CN105426986B - High-reliability Control method and system in multi-robot system - Google Patents
High-reliability Control method and system in multi-robot system Download PDFInfo
- Publication number
- CN105426986B CN105426986B CN201510729291.2A CN201510729291A CN105426986B CN 105426986 B CN105426986 B CN 105426986B CN 201510729291 A CN201510729291 A CN 201510729291A CN 105426986 B CN105426986 B CN 105426986B
- Authority
- CN
- China
- Prior art keywords
- robot
- working
- machine people
- standby machine
- value
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 63
- 238000013461 design Methods 0.000 claims abstract description 39
- 230000003862 health status Effects 0.000 claims abstract description 25
- 238000004519 manufacturing process Methods 0.000 claims abstract description 16
- 238000011084 recovery Methods 0.000 claims abstract description 15
- 238000012545 processing Methods 0.000 claims abstract description 8
- 238000004891 communication Methods 0.000 claims description 27
- 230000007704 transition Effects 0.000 claims description 24
- 239000011159 matrix material Substances 0.000 claims description 15
- 230000036541 health Effects 0.000 claims description 7
- 230000015556 catabolic process Effects 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 6
- 238000006731 degradation reaction Methods 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 4
- 239000012141 concentrate Substances 0.000 claims description 3
- 238000003745 diagnosis Methods 0.000 claims description 3
- 230000004888 barrier function Effects 0.000 claims description 2
- 230000008569 process Effects 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 7
- 239000000523 sample Substances 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000009826 distribution Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000009776 industrial production Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 206010033799 Paralysis Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005553 drilling Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Educational Administration (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Manipulator (AREA)
Abstract
The present invention provides the High-reliability Control method and system in a kind of multi-robot system, the described method includes: the design of robot topology design, failure predication, fault recovery design, wherein: robot topology design: robot topology includes the working group being made of working robot, and the spare working group being made of standby machine people, the position between standby machine people and working robot are replaceable；Failure predication design: in conjunction with the health status of robot in system, failure predication is carried out to working robot using Markov model predicted method；Fault recovery design: when certain working robot is broken down, control standby machine people substitutes the working robot.Analogue system is as the result is shown, the present invention can successfully coordinate to complete the production and processing task of device under non-failure conditions and fault condition, it allows standby machine people to take over failed machines people under certain robot fault state in systems and completes operation, realize the seamless interfacing of device fabrication production.
Description
Technical field
The present invention relates to automation fields, and in particular, to the High-reliability Control side in a kind of multi-robot system
Method and system are applied in multi-robot system, pass through failure predication, topology arrangement and the misarrangement control to multi-robot system
System realizes the High-reliability Control to multi-robot system.
Background technique
Since 1970s, industrial robot begins to become an important technology in industrial circle.It is alive
Within the scope of boundary, industrial robot application has started a climax.With the continuous improvement of human cost, enterprises using the labor cost is continuous
Go up, industrial robot just has objective growth requirement.Meanwhile the application field of industrial robot also from automobile industry gradually
It is expanded to electronic manufacture, food and medicine and plastic industry.In order to complete complicated procedures of forming, industrial robot is all in many cases
Cooperating.Therefore, industrial robot is worked in the form of multi-robot system.
Multiple robots in the industrial production are usually all the tandem workings on assembly line, are cooperated with each other to complete to produce
Operation.In entire production process, if some robot breaks down, the entire production line road paralyses.In high speed
Process industry in, the failure of production line undoubtedly will cause the reduction of production efficiency and the loss of economic interests.
Currently, the multi-robot system in industrial production does not occur the controlling party of more excellent raising reliability
Method.Belong to faults-tolerant control scope on High-reliability Control technological essence, but proper fault-tolerant controller is rate of exchange hardly possible
With realization, especially in industrial robot system.Its reason has two o'clock, and industrial robot first is typically all and standardizes to produce
The product of product, the faults-tolerant control of individual machine people have no way of implementing；Secondly, the institutional framework of multi-robot system is complicated and changeable
, even if designing the fault-tolerant controller of a high quality, it is also difficult to meet the requirement of robustness.One more reasonable method
It is the mode using compromise cost and complexity.
