CN102830701A - Coordination control method for system with multiple mobile robots - Google Patents
Coordination control method for system with multiple mobile robots Download PDFInfo
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- CN102830701A CN102830701A CN2012103152562A CN201210315256A CN102830701A CN 102830701 A CN102830701 A CN 102830701A CN 2012103152562 A CN2012103152562 A CN 2012103152562A CN 201210315256 A CN201210315256 A CN 201210315256A CN 102830701 A CN102830701 A CN 102830701A
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Abstract
The invention provides a coordination control method for a system with multiple mobile robots. The coordination control method comprises the following steps of: obtaining a personnel current moment position, an input matrix, an output matrix and an experience control quantity of each mobile robot, and a current moment position of a neighbor robot; determining a first parameter of each mobile robot according to existence of predetermined expectation position information of each mobile robot; determining a learning parameter of each mobile robot according to the first parameter of each mobile robot and a weighting adjacent matrix of the system with the multiple mobile robots; determining a learning gain matrix of each individual mobile robot according to the input matrix and the output matrix of each mobile robot; and controlling each mobile robot according to the current moment position, the first parameter, the learning parameter, the experience control quantity and the learning gain matrix of each mobile robot, and the current moment position of the neighbor robot. According to the invention, the control precision is improved through adding a learning process, so that each mobile robot can complete a task in a limited time.
Description
Technical field
The present invention relates to the Robot Control Technology field, particularly a kind of control method for coordinating of multiple-mobile-robot system.
Background technology
At present, multiple mobile robot's control method for coordinating has obtained application more and more widely in practical problems.This mainly is because increasing actual task more complicated all, and often single mobile robot is difficult to accomplish, and need accomplish through the cooperation between the multiple mobile robot.In addition; Through the cooperation between the multiple mobile robot; Can improve the efficient of robot system in operation process, and then change or robot system part when breaking down when working environment, the cooperative relationship that multiple-mobile-robot system still can have through itself is accomplished preset task.Yet the shortcoming that prior art exists is that control accuracy is not high, often can only make each mobile robot when the time is tending towards infinite, progressively accomplish a certain particular task.Especially, when relating to multiple mobile robot's tracking problem, often can only guarantee that each mobile robot reaches certain position or target, and can not guarantee that each mobile robot can fully follow the tracks of the desired trajectory or the target of any appointment.
Summary of the invention
The object of the invention is intended to solve at least one of above-mentioned technological deficiency.
For achieving the above object; The present invention proposes a kind of control method for coordinating of multiple-mobile-robot system; Said multiple-mobile-robot system comprises a plurality of individual mobile robots, said method comprising the steps of: A: each said individual mobile robot obtains the current time position of self current time position, experience controlled quentity controlled variable, input matrix, output matrix and neighbours robot; B: judge whether each said individual mobile robot has predetermined desired locations information, and confirm each said individual mobile robot's first parameter according to the result of said judgement; C: the learning parameter of confirming each said individual mobile robot according to the weighting adjacency matrix of each said individual mobile robot's first parameter and predetermined multiple-mobile-robot system; Wherein said learning parameter comprises first learning parameter and second learning parameter, and said first learning parameter and the non-negative and satisfied predetermined power rule condition of second learning parameter; And D: the learning gain matrix of confirming each said individual mobile robot according to each said individual mobile robot's input matrix and output matrix; And E: according to each said individual mobile robot of position control of the current time of each said individual mobile robot's self current time position, first parameter, learning parameter, experience controlled quentity controlled variable and learning gain matrix and said neighbours robot.
In one embodiment of the invention, said step B further comprises: if said individual mobile robot has said predetermined desired locations information, confirm that then said first parameter is 1; If said individual mobile robot does not have said predetermined desired locations information, confirm that then said first parameter is 0.
