CN110262523A - A kind of automatic obstacle avoiding of distribution Group Robots is swarmed control method - Google Patents
A kind of automatic obstacle avoiding of distribution Group Robots is swarmed control method Download PDFInfo
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
- G05D1/0289—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling with means for avoiding collisions between vehicles
Abstract
A kind of automatic obstacle avoiding of distribution Group Robots is swarmed control method, first initiation parameter, then the position and speed of " Vector triangle " computational intelligence robot α corresponding Virtual Intelligent robot β on current time barrier edge according to vector；When intelligent robot α is close to barrier, the position operator and speed operator between intelligent robot α and Virtual Intelligent robot β are designed, realizes the automatic obstacle avoiding of intelligent robot α；Meanwhile position operator and speed operator between intelligent robot α and its neighbours' intelligent robot α are designed, realize the separation and polymerization between them；In addition, position operator and speed operator between design intelligent robot α and mobile target robot, realize the tracking to mobile target robot.The present invention is by identification of the swarm intelligence robot to barrier, in conjunction with three sub- control protocols, realizes that the automatic obstacle avoiding of distributed Group Robots is swarmed control, enables Group Robots in obstacle environment to cooperate with the tracking task for completing movement target.
Description
Technical field
The present invention relates to intelligent robot technology fields, relate in particular to a kind of independently keeping away for distributed Group Robots
Hinder control method of swarming.
Background technique
In recent years, the research of population system Collaborative Control is received from biology, computer science, mathematics, artificial intelligence
And the numerous researchers of different fields such as control engineering are more and more paid close attention to, it has also become research hotspot.Group Robots system
System is to be opened by the intelligent robot largely with Dynamic Evolution Characteristics by a kind of complexity that local sensing and interaction are formed
The distributed system put, generally by local message is interactive and the design of controller is realized from macroscopic aspect it is complicated orderly
Agreement.The exploratory development Partial global planning mechanism institute mutual as intelligent robot in the robot system of object using group
No matter the global behavior of presentation is transferred to biological or social groups' behavior the cognition and comprehension, or to Collaborative Control technology is accelerated
The process of practical engineering application all has important theoretical significance and value.The Collaborative Control of large-scale groups robot exists
The key areas of the national economic development such as military, industrial and civil is all with a wide range of applications.
Control technology of swarming is one of the important branch of large-scale groups robot Collaborative Control technical research.It swarms control
The thought of technology is derived from Boid model (the A distributed behavioral model.Computer of Reynolds building
Graphics (ACM), 1987), which follows three simple rules: separation, polymerization and speeds match.R.Olfati-
Saber Preliminary design intelligent group system distribution is swarmed control algolithm (Flocking for multi-agent dynamic
Systems:algorithms and theory.IEEE Transactions on Automatic Control, 2006), right
In different spaces environment, no leader is given, there is leader and there are three kinds of control algolithms of swarming of barrier.Q.Zhang and
P.Li devises adaptive controller and corresponding more new law (Adaptive flocking of non-linear multi-
agents systems with uncertain parameters.IET Control Theroy and Applications,
2014) it, can be realized the control of adaptively swarming of Nonlinear Intelligent population system, while identifying uncertain parameter.H.Zhao,
H.Liu, Y.Leung and X.Chu have studied control problem of swarming (the Self-adaptive collective of cluster robot
Motion of swarm robots.IEEE Transactions on Automation and Engineering, 2018),
The adaptive aggregation motion algorithm proposed enables to one group of preset track of robot tracking orderly in 2D and 3d space.
However, about dividing in the case of in obstacle environment in most of research work of the behavior of swarming of large-scale groups robot
That analyses is less.In practice, cognitive disorders object when Group Robots are performed in unison with task in complex environment, automatic obstacle avoiding are extremely heavy
It wants, such as: the Collaborative Control of unmanned underwater submarine/unmanned spacecraft, multirobot is raw in ruins environment caused by earthquake disaster
Order search and rescue and the rescue etc. of body.For the task execution of environment non-ideal for multi-robots system, essence is group's machine
The automatic obstacle avoiding of people is swarmed control problem, and there are two notable features for problem tool, first is that the distributed control that intelligent robot is swarmed
System, second is that the automatic obstacle avoiding of intelligent robot.Therefore, it swarms control problem, closes to solve the automatic obstacle avoiding of Group Robots
Key be to focus on solving each intelligent robot how automatic obstacle avoiding the problem of.