Pure fault tolerant control method should have more reliable theoretical performance, pass through the identification to failure system, adjustment control
Rate processed can extremely economical realize High-reliability Control.This fault tolerant control method carry out distinguishing as unit of system unit and
Mould is rebuild, the control rate of elastic variable improves the life and reliability of system unit indirectly in fact.In many industrial machines
In people's application scenarios, the global reliability of multi-robot system is often more important than the service life of component, because of portion, robot
The alternative costs of part are less than the failure cost of system.So it is a kind of for carrying out High-reliability Control as unit of robot
Very good solution method.
Summary of the invention
For the defects in the prior art, the object of the present invention is to provide it is a kind of controlled as unit of robot it is more
High-reliability Control method and system in robot system.
In order to achieve the above object, the invention adopts the following technical scheme:
According to a first aspect of the present invention, a kind of High-reliability Control method in multi-robot system, the method are provided
Include:
Robot topology design: robot topology includes the working group being made of working robot, and by standby machine
The spare working group that people is constituted, the position between standby machine people and working robot are replaceable；
Failure predication design: in conjunction with the health status of robot in system, using Markov model predicted method to work
Robot carries out failure predication；
Fault recovery design: when certain working robot is broken down, control standby machine people substitutes the working robot.
Preferably, the robot topology design, wherein working group is that one group of hardware configuration is identical, physical location is close
Multiple robots (working robot or standby machine people), the control program of multiple robots can be identical, be also possible to
Different, each robot in working group is that physics is interchangeable, and software program can change according to demand.Guest machine simultaneously
Operating position between device people and working robot is replaceable, and standby machine people, can completely certainly when being substituted into failure stations
Dynamic realization is intervened without others.
Preferably, the failure predication design, wherein the health status of robot is real using fault diagnosis (System Discrimination)
It is existing, i.e., the health status of the robot in system is assessed and classified, output information is the health grading of robot, and fixed
The health status of adopted robot.Health status can be set according to actual needs.
It is highly preferred that health grading is five discrete grades, the health status of robot is defined as following five states:
Normal state, slight degenerate state, gently degraded state, high degradation state, fault case.
Preferably, the failure predication design, wherein carrying out event to working robot using Markov model predicted method
Barrier prediction, specific as follows:
S1, prediction Obj State divide: corresponding to the health status of robot, by " normal state ", " slight degenerate state ",
" gently degraded state ", " high degradation state ", " fault case " this Obj State of five states as Markov model；
S2 calculates probability pi:
For the new engine people of passage capacity detection, it is believed that it is in " normal state ", and the probability of " normal state " is about etc.
In 1, probability vector is exactly { 1,0,0,0,0 }；
S3 calculates the lower transition probability p of each stateij
Its probability is approximatively described with the frequency mutually shifted between state, obtains state transition probability matrix；
S4 is predicted according to transition probability matrix and probability.
It is highly preferred that carrying out transition probability matrix using EM (expectation maximization) algorithm in Markov model in S3
Calculating.
It is highly preferred that in S4, when realizing status predication, robot history " health status " data and five possible shapes
State connects, and as a result obtains five status switches, and status switch brought into Markov model to calculate separately out likelihood general
The size of rate and more several probability, the then corresponding end state, that is, predicted state of the maximum sequence of select probability, this end
Shape of tail state is prediction result.
Preferably, the fault recovery design, wherein working robot, standby machine are equipped with the controller of itself per capita,
The working robot on station and master controller carry out communication and complete production operation, the work on certain station when working properly
When robot breaks down, standby machine people's heavy duty controller substitutes failed machines people and master controller communication, completes to workpiece
Processing tasks.