In one embodiment of the invention, said predetermined power rule condition is:
Wherein
Be first learning parameter between said individual mobile robot i and the individual mobile robot j, ψ
iBe second learning parameter of said individual mobile robot i, ω
iBe first parameter of said individual mobile robot i, a
IjElement for the weighting adjacency matrix of said multiple-mobile-robot system.
According to one embodiment of present invention, said step D further comprises: confirm each said individual mobile robot's learning gain matrix K according to each said individual mobile robot's input matrix and output matrix through following formula,
K=(CB)
T[CB(CB)
T]
-1
Wherein, B and C are respectively said individual mobile robot's input matrix and output matrix.
According to one embodiment of present invention; Said step e further comprises: E1: according to the current time position of self current time position of each said individual mobile robot, said first parameter, said learning parameter, said experience controlled quentity controlled variable, said learning gain matrix and said neighbours robot; Confirm each individual mobile robot's current controlled quentity controlled variable through following formula
Wherein, u
I, k(t) be the experience controlled quentity controlled variable of said individual mobile robot i, y
I, k(t+1) be that individual mobile robot i is at experience controlled quentity controlled variable u
I, k(t) position constantly of next under the control, y
J, k(t+1) be that the j of neighbours robot of individual mobile robot i is at experience controlled quentity controlled variable u
J, k(t) position constantly of next under the control, y
r(t+1) be said predetermined desired locations information, K is said learning gain matrix, u
I, k+1(t) be the current controlled quentity controlled variable of said individual mobile robot i; And
E2:, confirm next position constantly of said individual mobile robot through following formula according to said individual mobile robot's the current controlled quentity controlled variable and the position of said individual mobile robot's current time:
y
i，k+1(t+1)=C(I-q
-1A)
-1Bu
i,k+1(t)，
Wherein, y
I, k+1(t+1) be that said individual mobile robot i is at current controlled quentity controlled variable u
I, k+1(t) position in control next moment down, A is the state matrix of said individual mobile robot i, I is the cell matrix with the CBK same order, q
-1Be the drift operator of said individual mobile robot i, it satisfies q
-1u
I, k+1(t)=u
I, k+1(t-1).
Control method for coordinating according to the multiple-mobile-robot system of the embodiment of the invention; Through increasing learning process; Improve control accuracy; Make each mobile robot in finite time, to accomplish a certain particular task, guarantee that simultaneously the mobile robot can fully follow the tracks of the desired trajectory or the target of any appointment.
Aspect that the present invention adds and advantage part in the following description provide, and part will become obviously from the following description, or recognize through practice of the present invention.
Description of drawings
Above-mentioned and/or additional aspect of the present invention and advantage are from obviously with easily understanding becoming the description of embodiment below in conjunction with accompanying drawing, wherein:
Fig. 1 is the process flow diagram of control method for coordinating of the multiple-mobile-robot system of one embodiment of the invention;
Fig. 2 is the synoptic diagram of the multiple-mobile-robot system of one embodiment of the invention.
Embodiment
Describe embodiments of the invention below in detail, the example of said embodiment is shown in the drawings, and wherein identical from start to finish or similar label is represented identical or similar elements or the element with identical or similar functions.Be exemplary through the embodiment that is described with reference to the drawings below, only be used to explain the present invention, and can not be interpreted as limitation of the present invention.
In description of the invention, it will be appreciated that term " first ", " second " etc. only are used to describe purpose, and can not be interpreted as indication or hint relative importance.In description of the invention, need to prove that only if clear and definite regulation and qualification are arranged in addition, term " links to each other ", " connection " should be done broad understanding, for example, can be to be fixedly connected, also can be to removably connect, or connect integratedly; Can be mechanical connection, also can be to be electrically connected; Can be directly to link to each other, also can link to each other indirectly through intermediary.For those of ordinary skill in the art, can concrete condition understand above-mentioned term concrete implication in the present invention.In addition, in description of the invention, except as otherwise noted, the implication of " a plurality of " is two or more.
