CN108804385A - A method of solving articulated coordinate machine optimum measurement area - Google Patents
A method of solving articulated coordinate machine optimum measurement area Download PDFInfo
- Publication number
- CN108804385A CN108804385A CN201810857333.4A CN201810857333A CN108804385A CN 108804385 A CN108804385 A CN 108804385A CN 201810857333 A CN201810857333 A CN 201810857333A CN 108804385 A CN108804385 A CN 108804385A
- Authority
- CN
- China
- Prior art keywords
- error
- space
- machine
- measuring
- measurement
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Analysis (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- Artificial Intelligence (AREA)
- Biophysics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computational Linguistics (AREA)
- Geometry (AREA)
- Biomedical Technology (AREA)
- Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Operations Research (AREA)
- General Health & Medical Sciences (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Length Measuring Devices With Unspecified Measuring Means (AREA)
Abstract
A method of articulated coordinate machine optimum measurement area is solved, is applied in coordinate measuring technology field.This method according to the measurement model of articulated coordinate machine, establishes the articulated coordinate machine error model based on circle encoder angle error first；The random number of 6 joint rotation angles is obtained using Monte Carlo theory, using the measurement space of numerical method simulation analysis measuring machine；Using Newton iteration method and it is appropriate layout and extended method, obtain the worst error partial picture in entire space；Then it entire will measure that space is equally spaced to cut into several small cubes regions, each region maximum error of measuring is determined using FOA+PSO；Finally, the region of wherein maximum error of measuring minimum is found by comparing.This method can fast and accurately determine the optimum measurement area of articulated coordinate machine, to improve the precision of articulated coordinate machine.
Description
Technical field
The present invention relates to a kind of solution articulated coordinate machine optimum measurements applied in coordinate measuring technology field
The method in area.
Background technology
Articulated coordinate machine is the space fisher's formula cascaded structure that more bars are connected in series by multiple rotary joints,
Since it is fast with measuring speed, be convenient for carrying, measures that space is openr, measurement dead angle is less, the requirement to environment is low excellent
Point is widely used in vehicle complete vehicle and parts, mold, aerospace, steam turbine, heavy-duty machine and other mechanical processing rows
Industry.
Six-freedom joint type coordinate measurement machine is by 3 measuring arms, 6 joints, 6 round encoders and 1 gauge head structure
At.The angle of each articulation is obtained by circle encoder output mounted thereto；The angle and survey that 6 encoders record
Amount machine structural parameters determine the coordinate of measuring machine gauge head.
Due to the mechanical structure of articulated coordinate machine tandem, justify the error of encoder since amplification passes
When being delivered to gauge head, cause its measurement accuracy relatively low, improving the precision of articulated coordinate machine at present becomes core urgently to be resolved hurrily
Heart problem.
When articulated coordinate machine measures any point in space, it can be gone by a variety of different postures
It measures, the angle error of the round encoder of lower 6 of different postures will be there are many different combinations.It is possible thereby to be generalized to
The entire measurement space of articulated coordinate machine, i.e. the error change at any point be with certain rule and continuous, therefore
There are the cubical area of worst error minimum, that is, optimum measurement areas in entirely measurement space.
Drosophila optimization algorithm is a kind of new method deduced out based on drosophila foraging behavior and seek global optimization, by Pan Wen
Super professor proposed in 2011.Drosophila algorithm has many advantages, such as that simple, parameter is few, calculation amount is small, low optimization accuracy is high, answers extensively
For the various fields such as military affairs, engineering, medicine, management and finance, but there is presently no scholars to be applied to measurement of coordinates
Field.One kind that particle cluster algorithm (PSO) belongs to evolution algorithm is similar with simulated annealing, it is also from solving at random
Hair finds optimal solution by iteration, it is also the quality of solution to be evaluated by fitness, but it is more than genetic algorithm rule
Simply, it does not have the intersection of genetic algorithm and mutation operation, it by follow current search to optimal value come find it is global most
It is excellent.The advantages that this algorithm is easy with its realization, precision is high, convergence is fast causes the attention of academia, and practical in solution
Its superiority is illustrated in problem.
Domestic many scholars are studied improving articulated coordinate machine precision and optimum measurement area problem.Zheng
Big rise etc. obtains using spot measurement with support vector machines theory as the optimum measurement area of target and using space distance measurement as mesh
Target optimum measurement section model, but this method practicability is not strong, and model is established based on a large amount of measured data
, measurement error does not include circle encoder angle error.Qin Zirui obtains circle volume on measuring machine using the method for simulation analysis
Measurement error has certain compensated conclusion caused by code device error, and give measurement error it is smaller when 6 circle codings
The angle use scope of device.But since measuring machine is using manual measurement mode, measuring posture has randomness, therefore
This method is simultaneously impracticable.