It is highly preferred that the robot on the master controller and each station is each equipped with transmitter and receiver, it is standby
With robot equipped with receiver；Master controller transmitter channel initial value is the first numerical value, and receiver channel initial value is the
Two numerical value；Robot transmitter channel initial value on each station is second value, and receiver channel initial value is the first numerical value；
Standby machine people's receiver channel initial value is second value；
Communicate between multirobot when fault-free: when the working robot on station can work normally, communication concentrates on leading
Between working robot on controller and each station, the transmitter of master controller and the receiver of all working robot are all logical
Cross identical first numerical value Path Setup communication；It is main when the sensor of master controller, which detects on conveyer belt, workpiece arrival
Controller sends message by transmitter, informs that working robot prepares to start respective task；
Communication when certain working robot breaks down: when a certain working robot on station breaks down, at this time
The second value channel that the working robot passes through transmitter first is counted to master controller and the receiver of standby machine people second
It is worth channel and sends message, it is notified to have occurred and that failure；Standby machine people receives manually be displaced toward failed machines after message and move, and
And complete the adjustment of initial pose；After master controller receives message, pause a period of time enables standby machine people to reach failure work
Position, and complete the adjustment of initial pose；Then, receiver channel value is set the first numerical value by standby machine people, when next
When subjob passes through, master controller can be received by the message standby machine people that the first numerical value channel is sent；Finally by failure
The receiver channel of robot is set as the idle channel that system does not use, and disconnects logical between master controller and failed machines people
News；
It is communicated between standby machine man-hour multirobot: completing each robot transmitters and receivers channel after adjustment
As follows: master controller transmitter channel value is the first numerical value, and receiver channel value is second value；The transmitter of failed machines people
Channel value is second value, and receiver channel value is setting value；Other working robot's transmitter channel values are second value, are connect
Receipts device channel value is the first numerical value；The standby machine people's receiver channel value for replacing failed machines people is the first numerical value；It leads at this time
The transmitter of controller and the receiver of standby machine people, other working robots all pass through identical first numerical value Path Setup
Communication, and failed machines people and remaining robot then disconnect communication connection.
According to a second aspect of the present invention, the High-reliability Control System in a kind of multi-robot system, the system are provided
Include:
Robot topological system: it including the working group being made of working robot, and is made of standby machine people standby
With working group, the position between standby machine people and working robot is replaceable；
Failure prediction system: in conjunction with the health status of robot in system, using Markov model predicted method to work
Robot carries out failure predication；
Fault recovery system: according to the prediction result of failure prediction system, when certain working robot is broken down, control
The standby machine people of robot topological system substitutes the working robot.
Compared with prior art, the present invention have it is following the utility model has the advantages that
The present invention realizes High-reliability Control from the design of controlled system itself: using drawing for working group, robot
Point, working group is some to be made of the robot individual of physics substitutability；The division of working group can not significantly reduce system
Under the premise of reliability, cost is reduced.
Failure predication design of the present invention, which is avoided that, produces substandard products, workpiece damage even safety accident, the failure predication skill
Art may be implemented robot fault and occur according to " known time ", and then failure recovery operation can have the generation of lead.Together
When failure predication may be implemented elasticity Control for Dependability, by the way that robot system may be implemented to the change that fault case defines
The adjusting of stability margin, to realize the dynamic control of product quality；Further, Ma Er has been used in failure predication of the present invention
Section's husband's prediction technique, this is generally more natural thinking.
In fault recovery of the present invention design, by inside working group, robot communication mode and interaction flow design,
Can satisfy robot when normal, when failure and after fault recovery in whole process system operating mode variation.
The method of the present invention is not limited to certain robot system, does not also limit specific application scenarios.Using the present invention into
Capable multi-robot system emulation, can successfully coordinate to complete device as the result is shown under non-failure conditions and fault condition
Production and processing task, obtained satisfied result.
Detailed description of the invention
Upon reading the detailed description of non-limiting embodiments with reference to the following drawings, other feature of the invention,
Objects and advantages will become more apparent upon:
Fig. 1 is the flow chart of failure predication in one embodiment of the invention；
Communication schematic diagram between multirobot when Fig. 2 is fault-free in one embodiment of the invention；
Communication schematic diagram when Fig. 3 is certain station machine human hair life failure in one embodiment of the invention；
Fig. 4 communication schematic diagram between standby machine man-hour multirobot in one embodiment of the invention；
Fig. 5 is master controller control flow chart in one embodiment of the invention；
Fig. 6 is system structure diagram in one embodiment of the invention.