Describe and to be understood that in the process flow diagram or in this any process otherwise described or method; Expression comprises module, fragment or the part of code of the executable instruction of the step that one or more is used to realize specific logical function or process; And the scope of preferred implementation of the present invention comprises other realization; Wherein can be not according to order shown or that discuss; Comprise according to related function and to carry out function by the mode of basic while or by opposite order, this should be understood by the embodiments of the invention person of ordinary skill in the field.
Fig. 1 is the process flow diagram of control method for coordinating of the multiple-mobile-robot system of one embodiment of the invention.As shown in Figure 1, this method may further comprise the steps:
Step S101, each individual mobile robot obtain the current time position of self current time position, experience controlled quentity controlled variable, input matrix, output matrix and neighbours robot.
Wherein, individual mobile robot's neighbours robot refers to, and this mobile robot's of information flow direction every other mobile robot's set is arranged.Fig. 2 is the synoptic diagram of the multiple-mobile-robot system of one embodiment of the invention, and is as shown in Figure 2, and individual mobile robot 2 and 4 is individual mobile robot's 5 neighbours, and individual mobile robot 1,3 and 6 is not individual mobile robot's 5 neighbours.
Particularly, can be through being installed in the position that camera head on the individual mobile robot obtains the current time of self and neighbours robot thereof.In addition, all by the structure and parameter decision of robot self, in the present invention, the input matrix of each robot, output matrix are identical respectively for input matrix, output matrix.
Step S102 judges whether each individual mobile robot has predetermined desired locations information, and confirms first parameter according to the result who judges.
Particularly, if individual mobile robot has predetermined desired locations information, confirm that then first parameter is 1.If individual mobile robot does not have predetermined desired locations information, confirm that then first parameter is 0.
Step S103; Confirm each individual mobile robot's learning parameter according to the weighting adjacency matrix of each individual mobile robot's first parameter and multiple-mobile-robot system; Wherein learning parameter comprises first learning parameter and second learning parameter, and first learning parameter and the non-negative and satisfied predetermined power rule condition of second learning parameter.
In one embodiment of the invention, predetermined power rule condition is:
Wherein,
Be first learning parameter between individual mobile robot i and the individual mobile robot j, ψ
iBe second learning parameter of individual mobile robot i, ω
iBe first parameter of individual mobile robot i, a
IjBe the element of the weighting adjacency matrix of multiple-mobile-robot system, expression mobile robot i obtains situation with respect to the information of mobile robot j, for example based on the mobile robot 1 of vision preceding; Based on the mobile robot 2 of vision after; 2 is visible 1, and 1 is invisible 2, then a
12=0.
Step S104, the learning gain matrix of confirming each individual mobile robot according to each individual mobile robot's input matrix and output matrix.
Particularly, can obtain each individual mobile robot's learning gain matrix K through following formula,
K=(CB)
T[CB(CB)
T]
-1
Wherein, B and C are respectively individual mobile robot's input matrix and output matrix.
Should be understood that like above-mentioned step S101 saidly, because each individual mobile robot's B is identical with C, so for each the individual mobile robot in the multiple-mobile-robot system, the learning gain matrix K all is identical.
Step S105 is according to each individual mobile robot of current time position control of each individual mobile robot's self current time position, first parameter, learning parameter, learning gain matrix, experience controlled quentity controlled variable and neighbours robot.
Particularly; At first; According to the current time position of each individual mobile robot's self current time position, first parameter, learning parameter, experience controlled quentity controlled variable and learning gain matrix and neighbours robot, confirm each individual mobile robot's current controlled quentity controlled variable through following formula:
Wherein, u
I, k(t) be the experience controlled quentity controlled variable of individual mobile robot i, y
I, k(t+1) be that individual mobile robot i is at experience controlled quentity controlled variable u
I, k(t) position constantly of next under the control, y
J, k(t+1) be that the j of neighbours robot of individual mobile robot i is at experience controlled quentity controlled variable u
J, k(t) position constantly of next under the control, y
r(t+1) be predetermined desired locations information,
Be first learning parameter between individual i of robot and the individual j of robot, a
IjBe the element of the weighting adjacency matrix of multiple-mobile-robot system, K is the learning gain matrix, u
I, k+1(t) be the current controlled quentity controlled variable of individual mobile robot i.