Invention content
In order to overcome the shortcomings of in background technology, the invention discloses a kind of solution articulated coordinate machines most preferably to survey
The method for measuring area, the above method can solve the optimum measurement area of articulated coordinate machine, make in its optimum measurement area
Industry can achieve the purpose that improve articulated coordinate machine precision.
The present invention is a kind of method in solution articulated coordinate machine optimum measurement area, the articulated type measurement of coordinates
Machine is six-freedom joint type coordinate measurement machine, is made of 3 measuring arms, 6 joints, 6 round encoders and 1 gauge head.Respectively
The angle of a articulation is obtained by circle encoder output mounted thereto；
The present invention realizes that goal of the invention adopts the following technical scheme that：
Step 1: the measurement equation p of articulated coordinate machine is established using D-H methods,
Wherein：C indicates that cos, s indicate sin, liIt is the length of rod piece；θiIt is each joint actual rotation amount；diIt is that joint is inclined
The amount of setting；aiIt is the windup-degree of adjacent segment axis；L is measuring machine gauge head length.
Step 2: demarcating circle encoder errors, obtain its error characteristics function ei(θi).By articulated coordinate machine knot
Structure parameter and error characteristics function substitute into it and measure equation p, obtain the coordinate formula with joint rotation angle error：
Then since measurement error caused by circle encoder is：
Step 3: obtaining the random number of each joint rotation angle using monte carlo method, surveyed using the method for numerical value
The whole of amount machine measures space.(being emulated with Matlab)
A sampled point is taken Step 4: appointing, its coordinate is substituted into the measurement model of articulated coordinate machine, using newton
Solution by iterative method Nonlinear System of Equations is obtained a variety of angle measurements combination of arbitrary point in space, then substitutes into and missed based on circle encoder
In the Measuring error model of difference, error distribution and the maximum error of measuring of the sampled point are obtained.In x>In 0, y=0 half of plane
It arranges sampled point, the data acquisition system of sampled point in this half of plane is obtained, to the angle value θ in joint 11In addition a deflection angle
Spend Δ θ1, obtain and x>Angle is Δ θ between 0, y=0 half of plane1Another plane on corresponding all the points in difference
The angle set under posture is measured, to obtain entirely measuring the error distribution in space, the maximum of each sampled point is acquired and surveys
Error is measured, the worst error distribution situation in entire space is obtained.
Step 5: worst error model can be obtained by step 1 and step 2：
The whole space that measures is divided into several small solid spaces at equal intervals, is acquired using FOA+PSO each three-dimensional empty
Interior worst error, the worst error of more each solid space obtain the solid space of worst error minimum, as most
Good measurement zone.
Compared with the prior art, the present invention has the beneficial effect that：
The structural parameters of circle encoder errors characterisitic function and articulated coordinate machine are substituted into articulated type in the present invention
In the measurement model of coordinate measuring machine, the error model of the articulated coordinate machine based on circle encoder angle error is obtained；
It is combined using the inverse multiple round encoder angle measurements for solving arbitrary sampled point of Newton iteration method, and substitutes into its error model, be somebody's turn to do
The measurement error distribution of point and maximum error of measuring；It is layouted and extended method using appropriate, acquires entire measure in space
Error is distributed and worst error distribution, not only solves the problem that measuring data sample number is limited in practical measurement, also reduces
Many workloads, improve work efficiency；Drosophila algorithm (FOA) and particle cluster algorithm (PSO) are finally combined utilization for the first time
It is substantially increased to measurement of coordinates field using the advantages that drosophila algorithm is simple, parameter is few, calculation amount is small, low optimization accuracy is high
Computational efficiency and precision.The present invention can acquire the optimum measurement region of articulated coordinate machine, and six degree of freedom is improved to be follow-up
It articulated coordinate machine automatic measurement precision and establishes optimum measurement area database and lays a good foundation.
Description of the drawings
Fig. 1 is to measure space cloud point figure.
Fig. 2 is error point cloud chart under the different postures of sampled point M (200,0, -200).
Fig. 3 is each sampled point maximum error of measuring distribution map in entire measurement space.
