:
Wherein,,, obtain, will
Obtained parallel institution Jacobian matrix substitutes into preceding 3 column of hybrid mechanism Jacobian matrix.
According to hybrid mechanism kinematics model figure, the homogeneous transform matrix of hybrid mechanism is established0 T i , joined according to the D-H of mechanism
Several and mechanism transformation matrix of coordinatesAGeneral expression obtain homogeneous transform matrix of each joint relative to basis coordinates:
Serial mechanism Jacobian matrix is solved, for cradle headi, have:
Obtain hybrid mechanism Jacobian matrix are as follows:
In formula, c2Indicate cosθ 2, s2Indicate sinθ 2,θ 2For mechanical arm of connectingl 3Corner, c3Indicate cosθ 3, s3Indicate sinθ 3,θ 3For mechanical arm of connectingl 4Corner.
Step 3, set up mechanism universe kinematics performance index functionη J , with the conditional number of series-parallel robot Jacobian matrixK J Measure the kinematics performance of mechanism, when conditional number is infinitely great, mechanism is singular configuration, and conditional number is smaller, mechanism fortune
It is dynamic to learn best performance,K J It is defined by the maximum singular value of Jacobian matrix and the ratio of minimum singular value:
WhereinIt isJ2 norms, matrix norm be mathematically it is of equal value, using this black norm of the not Luo Beini of matrix,
That is:
Kinematics performance indicator is variation in space, so should be in robot working spaceWIt is middle to use universe kinematics
Performance indicator, expression formula are as follows:
;
Step 4, set up mechanism universe rigidity property target functionη G , with the rigidity property of stiffness matrix outgoing mechanism, mechanism
Stiffness matrix are as follows:
G=kJ T J
Wherein,kFor stiffness coefficient, takek=1, matrix (J T J) characteristic value maximum value correspond to mechanism maximum rigidity, optimization aim is
Obtain maximum rigidity, it may be assumed that
Wherein,, whereinIt isG2 norms, matrix norm be mathematically it is of equal value, using matrix
Not this black norm of Luo Beini, it may be assumed that
Rigidity property index is variation in space, so should be in robot working spaceWIt is middle to use universe rigidity property
Index, expression formula are as follows:
;
Step 5, set up mechanism universe transmission performance target functionη S , gearing using the inverse of global conditioning index as adjudication organization
The inverse of the index of energy, conditional number is bigger, and the transmission performance of mechanism is better, therefore using the negative of global conditioning index inverse as universe
Transmission performance target function, it may be assumed that
Wherein,
,
Step 6, withη J ,η G ,η S As optimization object function, wherein parallel institution terminal position information withx,y,zIt indicates,
The joint variable of middle serial mechanism is obtained by Monte Carlo method;
Step 7, using Matlab programming tool, using the forward position pareto method and the non-dominated ranking with elite retention strategy is hereditary
Algorithm (NSGA-II) finds objective function minimum value, and the value area of each design variable is limited according to practical labeling application scenarios
Between, obtain mathematical model are as follows:
The optimized scale parameter that round steel end face labeling series parallel robot in five degrees of freedom is calculated are as follows:
P=[232.2749 577.6572 76.9924 76.8491 68.3872]T。
Claims (2)
1. round steel end face labels series parallel robot in five degrees of freedom Dimension Synthesis method, the series parallel robot in five degrees of freedom that method is directed to
Mechanism by three translation parallel mechanism concatenation two degrees of freedom rotation serial mechanism constitute, parallel institution be by silent flatform, moving platform with
And 3 RRP of connection silent flatform and moving platform4RThe closing means that R branch is constituted, 3 RRP4RR branch is by revolute pair
R, revolute pair R, parallelogram mechanism P4RIt is concatenated with revolute pair R, three branches are circumferentially uniformly distributed along silent flatform, serial mechanism
Two cradle heads be sequentially connected in series on parallel institution moving platform, and two joint axial space is vertical, it is characterised in that uses
Following method carries out Dimension Synthesis, the specific steps are as follows:
Step 1 establishes the geometric parameter i.e. optimization aim for needing to optimize, including parallel institution master arml 1, parallel institution slave arml 2, parallel institution sound platform semidiametere, mechanical arm of connectingl 3, mechanical arm of connectingl 4, i.e. optimization problem is to find a vectorP:P=[l 1 l 2 el 3 l 4]T;
Step 2 establishes hybrid mechanism Jacobian matrixJ, by series-parallel robot integrally depending on doing serial mechanism, wherein parallel institution is regarded
For a series connection joint, the Jacobian matrix of parallel institution is solved using differential transform method and by the Jacobian matrix of parallel institution
As the corresponding column of hybrid mechanism Jacobian matrix, the Jacobian matrix of serial mechanism equally uses differential transform method to acquire,
And then obtain the Jacobian matrix of hybrid mechanism entirety;
Step 3, set up mechanism universe kinematics performance index functionη J , weighed with the conditional number of series-parallel robot Jacobian matrix
The kinematics performance of measuring mechanism, when conditional number is infinitely great, mechanism is singular configuration, and conditional number is smaller, kinematics of mechanism
Can be optimal, therefore optimization aim isη J →min;
Step 4, set up mechanism universe rigidity property target functionη G , with the rigidity property of stiffness matrix outgoing mechanism, by rigidity square
The minimum singular value of battle array is as its conditional number, therefore optimization aim isη G →min;
Step 5, set up mechanism universe transmission performance target functionη S , gearing using the inverse of global conditioning index as adjudication organization
The inverse of the index of energy, conditional number is bigger, and the transmission performance of mechanism is better, therefore using the negative of global conditioning index inverse as universe
Transmission performance target function, optimization aim areη S →min;
Step 6, withη J ,η G ,η S As optimization object function, parallel institution terminal position information withx,y,zIt indicates, cascade machine
The joint variable of structure is obtained by Monte Carlo method;
Step 7 finds objective function minimum value: min using optimization algorithm using the forward position pareto methodF(P)=min(η J ,η G ,η S )T, and obtain corresponding design variable.
2. round steel end face according to claim 1 labels series parallel robot in five degrees of freedom Dimension Synthesis method, feature exists
In: step 7 uses, using Matlab programming tool, using the non-dominated sorted genetic algorithm (NSGA- with elite retention strategy
II objective function minimum value) is found.
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CN110666840A (en) * | 2019-10-16 | 2020-01-10 | 金陵科技学院 | Industrial robot comprehensive performance index design and evaluation method |
CN111571584A (en) * | 2020-04-28 | 2020-08-25 | 石家庄钢铁有限责任公司 | Robot labeling path planning and singularity checking method for bundled bars |
CN111775138A (en) * | 2020-06-01 | 2020-10-16 | 上海大学 | Design method for optimizing size parameters of series-parallel robot for constructing multi-objective function |
CN113172603A (en) * | 2021-04-19 | 2021-07-27 | 嘉兴学院 | Decoupling method of rigidity model of hybrid robot |
CN113400347A (en) * | 2021-05-25 | 2021-09-17 | 华南理工大学 | Performance evaluation method of 3-PRRU parallel robot |
CN114193436A (en) * | 2021-12-07 | 2022-03-18 | 珠海格力智能装备有限公司 | Robot working space optimization method and device, storage medium and equipment |
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CN107398893A (en) * | 2017-09-06 | 2017-11-28 | 河北科技大学 | Round steel end face labels series-parallel robot structural topology method |
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CN110666840A (en) * | 2019-10-16 | 2020-01-10 | 金陵科技学院 | Industrial robot comprehensive performance index design and evaluation method |
CN111571584A (en) * | 2020-04-28 | 2020-08-25 | 石家庄钢铁有限责任公司 | Robot labeling path planning and singularity checking method for bundled bars |
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CN114831847A (en) * | 2022-03-29 | 2022-08-02 | 中国农业大学 | Neck rehabilitation training robot with four branched chain parallel mechanisms and force control method thereof |
CN115039572A (en) * | 2022-07-22 | 2022-09-13 | 农业农村部南京农业机械化研究所 | Six-degree-of-freedom series-parallel picking manipulator |
CN115039572B (en) * | 2022-07-22 | 2023-11-14 | 农业农村部南京农业机械化研究所 | Six-degree-of-freedom series-parallel picking manipulator |
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