Summary of the invention
It swarms control method the object of the present invention is to provide a kind of automatic obstacle avoiding of distributed Group Robots, it is effectively autonomous
Mobile target robot is tracked in avoidance and collaboration.
The present invention is realized by technical solution as described below.
A kind of automatic obstacle avoiding of distributed Group Robots of the present invention is swarmed control method, it is characterised in that: group
The robot autonomous avoidance of body is swarmed in control, proposes " Vector triangle " the computational intelligence robot α according to vector when current
Carve the position and speed of corresponding Virtual Intelligent robot β (virtual intelligent robot) on barrier edge；Work as intelligence machine
When people α is close to barrier, the position operator between intelligent robot α and Virtual Intelligent robot β and (the sub- control of speed operator are designed
Agreement I processed), realize the automatic obstacle avoiding of intelligent robot α；Meanwhile design intelligent robot α and its neighbours' intelligent robot α it
Between position operator and speed operator (sub- control protocol II), realize the separation and polymerization between them；In addition, design intelligent machine
Position operator and speed operator (sub- control protocol III) between device people α and mobile target robot are realized to mobile target machine
The tracking of device people.
The control method specifically, a kind of automatic obstacle avoiding of distributed Group Robots of the present invention is swarmed, including
Following steps:
(1) initiation parameter: the position of barrier and radius, the safe distance between intelligent robot α and barrier, intelligence
The energy total number of robot α and the perception radius of intelligent robot α, the initial bit of intelligent robot α and mobile target robot
It sets and speed；
(2) corresponding on current time barrier edge according to " Vector triangle " the computational intelligence robot α of vector
The position and speed of intelligent robot β (virtual intelligent robot)；
(3) when intelligent robot α is close to barrier, the position between intelligent robot α and Virtual Intelligent robot β is designed
Operator and speed operator (sub- control protocol I) are set, realizes the automatic obstacle avoiding of intelligent robot α；
(4) simultaneously, the position operator and speed operator (son between intelligent robot α and its neighbours' intelligent robot α are designed
Control protocol II), realize the separation and polymerization between them；
(5) position operator and speed operator (sub- control protocol between intelligent robot α and mobile target robot are designed
III) tracking to mobile target robot, is realized；
(6) three sub- control protocols of intelligent robot α, swarm intelligence robot cut-through object are combined, collaboration is completed
The tracking task of mobile target robot.
The corresponding intelligent robot β on current time barrier edge of intelligent robot α described in step (2) of the present invention
The determination of position and speed:
(1) pass through the norm of matrix theory | | pi-pob,h| | determine i-th of intelligent robot α and barrier OhSpacing,
Middle pi indicates the position of i-th of intelligent body robot α, pob,hIndicate barrier Oh, the position of h ∈ { 1,2 ... m }；
(2) if | | pi-pob,h| | < (ds+rob,h), dsIt is i-th of intelligent robot α and barrier OhBetween safety away from
From rob,hIndicate barrier OhRadius, then barrier OhThere are Virtual Intelligent robot β on edge, it is located at i-th of intelligence
Robot α and barrier OhAt the line of centres and its edge crossing point, the positive direction one of the tangent line in directional velocity and the crosspoint
It causes；
(3) position of Virtual Intelligent robot β is calculated according to " Vector triangle " of vectorAnd speed WhereinRespectively
Indicate i-th of intelligent body robot α and barrier OhTo the position vector of coordinate origin, rob,hIndicate barrier OhRadius, this
In
Position operator and speed described in step (3) of the present invention between intelligent robot α and Virtual Intelligent robot β are calculated
Son, the i.e. design of intelligent robot α control protocol I:
(1) kinetics equation of mobile target robot and intelligent robot α are respectively Wherein pr,vr,urRespectively move position, speed and the control input of target robot
Amount, pi,vi,uiRespectively indicate position, speed and the control input quantity of i-th of intelligent robot α；
(2) i-th of intelligent robot α control protocol I are designed as
WhereinIt is the set of neighbours' intelligent robot β of i-th of intelligent robot α,It is force function,
c11> 0, c12> 0.
Position operator and speed between intelligent robot α described in step (4) of the present invention and its neighbours' intelligent robot α
Operator, the i.e. design of intelligent robot α control protocol II:
I-th of intelligent robot α control protocol II is designed as
WhereinIt is the set of neighbours' intelligent robot α of i-th of intelligent robot α,It is force function,
c21> 0, c22> 0.
