CN106272428B - A kind of apple picking robot end effector grasp force Active Compliance Control method - Google Patents
A kind of apple picking robot end effector grasp force Active Compliance Control method Download PDFInfo
- Publication number
- CN106272428B CN106272428B CN201610821173.9A CN201610821173A CN106272428B CN 106272428 B CN106272428 B CN 106272428B CN 201610821173 A CN201610821173 A CN 201610821173A CN 106272428 B CN106272428 B CN 106272428B
- Authority
- CN
- China
- Prior art keywords
- force
- end effector
- grasp force
- picking robot
- apple
- 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.)
- Expired - Fee Related
Links
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1653—Programme controls characterised by the control loop parameters identification, estimation, stiffness, accuracy, error analysis
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Manipulator (AREA)
Abstract
The invention discloses a kind of apple picking robot end effector grasp force Active Compliance Control methods, belong to picking robot control technology field, the crawl force control method be characterized in that being collected by the force snesor and encoder configured on apple picking robot end effector act on active force on crawl object and and evolution amount, using the displacement collected and power as the input for the recurrent least square method identifier for becoming forgetting factor, on-line identification is carried out to impedance controller stiffness coefficient, and the stiffness parameters of the impedance controller of varying environment requirement are adapted to according to adjust automatically when the output fructufy of second order impedance controller.The control method can effectively reduce crawl damage ratio of the picking robot to apple, and improve the anti-interference ability that robot works in the wild.
Description
Technical field
The present invention relates to apple picking robot control fields, are controlled based on variation rigidity coefficient resister especially with respect to one kind
Apple picking robot end effector grasp force Active Compliance Control method, belong to IT application to agriculture field.
Background technology
China is a large agricultural country, realize the modernization, mechanization and automation of agricultural production be social development must
Right trend.Picking fruit is the link most taken time and effort in agricultural production, has of high cost, seasonal strong, needs largely
The features such as labour.But due to industrial rapid development, a large amount of agricultural workforce's missings and aging of population aggravation etc.
Reason, enabling the labour being engaged in agricultural production is fewer and fewer, and existing demand cannot be met by depending merely on hand labor.
In order to the problems of solve, agricultural robot comes into being, end effector as the component being in direct contact with fruits and vegetables,
Consequence is occupied in agricultural robot research, in existing end effector research, there is two difficult points：1. end is held
The design of row device does not have versatility, and existing end effector is designed both for a kind of or a kind of fruits and vegetables, and
Used passive smoothing method is difficult to realize the lossless picking to fruits and vegetables, hinders the popularization of agricultural robot；2. existing
End effector crawl control technology cannot achieve the active compliance crawl to fruits and vegetables, and end effector grasp force crosses conference damage
Fruits and vegetables, smaller grasp force can cause to occur fruits and vegetables in the process of grasping to fall, and to also lead to the damage of fruits and vegetables, this is also hindered
The business promotion of agricultural robot.So invent a kind of active compliance crawl controlling mechanism, can to crawl active force into
Row perception is adapted to and is controlled, particularly important to the complaisant grasping picking of fruits and vegetables to realizing end effector.
Invention content
This programme is the deficiency for solving existing apple picking robot end effector grasp force control technology, be cannot achieve
The defect of complaisant grasping control, proposes a kind of end effector of robot grasp force Active Compliance Control method of two close cycles,
Middle position inner ring uses incremental timestamp, power outer shroud to use the impedance control of variation rigidity coefficient, and this control method can be simultaneous
The shift transformation of grasp force and end effector is cared for, and also there is certain fit for the field work environment of agricultural robot
Ying Xing.