Specific embodiment
The present invention is described in detail combined with specific embodiments below.Following embodiment will be helpful to the technology of this field
Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that the ordinary skill of this field
For personnel, without departing from the inventive concept of the premise, various modifications and improvements can be made.These belong to the present invention
Protection scope.
The present invention is mainly a kind of High-reliability Control technology for being directed to multi-robot system, first against high reliability
System it is basic --- controlled system, propose multi-robot system working group divide, physical topology design.There is object in robot
Controller is needed to be controlled after reason structure, based on above-mentioned thinking, the invention proposes highly reliable in multi-robot system
Property control method and system.
A kind of High-reliability Control method in multi-robot system, which comprises
Robot topology design: robot topology includes the working group being made of working robot, and by standby machine
The spare working group that people is constituted, the position between standby machine people and working robot are replaceable；
Failure predication design: in conjunction with the health status of robot in system, using Markov model predicted method to work
Robot carries out failure predication；
Fault recovery design: when certain working robot is broken down, control standby machine people substitutes the working robot.
Correspondingly, including: with the matched control system of the above method
Robot topological system: it including the working group being made of working robot, and is made of standby machine people standby
With working group, the position between standby machine people and working robot is replaceable；
Failure prediction system: in conjunction with the health status of robot in system, using Markov model predicted method to work
Robot carries out failure predication；
Fault recovery system: according to the prediction result of failure prediction system, when certain working robot is broken down, control
The standby machine people of robot topological system substitutes the working robot.
It is of the invention for ease of understanding, the details in terms of above-mentioned three is described in detail below:
1, robot topology design:
Robot topology design is a basis of this technology.In other words the topology design of robot is exactly flow production line
A part of design.Difference and general Design of Production Line, the Topology Structure Design in the present invention is it is emphasised that extension wire
Design.It is parallel relationship between regular link and extension wire according to the basic common sense of system reliability.In system reliability point
When analysis, system forms the linear superposition of reliability.When robot system will break down, system carries out regular link and failure
The switching of route can guarantee the recovery for realizing system in a short time.In addition, being also of the invention to the reparation of faulty line
A part of content.System can be allowed to realize round-the-clock normal operation the timing reparation of faulty line, this is undoubtedly very heavy
It wants.
Meanwhile robot topology design must also consider the cost of system.If each robot design one spare
The totle drilling cost of individual, robot system almost wants double.This result is difficult to receive in most occasions.So this
Invention proposes the concept of a working group and spare working group, and working group is made of working robot, and spare working group is by standby
It is constituted with robot.Each working group is multiple robots that one group of hardware configuration is identical, physical location is close.Certainly their control
Processing procedure sequence can be identical, be also possible to different.That is the robot in working group is that physics is interchangeable, and soft
Part program is to change according to demand.The second layer of " physics is replaceable " mentioned here is meant that standby machine people and work
The operating position made between robot is replaceable.Standby machine people completely automatic can realize when being substituted into failure stations,
Intervene without others.
2, failure predication designs:
For the High-reliability Control for realizing multirobot, the present invention further designs on the basis of above-mentioned hardware modifications
Failure prediction method, the practical significance of failure predication are that there is certain stability margin in the robot in guarantee system.In machine
In device people's life cycle, health status is in change procedure.And its changing rule is a statistical law.If not into
Row failure predication is just likely to occur producing substandard products, workpiece damage or even safety accident occurs.This is undoubtedly in this method very
One technology of significant.Failure predication technology is established on the basis of fault diagnosis (System Discrimination in other words).Failure is examined
Disconnected (System Discrimination) is that the health status of the robot in system is assessed and classified.The output information of System Discrimination process
It is the health grading of robot.Health grading is five discrete grades, and " health status " of robot is defined as by the present invention
Following state: normal state, slight degenerate state, gently degraded state, high degradation state, fault case.Certainly, these states can also
To be adjusted or change according to actual needs, this has no effect on the realization of the object of the invention.