Three sub- control protocols of combination intelligent robot α described in step (5) of the present invention, i-th of intelligent robot α control
The design of input quantity processed:
(1) position operator and speed operator between intelligent robot α and mobile target robot, i.e. intelligent robot α
Sub- control protocol III is designed asWherein c31> 0, c32> 0；
(2) three sub- control protocols of intelligent robot α are combined, i-th of intelligent robot α control input quantity is
Advantages of the present invention and technical effect:
(1) present invention combines complex network with the control of swarming of Group Robots, the position of intelligent robot and phase
Communication connection relationship between mutually is clearly described by network topological diagram.
(2) present invention proposes that " Vector triangle " according to vector determines intelligent robot α on current time barrier side
Corresponding Virtual Intelligent robot β (virtual intelligent robot) on edge, be conducive to calculate Virtual Intelligent robot β position and
Speed.
(3) when intelligent robot α is close to barrier, the sub- control protocol I of designed intelligent robot α can be realized intelligence
The automatic obstacle avoiding of robot α.
(4) simultaneously, the sub- control protocol II and sub- control protocol III of designed intelligent robot α is able to realize intelligence
Separation and polymerization between robot α and the tracking to mobile target robot.
(5) present invention is by identification of the swarm intelligence robot to barrier, in conjunction with three son controls of intelligent robot α
Agreement, as control input quantity, and then realize that the automatic obstacle avoiding of distributed Group Robots is swarmed control, so that obstacle environment
Middle Group Robots can cooperate with the tracking task for completing mobile target.
Detailed description of the invention
Fig. 1 is the vector schematic diagram present invention determine that barrier Edge intelligence robot β, r in figureob,hIndicate barrier Oh
Radius, r indicate intelligent robot α the perception radius.
Fig. 2 is swarm intelligence robot initial distribution map of the present invention, and circle (☉) indicates intelligent robot α in figure
(agent), five-pointed star (★) indicates mobile target robot (target), and solid great circle (●) indicates barrier.
The motion state diagram of swarm intelligence robot when Fig. 3 is t=3s.
The motion state diagram of swarm intelligence robot when Fig. 4 is t=5s.
The motion state diagram of swarm intelligence robot when Fig. 5 is t=8s.
The motion state diagram of swarm intelligence robot when Fig. 6 is t=10s.
The motion state diagram of swarm intelligence robot when Fig. 7 is t=20s.
The end-state figure of swarm intelligence robot when Fig. 8 is t=80s.
The enlarged drawing of the end-state of swarm intelligence robot when Fig. 9 is t=80s.
Figure 10 is that the automatic obstacle avoiding of Group Robots is swarmed control method flow chart.
Specific embodiment
With reference to the accompanying drawing, the present invention is explained in detail.
In 2- dimension space, consideration has b round barrier, and multi-robots system is moved by n intelligent robot and 1
Moving-target robot is constituted.All intelligent robots and target robot are considered as particle in the system, ignore their shape ruler
It is very little.Here, pi,vi∈R2The position and speed of intelligent robot i is respectively indicated, wherein i ∈ { 1,2 ..., n }；pr,vrRespectively
The position and speed of mobile target robot；ui,urRespectively indicate the control input of intelligent robot i and mobile target robot
Amount；pob,hIndicate barrier Oh, the position of h ∈ { 1,2 ... m }；dsIt is i-th of intelligent robot α and barrier OhBetween peace
Full distance, rob,hIndicate barrier OhRadius；D is the desired distance between intelligent robot α；R indicates i-th of intelligence machine
The perception radius of people α, then its neighbours' intelligent robot α set can be with is defined as:
In multi-robots system, during each intelligent robot α and other intelligent robot coordinated movements of various economic factors, have
Control independent input.Shown in the continuous equation of motion such as formula (1) of intelligent robot α:
In addition, shown in the continuous kinetics equation such as formula (2) of mobile target robot:
As shown in Fig. 2, the initial position of swarm intelligence robot meets Gaussian Profile, initial communication topological diagram is not to be connected to
's.Initial parameter setting: n=150, m=4, d=ds=8, r=8.4, pr=[160,2], vr=1, barrier parameter matrix is
Second step is described below, " Vector triangle " the computational intelligence robot α according to vector is in current time barrier
The position and speed specific implementation process of corresponding Virtual Intelligent robot β (virtual intelligent robot) on edge.
Pass through the norm of matrix theory | | pi-pob,h| | determine i-th of intelligent robot α and barrier OhSpacing.If | |
pi-pob,h| | < (ds+rob,h), then barrier Oh, there are Virtual Intelligent robot β on the edge h ∈ { 1,2 ... m }, it is located at i-th
A intelligent robot α and barrier OhAt the line of centres and its edge crossing point, the tangent line in directional velocity and the crosspoint is just
Direction is consistent, as shown in Figure 1.