The technical solution adopted by the present invention to solve the technical problems includes the following steps：
Step 1 obtains the grasp force f that end effector acts on apple using force snesor, is obtained using position coder
To displacement converted quantity Δ x；F, Δ x are sampled using force snesor and position coder, sampling number N, and N ＞ 3；
The grasp force and displacement data that step 2 is obtained according to detection, using identifier to equivalent stiffness coefficients keqIt carries out
On-line identification, wherein the recurrent least square method that change forgetting factor is introduced in identifier recognizes equivalent stiffness coefficients,
Forgetting factor will be become and be set as the function about measured value and calculated value error, enable forgetting factor with the transformation of grasp force error
And adjust automatically；
Kinetic model when end effector and apple are collided is reduced to single order admittance model：F=keq·Δ
x；Wherein, f is the grasp force of force snesor detection, and Δ x is the shift transformation amount that position coder measures, keqIt is striked etc.
Imitate stiffness coefficient；
Step 3 obtains impedance control stiffness parameters by equivalent stiffness equations, the equivalent stiffness coefficients obtained using identification
keqImpedance controller stiffness coefficient is adjusted, the impedance controller is：
Wherein, mt, bt, ktIt is the inertia coeffeicent of impedance controller, damped coefficient and stiffness coefficient respectively,It is to set
Fixed acceleration, speed and displacement,It is actual acceleration, speed and displacement；fe, frBe actual grasp force and to
Fixed grasp force；
The position quantity that impedance controller exports is overlapped to obtain positioner by step 4 with given position signal
Input signal passes through the voltage signal of positioner output driving motor；Positioner is incremental timestamp device：
Wherein, u (t), u (t-1) indicate t, the output of t-1 sampling instant positioner, e (t), e (t- respectively
1), e (t-2) is t, t-1, the deviation of t-2 sampling instant, k respectivelypGain, T, T are controlled for ratioD、T1It is PID respectively
Controller sampling time, derivative time, the time of integration；
The voltage signal that positioner exports is changed into the drive signal of torque motor by step 5, for controlling motor
Work, execute crawl task.
Further, in the step 1, force snesor is 402 force sensing resistance type force snesors of FSR；Position coder model
For TRD-NA1024NW.
Further, in the step 2, in iteration identification process, when the error between measured value and given grasp force is small
When 10%, system enters stable state, and iteration terminates.
Further, the specific identification process of identifier is in step 2~3：
Measure one group of (xt, yt) when, equivalent stiffness coefficients k is obtained by following formulaeqInitial value, x in formulat, ytRespectively represent t
The displacement of secondary end effector and the size of grasp force；
kEq, t=(xt Txt)-1xt Tyt(t=1,2 ...)
Then equivalent stiffness coefficients k is sought by recurrent least square methodeqIterative formula it is as follows：
Pt+1=Pt/(Ct+xt+1Ptxt+1)；θt+1=Pt+1xt+1；
kEq, t+1=kEq, t+θt+1(yt+1-xt+1θt) (t=0,1,2 ...)
Wherein：PtIt is covariance matrix, kEq, tIt is equivalent stiffness, as t=0, P0And kEq, 0Respectively represent initial covariance
Matrix and initial equivalent stiffness, take P0=0, kEq, 0=1.CtFor forgetting factor, CtSelection be very important because not just
When value can lead to covariance matrix PtBecome inaccurate；In time-varying system, one is established about error etFunction be used for ask
Take CtIt is typically considered a very reasonable effective mode；As common recurrent least square method structure, it will forget
The factor is set to a function about error；
Ct=1-a1[arctan(a2(|et|-a3))/π+1/2]
Wherein, et=yt-KEq, txt；a1, a2, a3It is set to 0.4,0.5,1 by test of many times；
It is defined according to equivalent stiffness coefficients：ktkeRespectively represent impedance controller rigidity
Coefficient and environment rigidity coefficient；
Impedance controller stiffness coefficient can then be obtained：
Last controller can be designed to：
The present invention due to using the technology described above, has the following advantages：
1. the present invention can realize the dynamic equilibrium between grasp force and crawl position, to realize by impedance control
The Active Compliance Control of apple picking robot crawl.