The present invention realizes the failure predication of robot using Markov model predicted method.Markov model prediction is benefit
A kind of method that stochastic pattern temporal model is predicted is established with probability.Prediction of Markov method is markoff process and Ma Er
Section's husband's chain prediction field a kind of application, this method by probability to things state classification, each state of research and
Transition probability predicts the variation tendency of things future state between state, to predict the future of things.
If time and state parameter are all discrete markoff process, and have markov property, this random process is
Markov chain.If markov property can specifically be expressed as the time parameter t sequence of random variables { Y (t), t ∈ T }sAs
" present ", then t > tsIt indicates " future ", t < tsIt indicates " past ", then, system is in current situation Y (ts) known to item
Under part, the case where locating for Y (t) " future " subsequent time with " past " the case where, is unrelated, this characteristic of random process is known as
Markov property.
Prediction model: S(k+1)=S(k)In P formula: S(k)It is the state vector for predicting the object t=k moment；P is that step transfer is general
Rate matrix；S(k+1)It is the state vector for predicting object in t=k+1, the result of prediction.
It can be obtained according to above-mentioned prediction model: S(1)=S(0)P
S(2)=S(1)P
S(k+1)=S(0)P(k+1)
Prediction model: in formula: S(0)For predict object initial state vector, be from the probability of state form to
Amount.For markov chain, the probability that it is in any moment t can be determined by probability initial state vector and a step transition probability
It is fixed.
Applicable elements: prediction model is only applicable to the time series with Markov property, in time span of forecast, each moment
State transition probability keep stablize, be a step transition probability.If the state transition probability of timing is changing with different moments,
The method should not be used.The method applies in general to short-term forecast.
State transition probability matrix P comprehensively describes the relationship that prediction object changes between each state, is predicting
In play the role of it is critically important.It not only determines prediction object state in which, but also decides that the variation of prediction object becomes
Gesture and final result.
The step of Markov model prediction technique, is as follows:
1), prediction Obj State divides
The state and previously described robot " health status " for predicting object are same meanings.In the step, we
Just using " normal state ", " slight degenerate state ", " gently degraded state ", " high degradation state ", " fault case " this five states as horse
The Obj State of Er Kefu model.
2) probability p, is calculatedi
Probability refers to the probability that state occurs.When the theoretical distribution of state probability is unknown, if sample size is enough
Greatly, usable samples distribution approximatively describes the theoretical distribution of state.Therefore, the frequency approximatively estimated state that available mode occurs
The probability of appearance.It is assumed that prediction object has Ei(i=1,2 ..., n) a state, in known historical data, EiTime that state occurs
Number is Mi；Then EiThe frequency F of appearancei=Mi/N.It works this application scenarios in robot, for the new machine of passage capacity detection
Device people, it is generally recognized that it is in " normal state ", this is a quite reasonable setting.It is equivalent to five states in prediction object
In, the probability of " normal state " be approximately equal to 1 namely new engine people carve can not be in other states at the beginning.So just
Beginning probability vector is exactly { 1,0,0,0,0 }.
3) the lower transition probability p of each state, is calculatedij
The same with the probability of state, the theoretical distribution of state transition probability is unknown, when sample size is sufficiently large,
Its probability can approximatively be described with the frequency mutually shifted between state.It is assumed that by state EiTurn to EjNumber be Mi, then
pij=P (Ei→Ej)=P (Ej|Ei)≈Mij/Mi(i=1,2, L, n) (j=1,2, L, n)
Just obtain a step transition probability matrix (state transition probability matrix):
P on matrix leading diagonal11, P22... PnnIt indicates still to be in original state probability of state after step transfer.It uses
This method calculate state transition probability be it is fairly simple, operation is more basic.But there is also significantly not for this method
Foot, simple statistics calculate the ordinal relation having ignored between status switch, this causes many information in initial data not have
It is utilized.Better method be using Markov model in EM (expectation maximization) algorithm carry out state transition probability square
The calculating of battle array.