Fig. 4 is the structure chart of six-freedom joint type coordinate measurement machine.
Specific implementation mode
Explanation is further explained to the present invention below by way of specific embodiment.
In the present embodiment articulated coordinate machine be six-freedom joint type coordinate measurement machine, by 3 measuring arms, 6
Joint, 6 round encoders and 1 gauge head are constituted.The angle of each articulation is obtained by circle encoder output mounted thereto
?；
Specific implementation step is as follows：
Step 1: the measurement equation p of articulated coordinate machine is established using D-H methods,
Wherein：C indicates that cos, s indicate sin, liIt is the length of rod piece；θiIt is each joint actual rotation amount；diIt is that joint is inclined
The amount of setting；aiIt is the windup-degree of adjacent segment axis；L is measuring machine gauge head length.
Step 2: demarcating circle encoder errors, error distribution curve be meet Dirichlet condition using 2 π as the period
Class sine curve, its error distribution curve is set as three rank Fourier spaces, obtains its error characteristics function ei(θi)。
ei(θi)=ai+bicos(θi)+cisin(θi)+dicos(2θi)+eisin(2θi)+ficos(3θi)
+gisin(3θi)
Articulated coordinate machine structural parameters and error characteristics function are substituted into it and measure equation p, obtain carrying joint
The coordinate formula of angular errors：
Then since measurement error caused by circle encoder is：
Step 3: obtaining the random number of each joint rotation angle using monte carlo method, surveyed using the method for numerical value
The whole of amount machine measures space.According to articulated coordinate machine structural parameters, with Matlab simulation analysis, its entire measurement is empty
Between, as shown in Figure 1.According to simulation result it is found that it is a complete sphere that this coordinate measuring machine, which measures space, inside is without sky
Chamber, gauge head coverage are：
xmin=-6.06286 × 102mm xmax=6.05847 × 102mm
ymin=-6.05503 × 102mm ymax=6.07493 × 102mm
zmin=-3.12345 × 102mm zmax=9.02439 × 102mm
Step 4:
A, sampled point M (200,0, -200) is taken, its coordinate is substituted into the measurement model of articulated coordinate machine, is used
Newton iteration method solves Nonlinear System of Equations, and the 5000 kinds of angle measurements combination for obtaining arbitrary point in space (it is as follows to choose 20 groups of data
Shown in table),
Then this 5000 kinds of angle measurement combinations are substituted into the Measuring error model based on circle encoder errors, obtains this and adopts
The error of sampling point is distributed and maximum error of measuring.(as shown in Figure 2)
B, in x>Sampled point is arranged in 0, y=0 half of plane, obtains the data acquisition system of sampled point in this half of plane, it is right
The angle value θ in joint 11In addition a deflection angle Δ θ1, obtain and x>Angle is Δ θ between 0, y=0 half of plane1It is another
Angle set of the corresponding all the points under different measurement postures in one plane, to obtain entirely measuring in space
Error is distributed, and is acquired the maximum error of measuring of each sampled point, is obtained the worst error distribution situation in entire space.(such as Fig. 3
It is shown)
Step 5:
A, worst error model can be obtained by step 1 and step 2：
Above formula is converted to
Because being constrained optimization problem, constraint is handled using exterior penalty function, is become a kind of extrapunitiveness letter
Number, is then added in object function.Remember that feasible zone is：
Constructing penalty function is：
Target augmented program is：
Thus constrained optimization problem is converted for unconstrained optimization problem, then object function is：
B, object function minimum value, the sampling of corresponding point, that is, worst error minimum are acquired using FOA+PSO algorithms
Point.
Drosophila algorithm basic procedure is
(1) random initial drosophila group position
InitX_axis
InitY_axis
(2) random direction and distance that drosophila individual utilizes smell search of food are assigned
Xi=X_axis+Random Value
Yi=Y_axis+Random Value
(3) due to that can not learn food position, so first estimating at a distance from origin (Dist), then flavor concentration is calculated
Decision content (S), value are the inverse of distance.
(4) flavor concentration decision content (S) substitutes into flavor concentration decision function, and the taste for acquiring the drosophila body position is dense
It spends (Smelli).
Smelli=Function (Si)
(5) the minimum drosophila (minimizing) of flavor concentration in this drosophila group is found out
[bestSmell, bestIndex]=min (Smell)
(6) retain best flavors concentration value and x, y-coordinate, drosophila group is flown to using vision toward the position at this time.