2. in view of the particularity of operating environment, impedance control parameter is adjusted in real time using recurrent least square method
It is whole, it can be better achieved and grasp force is followed, be effectively reduced apple crawl loss percentage.
Description of the drawings
It is this system control method block diagram to scheme (1)；
Figure (2) is the schematic diagram of institute's foundation apple picking robot end effector of the invention.
Specific implementation mode
A kind of apple picking robot grasp force Active Compliance Control method based on impedance control, includes the following steps：
1) end effector grasp force f is obtained using the measurement of FSR402 force sensing resistance types force snesor 200, utilizes TRD-
The information of NA1024NW position coders 190 obtains the shift transformation amount Δ x of end effector, will obtain grasp force and displacement letter
Number it is input to the equivalent stiffness coefficients k of on-line Identifier environment-identification and controllereq, and the second order impedance single order by being established
Admittance model y=keqΔ x finds out the stiffness coefficient in impedance controller.
2) the grasp force f of force snesor 200 and position coder 210 to end effector is utilizedrWith offset variable Δ x,
Within a sampling period, n times sampling, and N ＞ 3 are carried out, the average value that n times data measure is taken to be obtained as a sampling period
Final data is input in on-line Identifier, further according to equivalent crawl model, using the recurrent least square method for becoming forgetting factor
The On-line Estimation value of equivalent stiffness coefficients is calculated.When the error between practical grasp force and given grasp force is less than 10%
When, iteration terminates, and system enters steady-working state.
3) equivalent stiffness coefficients k is utilizedeqStiffness coefficient 123 in impedance controller 120 is adjusted.The impedance
Controller 120 is：
Wherein, mt, bt, ktIt is the inertia coeffeicent of impedance controller, damped coefficient and stiffness coefficient respectively,It is to set
Fixed acceleration, speed and displacement,It is actual acceleration, speed and displacement.fe, frBe actual grasp force and to
Fixed grasp force.
Only consider one-dimensional condition impedance, that is, by multidimensional variable matrix conversion is one-dimensional variable, it is rigid to impedance controller
Spending the modified method of coefficient is
4) position quantity of impedance controller output is overlapped to obtain the defeated of positioner with given position signal
Enter signal, passes through the voltage signal of positioner output driving motor.Positioner is incremental timestamp device：
Wherein, u (t), u (t-1) indicate t, the output of t-1 sampling instant positioner, e (t), e (t- respectively
1), e (t-2) is t, t-1, the deviation of t-2 sampling instant, k respectivelypGain, T, T are controlled for ratioD、T1It is PID respectively
Controller sampling time, derivative time, the time of integration.
5) the evolution amount of the output of impedance controller 120 is input in positioner, positioner output
The voltage of driving moment motor movement, to realize the crawl of end effector.
The present invention is described in detail below with reference to the accompanying drawings and embodiments
A kind of apple picking robot end effector grasp force active compliance control based on the control of variation rigidity coefficient resister
Method processed, as shown in Figure 1, its structure includes：Comparator 110,130,180, impedance controller 120, position PID controller 150,
Driving motor 160, controlled device end effector 170, position coder 190, force snesor 200 and on-line Identifier 210.Its
Middle impedance controller 120 includes inertia coeffeicent 121, damped coefficient 122 and stiffness coefficient 123.Comparator 110 receives given grab
Power taking and practical grasp force, the input terminal of the output termination impedance controller of comparator, the output end of impedance controller with give
Location information is added the input as comparator 130, and the output of comparator 130 connects 150 end of positioner.Positioner
The input terminal of 150 output end relay torque motors 160, the input terminal of the output termination end effector 170 of torque motor 160, end
The input terminal of actuator 170 output termination position coder 190 and force snesor 200, the output of force snesor 200 is held to terminate ratio
Compared with the input terminal of device 110, meanwhile, the output end of position coder 190 and force snesor 200 is also connected to on-line Identifier 210
Input terminal.