Then, according to above-mentioned individual mobile robot's the current controlled quentity controlled variable and the position of individual mobile robot's current time, confirm next position constantly of individual mobile robot through following formula:
y
i,k+1(t+1)=C(I-q
-1A)
-1Bu
i，k+1(t)，
Wherein, y
I, k+1(t+1) be that individual mobile robot i is at current controlled quentity controlled variable u
I, k+1(t) position in control next moment down, A is that (likewise, state matrix is also by robot construction and parameter determining for the state matrix of individual mobile robot i; In the present invention; Each mobile robot's state matrix is all identical), I is the same order cell matrix of CBK, q
-1Be the drift operator of individual mobile robot i, it satisfies q
-1u
I, k+1(t)=u
I, k+1(t-1).
Control method for coordinating according to the multiple-mobile-robot system of the embodiment of the invention; Through increasing learning process, improve control accuracy, make each mobile robot can in finite time, accomplish a certain particular task; Guarantee that simultaneously the mobile robot can fully follow the tracks of the desired trajectory or the target of any appointment; In commercial production, be significant, for example, the multiple-mobile-robot system that uses collective to form into columns is realized the carrying of large-sized object; Each mobile robot shares part weight at work, finishes the work through coordinating control.
Although illustrated and described embodiments of the invention; For those of ordinary skill in the art; Be appreciated that under the situation that does not break away from principle of the present invention and spirit and can carry out multiple variation, modification, replacement and modification that scope of the present invention is accompanying claims and be equal to and limit to these embodiment.
Claims (5)
1. the control method for coordinating of a multiple-mobile-robot system is characterized in that, said multiple-mobile-robot system comprises a plurality of individual mobile robots, said method comprising the steps of:
A: each said individual mobile robot obtains the current time position of self current time position, experience controlled quentity controlled variable, input matrix, output matrix and neighbours robot;
B: judge whether each said individual mobile robot has predetermined desired locations information, and confirm each said individual mobile robot's first parameter according to judged result;
C: the learning parameter of confirming each said individual mobile robot according to the weighting adjacency matrix of each said individual mobile robot's first parameter and multiple-mobile-robot system; Wherein said learning parameter comprises first learning parameter and second learning parameter, and said first learning parameter and the non-negative and satisfied predetermined power rule condition of second learning parameter;
D: the learning gain matrix of confirming each said individual mobile robot according to each said individual mobile robot's input matrix and output matrix; And
E: according to each said individual mobile robot of current time position control of self current time position of each said individual mobile robot, first parameter, learning parameter, experience controlled quentity controlled variable, output matrix, learning gain matrix and said neighbours robot.
2. the control method for coordinating of multiple-mobile-robot system according to claim 1 is characterized in that, said step B further comprises:
If said individual mobile robot has said predetermined desired locations information, confirm that then said first parameter is 1;
If said individual mobile robot does not have said predetermined desired locations information, confirm that then said first parameter is 0.
3. the control method for coordinating of multiple-mobile-robot system according to claim 1 is characterized in that, said predetermined power rule condition is:
Wherein,
Be first learning parameter between individual mobile robot i and the individual mobile robot j, ψ
iBe second learning parameter of said individual mobile robot i, ω
iBe first parameter of said individual mobile robot i, a
IjElement for the weighting adjacency matrix of said multiple-mobile-robot system.
4. according to the control method for coordinating of each described multiple-mobile-robot system in the claim 1 to 3, it is characterized in that said step D further comprises:
Confirm each said individual mobile robot's learning gain matrix K according to each said individual mobile robot's input matrix and output matrix through following formula,
K=(CB)
T[CB(CB)
T]
-1
Wherein, B and C are respectively said individual mobile robot's input matrix and output matrix.