Smellbest=bestSmell
X_axis=X (bestIndex)
Y_axis=Y (bestIndex)
(7) enter iteration optimizing, repeat step 2-5, judge whether flavor concentration is better than the flavor concentration of prior-generation, such as
Fruit, which is more than, thens follow the steps 6.
Parameter in PSO algorithms has c1、c2And ω, c1、c2For acceleration factor, ω is inertia weight.These three parameters
It can influence the efficiency and accuracy of particle cluster algorithm.Accelerated factor c1Larger value is set, can make particle is excessive to hesitate locally
It wanders, on the contrary, larger c2Value can make particle Premature Convergence to local optimum.What inertia weight ω embodied is that particle is inherited
The ability of previous speed, larger inertia weight value are conducive to global search, and smaller inertia weight value is then more advantageous to office
Portion is searched for.It is selected here for the selection of inertia weight by consulting literatures and many experiments：
Wherein ωstart=0.9, ωend=0.4, k are current iteration algebraically, TmaxFor greatest iteration algebraically.
Drosophila algorithm (FOA) optimizing is then utilized for acceleration factor, it is c to acquire optimal value1=c2=1.49445.
The whole space that measures is divided into 343 small solid spaces by interval of 200mm respectively from three directions of x, y, z,
The worst error in each solid space is acquired using particle cluster algorithm (PSO), runs program, rejects and is not measuring in space
Data, obtain 220 groups of data, take 15 groups of data as shown in the table,
Analyze the data obtained it is found that each region maximum error of measuring variation range be 0.0634mm~0.1876mm its
The error of middle region -100≤x≤100, -100≤y≤100,400≤z≤600 is minimum, is 0.0634mm, workpiece is placed
It is measured in the small cubes region, precision highest, i.e. the optimum measurement region of the six-freedom joint type coordinate measurement machine.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case of without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, nothing
By from the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by institute
Attached claim rather than above description limit, it is intended that will fall within the meaning and scope of the equivalent requirements of the claims
All changes be included within the present invention.Any reference numeral in claim should not be considered as to the involved right of limitation
It is required that.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment is only
It contains an independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art answer
When considering the specification as a whole, the technical solutions in the various embodiments may also be suitably combined, forms people in the art
The other embodiment that member is appreciated that.
Claims (1)
1. a kind of method solving articulated coordinate machine optimum measurement area, the articulated coordinate machine is six degree of freedom
Articulated coordinate machine is made of 3 measuring arms, 6 joints, 6 round encoders and 1 gauge head；Each articulation
Angle is obtained by circle encoder output mounted thereto；
It is characterized by comprising following steps：
Step 1: establishing the measurement equation p of articulated coordinate machine using D-H methods；
Wherein：C indicates that cos, s indicate sin, liIt is the length of rod piece, θiIt is each joint actual rotation amount；diIt is joint amount of bias；
aiIt is the windup-degree of adjacent segment axis；L is measuring machine gauge head length；
Step 2: demarcating circle encoder errors, obtain its error characteristics function ei(θi)；Articulated coordinate machine structure is joined
Number and error characteristics function substitute into it and measure equation p, obtain the coordinate formula with joint rotation angle error：
Then since measurement error caused by circle encoder is：
Step 3: obtaining the random number of each joint rotation angle using monte carlo method, measuring machine is obtained using the method for numerical value
Whole measure space；(being emulated with Matlab)
A sampled point is taken Step 4: appointing, its coordinate is substituted into the measurement model of articulated coordinate machine, using Newton iteration method
Nonlinear System of Equations is solved, a variety of angle measurements combination of arbitrary point in space is obtained, then substitutes into the survey based on circle encoder errors
It measures in error model, obtains error distribution and the maximum error of measuring of the sampled point；In x>Arrangement is adopted in 0, y=0 half of plane
Sampling point obtains the data acquisition system of sampled point in this half of plane, to the angle value θ in joint 11In addition a deflection angle Δ θ1, obtain
It arrives and x>Angle is Δ θ between 0, y=0 half of plane1Another plane on corresponding all the points in different measurement postures
Under angle set, to obtain entirely measure space in error distribution, acquire the maximum error of measuring of each sampled point, obtain
To the worst error distribution situation in entire space；
Step 5: worst error model can be obtained by step 1 and step 2：
The whole space that measures is divided into several small solid spaces at equal intervals, is acquired in each solid space using FOA+PSO