Fig. 2 is the embodiment of the present invention：At work, motor rotating forward can drive end to execute to apple picking robot
Device closure carries out crawl apple, and motor reversal can make end effector open release apple, and riding position is compiled under torque motor
Code device 190 is used for measuring relative displacement, and installation force snesor 200 measures the power for capturing apple on end effector.
The workflow of system is：Comparator 110 is by the predetermined grasp force of input and the reality that obtains from force snesor 200
Border power is compared, and generates error signal.Impedance controller 120 controls error signal, obtains position offset signal, and
It is added to obtain the input signal of positioner 150 with given position signal, by the adjusting of positioner 150, obtain
The control signal of driving motor, driving end effector capture objective fruit with certain speed.Force snesor 200 will
Force signal Input Online identifier 210, while position signal is input in on-line Identifier 210 by position coder, is distinguished online
Know device 210 and the equivalent stiffness coefficients k of fruits and vegetables is obtained by identification algorithmeqImpedance control rigidity is being obtained by equivalent stiffness model
Coefficient, and be entered into impedance controller 120, preferably correct the stiffness coefficient kt of impedance controller 120.
The operation principle of system is：The information input of force snesor and position coder to on-line Identifier is obtained online
Equivalent stiffness coefficients keq.The wherein algorithm of the on-line Identifier, is divided into following steps in detail：
When measuring one group of (xt, yt) when, equivalent stiffness coefficients k is obtained by following formulaeqInitial value.
kEq, t=(xt Txt)-1xt Tyt(t=1,2 ...)
Then equivalent stiffness coefficients k is sought by recurrent least square methodeqIterative formula it is as follows
Pt+1=Pt/(Ct+xt+1Ptxt-1)
θt+1=Pt+1xt+1
kEq, t+1=kEq, t+θt+1(yt+1-xt+1θt)
In formula：P=1, kS, t=0, CtFor forgetting factor.CtSelection be very important because inappropriate value can be led
Cause covariance matrix PtBecome inaccurate.In time-varying system, one is established about error etFunction be used for seek C usually quilts
It is considered a very reasonable effective mode.As common recurrent least square method structure, forgetting factor is arranged to
For a function about error.
Ct=1-a1[arctan(a2(|et|-a3))/π+1/2]
Wherein, et=yt-KEp, txt。a1, a2, a3It is set to 0.4,0.5,1 by test of many times.
It is defined according to equivalent stiffness coefficients
Impedance controller stiffness coefficient can then be obtained：
Last controller can be designed to：
To sum up, a kind of apple picking robot end effector grasp force Active Compliance Control method of the invention, this is grabbed
Power taking control method is characterized in that the force snesor by being configured on apple picking robot end effector and encoder acquisition
Obtain acting on active force on crawl object and and evolution amount, using the displacement collected and power as become forgetting because
The input of the recurrent least square method identifier of son carries out on-line identification to impedance controller stiffness coefficient, and according to second order
Adjust automatically is adapted to the stiffness parameters of the impedance controller of varying environment requirement when the output fructufy of impedance controller.The control
Method processed can effectively reduce crawl damage ratio of the picking robot to apple, and improve that robot works in the wild it is anti-dry
Disturb ability.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention.All essences in the present invention
All any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention made by within refreshing and principle.