The position of Virtual Intelligent robot β is calculated according to " Vector triangle " of vectorAnd speed
Wherein Respectively indicate i-th of intelligent body robot α and barrier OhIt arrives
The position vector of coordinate origin, rob,hIndicate barrier OhRadius, here
Second step is described below, when intelligent robot α is close to barrier, intelligent robot α and Virtual Intelligent robot β
Between position operator and speed operator, i.e. the design of intelligent robot α control protocol I:
I-th of intelligent robot α control protocol I is designed as
WhereinIt is neighbours' Virtual Intelligent robot β of i-th of intelligent robot α
Set, c11> 0, c12> 0,It is force function, i.e.,
WhereinBoth constant parameters.dβIt is ψ (x) global minimum
X=dsσ-norm.
Here, shown in being described as follows of common mathematical function:
σ-norm of vector x
Impulse function
Non-uniform S type function
WhereinAndEnsureAnd in formula (4)aijIt is in swarm intelligence robot weighted adjacent matrix A
Element.
Third step is described below, the position operator and speed between intelligent robot α and its neighbours' intelligent robot α are calculated
Son, i.e. intelligent robot α control protocol II are designed as
WhereinIt is the set of neighbours' intelligent robot α of i-th of intelligent robot α, c21> 0, c22> 0,It is
Force function, i.e.,
Wherein pα=| | p | |σ,dα=| | pj-pi||σ,Both constant parameters.dαIt is ψ (x) global minima
σ-norm of value x=d, in formula (6)
The 4th step is described below, in conjunction with three sub- control protocols of intelligent robot α, i-th of intelligent robot α control is defeated
Enter the design of amount:
Position operator and speed operator between intelligent robot α and mobile target robot, i.e. intelligent robot α control
Agreement III processed is designed asWherein c31> 0, c32> 0；
In conjunction with three sub- control protocols of intelligent robot α, i-th of intelligent robot α control input quantity isI.e. are as follows:
Wherein c21< c31< c11,
Intelligent robot α can identify the obstacle in complex environment under the action of control protocol (8) controls input quantity
Object, and then realize that the automatic obstacle avoiding of distributed Group Robots is swarmed control, enables Group Robots in obstacle environment
The tracking task of mobile target is completed in collaboration.
From Fig. 3-Fig. 8, obstacle environment, we are it can clearly be observed that the group that 150 intelligent robot α are formed
Automatic obstacle avoiding tracks the substantially process of mobile target robot.The rambling swarm intelligence robot α of initial distribution, passes through office
The reciprocation of portion's information is artificially oriented to gradually with moving target machine around encountered barrier movement.When group's machine
When people α run duration t=3s, by Fig. 3 observation it is found that some intelligent robot α are obviously mobile around first barrier.With
The passage of run duration, when in motion between t=5s when, observed by Fig. 4, discovery part intelligent robot α bypassed first
Barrier, second barrier of part intelligent robot alpha wrap are mobile.As entire Group Robots run duration t=8s and t=
When 10s, as shown in Figure 5 and Figure 6, some intelligent robot α are moved around second barrier towards mobile target robot.When
When time t=15s, swarm intelligence robot α substantially by-passes all barriers towards mobile target robot movement, such as Fig. 7 institute
Show.Fig. 8 clearly demonstrates that the automatic obstacle avoiding of Group Robots is swarmed and has been formed, and will have been moved by 150 intelligent robot α
Moving-target robot surrounds, and the effect of amplification is as shown in Figure 9.
The phenomenon that observing from these operation results of Fig. 3-Fig. 9, further demonstrates that swarming for proposed automatic obstacle avoiding
The Group Robots that control method enables to scale expansible form swarm tracking and the mobile target robot of encirclement.In this hair
Various substitutions, changes and modifications are able to carry out on the basis of bright design, these replacements, change and modification should not be excluded in invention
Except protection scope.