5. according to the control method for coordinating of each described multiple-mobile-robot system in the claim 1 to 4, it is characterized in that said step e further comprises:
E1:, confirm each individual mobile robot's current controlled quentity controlled variable through following formula according to the current time position of self current time position of each said individual mobile robot, said first parameter, said learning parameter, said experience controlled quentity controlled variable, said learning gain matrix and said neighbours robot:
Wherein, u
I, k(t) be the experience controlled quentity controlled variable of said individual mobile robot i, y
I, k(t+1) be that individual mobile robot i is at experience controlled quentity controlled variable u
I, k(t) position constantly of next under the control, y
J, k(t+1) be that the j of neighbours robot of individual mobile robot i is at experience controlled quentity controlled variable u
J, k(t) position constantly of next under the control, y
r(t+1) be said predetermined desired locations information,
Be first learning parameter between individual i of robot and the individual j of robot, a
IjBe the element of the weighting adjacency matrix of said multiple-mobile-robot system, K is said learning gain matrix, u
I, k+1(t) be the current controlled quentity controlled variable of said individual mobile robot i; And
E2:, confirm next position constantly of said individual mobile robot through following formula according to said individual mobile robot's the current controlled quentity controlled variable and the position of said individual mobile robot's current time:
y
i，k+1(t+1)=C(I-q
-1A)
-1Bu
i,k+1(t)，
Wherein, y
I, k+1(t+1) be that said individual mobile robot i is at current controlled quentity controlled variable u
I, k+1(t) position constantly of next under the control, A is the state matrix of said individual mobile robot i, I is the cell matrix of CBK same order, q
-1Be the drift operator of said individual mobile robot i, it satisfies q
-1u
I, k+1(t)=u
I, k+1(t-1).
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| CN103914069A (en) * | 2014-03-14 | 2014-07-09 | 上海交通大学 | Multi-robot cooperation locating method capable of allowing cognitive errors |
| CN103970020A (en) * | 2014-05-21 | 2014-08-06 | 北京航空航天大学 | Mobile robot system and coordination control method of mobile robot system in hybrid interaction environment |
| CN104679002A (en) * | 2015-01-28 | 2015-06-03 | 北京航空航天大学 | Mobile robot system polluted by noises and coordination and control method of mobile robot system |
| CN108255168A (en) * | 2016-12-29 | 2018-07-06 | 北京航空航天大学 | Control method for coordinating of more vehicle networks in the case where switching changing environment |
| CN108255169A (en) * | 2016-12-29 | 2018-07-06 | 北京航空航天大学 | The control method for coordinating of vehicle and more vehicle networks |
| CN109799811A (en) * | 2017-11-17 | 2019-05-24 | 北京航空航天大学 | A kind of dynamic distributed control method of pleiotaxy robot system |
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| CN103914069A (en) * | 2014-03-14 | 2014-07-09 | 上海交通大学 | Multi-robot cooperation locating method capable of allowing cognitive errors |
| CN103970020A (en) * | 2014-05-21 | 2014-08-06 | 北京航空航天大学 | Mobile robot system and coordination control method of mobile robot system in hybrid interaction environment |
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| CN108255169B (en) * | 2016-12-29 | 2021-05-21 | 北京航空航天大学 | Vehicle and coordination control method of multiple vehicle networks |
| CN108255168B (en) * | 2016-12-29 | 2021-05-21 | 北京航空航天大学 | Coordination control method of multi-vehicle network under switching change environment |
| CN109799811A (en) * | 2017-11-17 | 2019-05-24 | 北京航空航天大学 | A kind of dynamic distributed control method of pleiotaxy robot system |
| WO2022032443A1 (en) * | 2020-08-10 | 2022-02-17 | 深圳技术大学 | Transport method for multi-intelligent agent formation, system, and computer-readable storage medium |
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