Claims (4)
1. a kind of apple picking robot end effector grasp force Active Compliance Control method, which is characterized in that including following
Step：
Step 1 obtains the grasp force f that end effector acts on apple using force snesor, is obtained using position coder
Shift transformation amount Δ x；F, Δ x are sampled using force snesor and position coder, sampling number N, and N ＞ 3；
The grasp force and displacement data that step 2 is obtained according to detection, using identifier to equivalent stiffness coefficients keqIt carries out online
Identification, wherein the recurrent least square method that change forgetting factor is introduced in identifier recognizes equivalent stiffness coefficients, will become
Forgetting factor is set as the function about measured value and calculated value error, enables forgetting factor with the transformation of grasp force error and oneself
Dynamic adjustment；
Kinetic model when end effector and apple are collided is reduced to single order admittance model：F=keq·Δx；Its
In, f is the grasp force of force snesor detection, and Δ x is the shift transformation amount that position coder measures, keqFor it is striked it is equivalent just
Spend coefficient；
Step 3 obtains impedance control stiffness parameters by equivalent stiffness equations, the equivalent stiffness coefficients k obtained using identificationeqIt is right
Impedance controller stiffness coefficient is adjusted, and the impedance controller is：
Wherein, mt, bt, ktIt is the inertia coeffeicent of impedance controller, damped coefficient and stiffness coefficient respectively,xrIt is setting
Acceleration, speed and displacement,X is actual acceleration, speed and displacement；fe, frIt is that actual grasp force is grabbed with given
Power taking；
The position quantity that impedance controller exports is overlapped to obtain the defeated of positioner by step 4 with given position signal
Enter signal, passes through the voltage signal of positioner output driving motor；Positioner is incremental timestamp device：
Wherein, u (t), u (t-1) indicate t, the output of t-1 sampling instant positioner, e (t), e (t-1), e respectively
(t-2) it is respectively t, t-1, the deviation of t-2 sampling instant, kpGain, T, T are controlled for ratioD、T1It is PID control respectively
Device sampling time, derivative time, the time of integration；
The voltage signal that positioner exports is changed into the drive signal of torque motor by step 5, the work for controlling motor
Make, executes crawl task.
2. a kind of apple picking robot end effector grasp force Active Compliance Control method according to claim 1,
It is characterized in that, in the step 1, force snesor is 402 force sensing resistance type force snesors of FSR；Position coder model
TRD-NA 1024NW。
3. a kind of apple picking robot end effector grasp force Active Compliance Control method according to claim 1,
It is characterized in that, in the step 2, in iteration identification process, when the error between measured value and given grasp force is less than
When 10%, system enters stable state, and iteration terminates.
4. a kind of apple picking robot end effector grasp force Active Compliance Control method according to claim 1,
It is characterized in that, the specific identification process of identifier is in step 2~3：
One group of (x is measured firstt, yt) when, equivalent stiffness coefficients k is obtained by following formulaeqInitial value, x in formulat, ytRespectively represent t
The displacement of secondary end effector and the size of grasp force；
kEq, t=(xt Txt)-1xt Tyt(t=1,2 ...)
Then equivalent stiffness coefficients k is sought by recurrent least square methodeqIterative formula it is as follows：
Pt+1=Pt/(Ct+xt+1Ptxt+1)；θt+1=Pt+1xt+1；
kEq, t+1=kEq, t+θt+1(yt+1-xt+1θt) (t=0,1,2 ...)