Claims (5)
- The control method 1. a kind of automatic obstacle avoiding of distribution Group Robots is swarmed, it is characterized in that including the following steps:(1) initiation parameter: the position of barrier and radius, the safe distance between intelligent robot α and barrier, intelligent machine The initial position of the total number of device people α and the perception radius of intelligent robot α, intelligent robot α and mobile target robot and Speed；(2) corresponding virtual on current time barrier edge according to " Vector triangle " the computational intelligence robot α of vector The position and speed of intelligent robot β；(3) when intelligent robot α is close to barrier, the position designed between intelligent robot α and Virtual Intelligent robot β is calculated Son and speed operator: sub- control protocol I realizes the automatic obstacle avoiding of intelligent robot α；(4) position operator and speed operator between intelligent robot α and its neighbours' intelligent robot α: sub- control protocol are designed II, realize the separation and polymerization between them；(5) position operator and speed operator between intelligent robot α and mobile target robot: sub- control protocol III are designed, Realize the tracking to mobile target robot；(6) three sub- control protocols of intelligent robot α, swarm intelligence robot cut-through object are combined, movement is completed in collaboration The tracking task of target robot.
- The control method 2. a kind of automatic obstacle avoiding of distributed Group Robots according to claim 1 is swarmed, it is characterized in that The corresponding Virtual Intelligent robot β position and speed on current time barrier edge of intelligent robot α described in step (2) Determination it is as follows:(1) pass through the norm of matrix theory | | pi-pob,h| | determine i-th of intelligent robot α and barrier OhSpacing, wherein piTable Show the position of i-th of intelligent body robot α, pob,hIndicate barrier Oh, the position of h ∈ { 1,2 ... m }；(2) if | | pi-pob,h| | < (ds+rob,h), dsIt is i-th of intelligent robot α and barrier OhBetween safe distance, rob,hIndicate barrier OhRadius, then barrier OhThere are Virtual Intelligent robot β on edge, it is located at i-th of intelligence machine People α and barrier OhAt the line of centres and its edge crossing point, directional velocity is consistent with the positive direction of the tangent line in the crosspoint；(3) position of Virtual Intelligent robot β is calculated according to " Vector triangle " of vectorAnd speed WhereinRespectively Indicate i-th of intelligent body robot α and barrier OhTo the position vector of coordinate origin, rob,hIndicate barrier OhRadius, this In
- The control method 3. a kind of automatic obstacle avoiding of distributed Group Robots according to claim 1 is swarmed, it is characterized in that Position operator and speed operator between intelligent robot α described in step (3) and Virtual Intelligent robot β: sub- control protocol I Design:(1) kinetics equation of mobile target robot and intelligent robot α are respectively Wherein pr,vr,urRespectively move position, speed and the control input of target robot Amount, pi,vi,uiRespectively indicate position, speed and the control input quantity of i-th of intelligent robot α；(2) i-th of intelligent robot α control protocol I are designed asWhereinIt is the set of neighbours' Virtual Intelligent robot β of i-th of intelligent robot α,It is force function, c11 > 0, c12> 0.
- The control method 4. a kind of automatic obstacle avoiding of distributed Group Robots according to claim 1 is swarmed, it is characterized in that Position operator and speed operator between intelligent robot α described in step (4) and its neighbours' intelligent robot α, i.e. intelligent machine The design of device people α control protocol II:I-th of intelligent robot α control protocol II is designed asWhereinIt is the set of neighbours' intelligent robot α of i-th of intelligent robot α,It is force function, c21> 0, c22> 0.
- The control method 5. a kind of automatic obstacle avoiding of distributed Group Robots according to claim 1 is swarmed, it is characterized in that Three sub- control protocols of combination intelligent robot α described in step (5), i-th of intelligent robot α control setting for input quantity Meter:(1) position operator and speed operator between intelligent robot α and mobile target robot, i.e. intelligent robot α control Agreement III processed is designed asWherein c31> 0, c32> 0；(2) three sub- control protocols of intelligent robot α are combined, i-th of intelligent robot α control input quantity is