Worst error, the worst error of more each solid space obtains the solid space of worst error minimum, as optimum measurement
Area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810857333.4A CN108804385A (en) | 2018-07-31 | 2018-07-31 | A method of solving articulated coordinate machine optimum measurement area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810857333.4A CN108804385A (en) | 2018-07-31 | 2018-07-31 | A method of solving articulated coordinate machine optimum measurement area |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108804385A true CN108804385A (en) | 2018-11-13 |
Family
ID=64078607
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810857333.4A Pending CN108804385A (en) | 2018-07-31 | 2018-07-31 | A method of solving articulated coordinate machine optimum measurement area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108804385A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109612420A (en) * | 2019-01-10 | 2019-04-12 | 安徽理工大学 | A kind of determination method applied to the joint arm measuring machine optimum measurement area for realizing workpiece on-line measurement |
| CN112833783A (en) * | 2020-12-31 | 2021-05-25 | 杭州电子科技大学 | Variable measurement space method of joint type coordinate measuring machine based on jaw joint |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104899431A (en) * | 2015-05-19 | 2015-09-09 | 上海大学 | LSSVM fluctuating wind speed prediction method based on integration of ant colony and particle swarm |
-
2018
- 2018-07-31 CN CN201810857333.4A patent/CN108804385A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104899431A (en) * | 2015-05-19 | 2015-09-09 | 上海大学 | LSSVM fluctuating wind speed prediction method based on integration of ant colony and particle swarm |
Non-Patent Citations (1)
| Title |
|---|
| 江超: "关节式坐标测量机最佳测量区实用化研究", 《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109612420A (en) * | 2019-01-10 | 2019-04-12 | 安徽理工大学 | A kind of determination method applied to the joint arm measuring machine optimum measurement area for realizing workpiece on-line measurement |
| CN112833783A (en) * | 2020-12-31 | 2021-05-25 | 杭州电子科技大学 | Variable measurement space method of joint type coordinate measuring machine based on jaw joint |
| CN112833783B (en) * | 2020-12-31 | 2022-05-03 | 杭州电子科技大学 | Variable measurement space method of joint type coordinate measuring machine based on jaw joint |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2021238191A1 (en) | Positioning compensation method and apparatus for robot | |
| CN104482911B (en) | Sphericity error assessment method based on error ball | |
| Zhang et al. | Machine tool thermal error modeling and prediction by grey neural network | |
| CN109612420A (en) | A kind of determination method applied to the joint arm measuring machine optimum measurement area for realizing workpiece on-line measurement | |
| CN102785129A (en) | On-line detection method of curved surface machining precision of complex part | |
| CN108804385A (en) | A method of solving articulated coordinate machine optimum measurement area | |
| CN108470358B (en) | Point cloud registration method based on second-order oscillation artificial bee colony algorithm | |
| CN110260786A (en) | A kind of robot vision measuring system and its scaling method based on external trace | |
| CN102607552A (en) | Industrial robot space grid precision compensation method based on neural network | |
| CN109141266B (en) | Steel structure measuring method and system | |
| CN108682043A (en) | A kind of complex-curved measure planning method based on parameter mapping | |
| CN109813225A (en) | A kind of flexible arm coordinate measuring machine space error compensation method | |
| CN109085643A (en) | The early substep joint inversion method to wave | |
| CN102013114A (en) | Microstation v8i-based city rapid-modeling method | |
| Zhao et al. | Workspace analysis for a 9-DOF hyper-redundant manipulator based on an improved Monte Carlo method and voxel algorithm | |
| CN112720480B (en) | Robot track correction method and system based on grading errors | |
| Pathak et al. | Evaluating geometric characteristics of planar surfaces using improved particle swarm optimization | |
| CN116049941B (en) | Method for extracting and analyzing multidimensional state of assembled ring truss structural member before assembly | |
| CN114707253B (en) | Feature-guidance-based three-dimensional measurement robot scanning track optimization method | |
| CN110900608A (en) | Robot kinematics calibration method based on optimal measurement configuration selection | |
| CN109631813B (en) | Calibration method of large-size articulated arm type coordinate measuring machine | |
| Cheng et al. | Selection and modeling of temperature variables for the thermal error compensation in servo system | |
| CN116520281B (en) | DDPG-based extended target tracking optimization method and device | |
| CN109613618A (en) | A kind of long term drift error compensating method of gravimeter | |
| CN109816783A (en) | The mapping method of three-dimensional modeling is realized in a kind of coordinate diffusion |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20181113 |
|
| WD01 | Invention patent application deemed withdrawn after publication |