Wherein：PtIt is covariance matrix, kEq, tIt is equivalent stiffness, as t=0, P0And kEq, 0Respectively represent initial covariance matrix
With initial equivalent stiffness, P is taken0=0, kEq, 0=1；CtFor forgetting factor, CtSelection be very important because inappropriate
Value can lead to covariance matrix PtBecome inaccurate；In time-varying system, one is established about error etFunction be used for seek Ct
It is typically considered a very reasonable effective mode；As common recurrent least square method structure, by forgetting factor
It is set to a function about error；
Ct=1-a1[arctan(a2(|et|-a3))/π+1/2]
Wherein, et=yt-KEq, txt；a1, a2, a3It is set to 0.4,0.5,1 by test of many times；
It is defined according to equivalent stiffness coefficients：ktkeRespectively represent impedance controller stiffness coefficient and
Environment rigidity coefficient；
Impedance controller stiffness coefficient can then be obtained：
Last controller can be designed to：
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610821173.9A CN106272428B (en) | 2016-09-13 | 2016-09-13 | A kind of apple picking robot end effector grasp force Active Compliance Control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610821173.9A CN106272428B (en) | 2016-09-13 | 2016-09-13 | A kind of apple picking robot end effector grasp force Active Compliance Control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106272428A CN106272428A (en) | 2017-01-04 |
| CN106272428B true CN106272428B (en) | 2018-10-09 |
Family
ID=57710021
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610821173.9A Expired - Fee Related CN106272428B (en) | 2016-09-13 | 2016-09-13 | A kind of apple picking robot end effector grasp force Active Compliance Control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106272428B (en) |
Families Citing this family (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106903689A (en) * | 2017-02-28 | 2017-06-30 | 深圳市笨笨机器人有限公司 | The method and a kind of robot of a kind of robot self-adaptative adjustment |
| CN107703748B (en) * | 2017-10-09 | 2020-01-07 | 东南大学 | Heavy-load robot static stiffness identification method based on offset plate design |
| CN108000477B (en) * | 2017-12-05 | 2021-06-15 | 哈尔滨工业大学 | Method for screwing valve by full-attitude active and passive flexible robot |
| CN108983601B (en) * | 2018-06-19 | 2021-08-03 | 江苏大学 | Parameter self-tuning impedance control system construction method for improving flexible grabbing performance of picking robot |
| CN109676634B (en) * | 2018-08-28 | 2021-02-19 | 杭州电子科技大学 | Active disturbance rejection controller and industrial robot |
| CN109062032B (en) * | 2018-10-19 | 2021-08-31 | 江苏省（扬州）数控机床研究院 | Robot PID variable impedance control method based on approximate dynamic inverse |
| CN109623818B (en) * | 2018-12-20 | 2021-06-18 | 北京理工大学 | Mechanical arm joint track optimization method based on time grouping |
| CN110053044B (en) * | 2019-03-19 | 2022-03-22 | 江苏大学 | Model-free self-adaptive smooth sliding mode impedance control method for clamping serial fruits by parallel robot |
| CN110449990A (en) * | 2019-07-11 | 2019-11-15 | 科德数控股份有限公司 | A kind of open loop dynamic error measurement method of closed-loop lathe |
| CN110561438B (en) * | 2019-09-19 | 2021-02-05 | 华中科技大学 | Industrial robot manpower/position compliance control method based on kinetic parameter identification |
| CN111249005A (en) * | 2020-03-20 | 2020-06-09 | 苏州新医智越机器人科技有限公司 | Puncture surgical robot compliance control system |
| CN111673733B (en) * | 2020-03-26 | 2022-03-29 | 华南理工大学 | Intelligent self-adaptive compliance control method of robot in unknown environment |
| CN111702767A (en) * | 2020-07-14 | 2020-09-25 | 重庆邮电大学 | Manipulator impedance control method based on inversion fuzzy self-adaptation |
| CN112247984B (en) * | 2020-09-17 | 2021-11-23 | 江苏大学 | Variable-stiffness joint trajectory tracking control method |
| CN112454351B (en) * | 2020-10-28 | 2022-06-21 | 上海景奕智能控制技术有限公司 | Manipulator control method and device and manipulator |
| CN112405531B (en) * | 2020-11-06 | 2022-03-29 | 广东电网有限责任公司电力科学研究院 | Position domain impedance control method and device, storage medium and operation robot |
| CN112959217B (en) * | 2021-03-25 | 2022-08-05 | 中国科学院宁波材料技术与工程研究所 | Force control method and device for reducing grinding and polishing vibration |
| CN112936291B (en) * | 2021-03-26 | 2022-11-15 | 中国科学院宁波材料技术与工程研究所 | Force control end effector vibration suppression method based on impedance control |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101332604A (en) * | 2008-06-20 | 2008-12-31 | 哈尔滨工业大学 | Control method of man machine interaction mechanical arm |