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112527014A (en) * | 2020-12-02 | 2021-03-19 | 电子科技大学 | Unmanned aerial vehicle cluster grazing method based on packing algorithm |
| CN113033756A (en) * | 2021-03-25 | 2021-06-25 | 重庆大学 | Multi-agent control method based on target-oriented aggregation strategy |
| CN113110524A (en) * | 2021-05-28 | 2021-07-13 | 北京理工大学 | Multi-robot self-organizing cooperation and clustering method |
| CN113146624A (en) * | 2021-03-25 | 2021-07-23 | 重庆大学 | Multi-agent control method based on maximum angle aggregation strategy |
| CN113485340A (en) * | 2021-07-12 | 2021-10-08 | 汕头大学 | Distributed enclosure control method and system for group robots |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101901012A (en) * | 2010-03-19 | 2010-12-01 | 华东交通大学 | Distributed type multi-robot synchronous swarming control method |
| CN104185310A (en) * | 2013-05-27 | 2014-12-03 | 南京邮电大学 | Mobile sensor target tracking method based on flocking control |
| WO2016079778A1 (en) * | 2014-11-17 | 2016-05-26 | 株式会社日立製作所 | Traffic flow control system and traffic flow control method |
| CN105867415A (en) * | 2016-04-20 | 2016-08-17 | 沈阳航空航天大学 | Cooperative control policy based on secure communication of multiple unmanned aerial vehicles |
| CN107179777A (en) * | 2017-06-03 | 2017-09-19 | 复旦大学 | Multiple agent cluster Synergistic method and multiple no-manned plane cluster cooperative system |
| CN107367944A (en) * | 2017-09-04 | 2017-11-21 | 贾永楠 | A kind of cluster control method towards multi-agent system |
| CN108958262A (en) * | 2018-08-02 | 2018-12-07 | 华东交通大学 | A kind of part of distributed robots is swarmed control method |
-
2019
- 2019-07-31 CN CN201910701050.5A patent/CN110262523B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101901012A (en) * | 2010-03-19 | 2010-12-01 | 华东交通大学 | Distributed type multi-robot synchronous swarming control method |
| CN104185310A (en) * | 2013-05-27 | 2014-12-03 | 南京邮电大学 | Mobile sensor target tracking method based on flocking control |
| WO2016079778A1 (en) * | 2014-11-17 | 2016-05-26 | 株式会社日立製作所 | Traffic flow control system and traffic flow control method |
| CN105867415A (en) * | 2016-04-20 | 2016-08-17 | 沈阳航空航天大学 | Cooperative control policy based on secure communication of multiple unmanned aerial vehicles |
| CN107179777A (en) * | 2017-06-03 | 2017-09-19 | 复旦大学 | Multiple agent cluster Synergistic method and multiple no-manned plane cluster cooperative system |
| CN107367944A (en) * | 2017-09-04 | 2017-11-21 | 贾永楠 | A kind of cluster control method towards multi-agent system |
| CN108958262A (en) * | 2018-08-02 | 2018-12-07 | 华东交通大学 | A kind of part of distributed robots is swarmed control method |
Non-Patent Citations (6)
| Title |
|---|
| DAI BIXIA 等: "《Flocking of Multi-Agents with Arbitrary Shape Obstacle》", 《PROCEEDINGS OF THE 33RD CHINESE CONTROL CONFERENCE》 * |
| HUIQIN PEI 等: "《A local flocking algorithm of multi-agent dynamic systems》", 《INTERNATIONAL JOURNAL OF CONTROL》 * |
| XIAOQING LU 等: "《Flocking in multi-agent systems with active virtual leader and time-varying delays coupling》", 《COMMUN NONLINEAR SCI NUMER SIMULAT》 * |
| 李春光 等: "《二阶多智能体系统量化蜂拥控制》", 《控制与决策》 * |
| 苏厚胜: "《多智能体蜂拥控制问题研究》", 《中国优秀博硕士学位论文全文数据库(博士) 信息科技辑》 * |
| 陈世明 等: "《邻域交互结构优化的多智能体快速蜂拥控制算法》", 《自动化学报》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112527014A (en) * | 2020-12-02 | 2021-03-19 | 电子科技大学 | Unmanned aerial vehicle cluster grazing method based on packing algorithm |
| CN112527014B (en) * | 2020-12-02 | 2022-05-17 | 电子科技大学 | Unmanned aerial vehicle cluster grazing method based on packing algorithm |
| CN113033756A (en) * | 2021-03-25 | 2021-06-25 | 重庆大学 | Multi-agent control method based on target-oriented aggregation strategy |
| CN113146624A (en) * | 2021-03-25 | 2021-07-23 | 重庆大学 | Multi-agent control method based on maximum angle aggregation strategy |
| CN113146624B (en) * | 2021-03-25 | 2022-04-29 | 重庆大学 | Multi-agent control method based on maximum angle aggregation strategy |
| CN113033756B (en) * | 2021-03-25 | 2022-09-16 | 重庆大学 | Multi-agent control method based on target-oriented aggregation strategy |
| CN113110524A (en) * | 2021-05-28 | 2021-07-13 | 北京理工大学 | Multi-robot self-organizing cooperation and clustering method |
| CN113485340A (en) * | 2021-07-12 | 2021-10-08 | 汕头大学 | Distributed enclosure control method and system for group robots |
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