| CN102306029A (en) * | 2011-08-08 | 2012-01-04 | 东南大学 | Impedance self-adapting motion control method based on rehabilitation training robot |
| CN102837314A (en) * | 2011-06-24 | 2012-12-26 | 镇江华扬信息科技有限公司 | Force/position mixed control method of open type robot controller |
| WO2013069291A1 (en) * | 2011-11-10 | 2013-05-16 | パナソニック株式会社 | Robot, and control device, control method and control program for robot |
| CN104626168A (en) * | 2014-12-16 | 2015-05-20 | 苏州大学 | Robot force position compliant control method based on intelligent algorithm |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6444510A (en) * | 1987-08-13 | 1989-02-16 | Omron Tateisi Electronics Co | Robot control device |
-
2016
- 2016-09-13 CN CN201610821173.9A patent/CN106272428B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101332604A (en) * | 2008-06-20 | 2008-12-31 | 哈尔滨工业大学 | Control method of man machine interaction mechanical arm |
| CN102837314A (en) * | 2011-06-24 | 2012-12-26 | 镇江华扬信息科技有限公司 | Force/position mixed control method of open type robot controller |
| CN102306029A (en) * | 2011-08-08 | 2012-01-04 | 东南大学 | Impedance self-adapting motion control method based on rehabilitation training robot |
| WO2013069291A1 (en) * | 2011-11-10 | 2013-05-16 | パナソニック株式会社 | Robot, and control device, control method and control program for robot |
| CN104626168A (en) * | 2014-12-16 | 2015-05-20 | 苏州大学 | Robot force position compliant control method based on intelligent algorithm |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106272428A (en) | 2017-01-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106272428B (en) | A kind of apple picking robot end effector grasp force Active Compliance Control method | |
| CN107677709B (en) | Method for testing semiconductor gas sensitive element with gas sensitive material preparation step | |
| Rovner et al. | Experiments toward on-line identification and control of a very flexible one-link manipulator | |
| US7643946B2 (en) | Method and system for appraising the wear of axles of a robot arm | |
| CN108983601B (en) | Parameter self-tuning impedance control system construction method for improving flexible grabbing performance of picking robot | |
| CN112276944A (en) | Man-machine cooperation system control method based on intention recognition | |
| CN107966242B (en) | One-touch baroceptor field calibration system and method suitable for deep ocean buoy | |
| CN101562422B (en) | Automatic setting method for speed ring control parameters of alternating current servo driver | |
| CN111639749A (en) | Industrial robot friction force identification method based on deep learning | |
| Yan et al. | Comparison of differentiation schemes for the velocity and acceleration estimations of a pneumatic system | |
| Rane et al. | Design of an IoT based smart plant monitoring system | |
| CN106569406B (en) | Method for rapidly identifying model parameters of brush direct-current motor based on scale transformation | |
| CN103279030B (en) | Dynamic soft measuring modeling method and device based on Bayesian frame | |
| CN109062051A (en) | A method of improving Identification of Dynamic Parameters of Amanipulator precision | |
| CN109039208A (en) | A kind of switched reluctance machines incremental inductance characteristic online test method | |
| CN110132628A (en) | A kind of combine harvester assembling quality detection device and method | |
| Piacenza et al. | Pouring by feel: An analysis of tactile and proprioceptive sensing for accurate pouring | |
| CN106533285B (en) | Permanent magnet DC motor method for controlling number of revolution based on Kriging model | |
| CN107370446A (en) | Agricultural operation machine actuating device | |
| CN109184925A (en) | Electronic Throttle Control method based on Adaptive Integral terminal sliding mode technology | |
| CN109975702B (en) | Direct-current gear reduction motor quality inspection method based on circulation network classification model | |
| CN103217458A (en) | Method for preparing humidity-sensitive film | |
| CN114337427A (en) | Rotational inertia identification method of recursive least square method with forgetting factor | |
| CN204536850U (en) | Plant's environment monitoring control system | |
| JP7094210B2 (en) | Characteristic estimation system, characteristic estimation method, and program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20181009 Termination date: 20190913 |