Intuitively understand EM algorithm, it is also seen as a successive approximation algorithm: being not aware that the ginseng of model in advance
Number, selection set of parameter that can be random or roughly gives some initial parameter λ 0 in advance, determines that corresponding to this group joins
Several most probable states, calculates the probability of the possible outcome of each training sample, again by sample to ginseng in the state of current
Number amendment, reevaluates parameter lambda, and the state of model is redefined under new parameter, in this way, following by multiple iteration
Ring is until some condition of convergence meets, so that it may so that the parameter of model gradually approaching to reality parameter.The use of EM algorithm
It is the key point that failure prediction algorithm is realized.For a Markov model, key parameter it is main it is stateful, initially to
Measure (each shape probability of state when system initialization), state transition probability matrix.The above two be all 1) and 2) in complete,
And it only needs simply to calculate.It is iterative calculation to the calculating (EM algorithm) of state transition probability matrix in 3), is model
Trained committed step.
4) it, is predicted according to state transition probability matrix and probability.Final step needs to utilize history run number
It is calculated according to Markov model.History data is one section of status switch, is machine individual human in pervious work
Make in the period data of " health status ".Markov model is substantially a probabilistic model, gives a status switch all
Its corresponding probability can be calculated according to state transition probability matrix.When realizing status predication, robot history " health
Situation " data and five possible states connect, and as a result obtain five status switches.Finally, bringing status switch into model
In calculate separately out the size of likelihood probability and more several probability, the then corresponding end state of the maximum sequence of select probability
(i.e. predicted state).This end state is prediction result.Shown in the procedure chart 1 of entire failure predication.
3, fault recovery technology:
Each controller for having itself by oneself of working robot, standby machine people on station.The station when equipment works normally
On working robot and master controller carry out communication complete production operation；When the working robot on certain station is broken down
When, standby machine people's heavy duty controller substitutes working robot and the master controller communication of failure, completes the processing to workpiece and appoints
Business.
The communication between multirobot and the control flow of each robot are introduced in citing below.
Communicated between multirobot: robot on master controller and each station each equipped with transmitter and receiver,
Standby machine people is equipped with transmitter.Master controller transmitter channel initial value is 0, and transmitter channel initial value is 1；Each station
On robot transmitter channel initial value be 1, receiver channel initial value be 0；Standby machine people's receiver channel initial value
It is 1.
1) it, is communicated between multirobot when fault-free
When the working robot on station can work normally, communication concentrates on the working machine on master controller and each station
Between device people, as shown in Fig. 2, robot A, robot B, robot C, robot D are working robot.The transmission of master controller
Device and robot A, robot B, robot C, robot D receiver all pass through identical channel 0 and establish communication.Work as main control
The sensor of device detects on conveyer belt when having workpiece arrival, and master controller sends message by transmitter, inform robot A,
Robot B, robot C, robot D prepare to start respective task.
2) communication when, certain working robot breaks down
(robot A might as well be set to break down) when a certain working robot on station breaks down, at this time machine
The channel 1 that people A passes through transmitter first sends message to master controller and the transmitter channel of standby machine people 1, notifies it
Through breaking down.Past robot A station is mobile after standby machine people receives message, and completes the adjustment of initial pose.Master control
After device processed receives message, pause a period of time enables standby machine people to reach robot A station, and completes the tune of initial pose
Whole, after the completion, standby machine people sets 0 for receiver channel, in order to when workpiece passes through next time, master controller
The message sent by channel 0 can be such that standby machine people receives.Finally setting system not for the receiver channel of robot A makes
Idle channel (might as well be set as channel 9), disconnect the communication between master controller and robot A.Whole flow process such as Fig. 3 institute
Show.
3) it, is communicated between standby machine man-hour multirobot
Each robot transmitters and receivers channel is as follows after completing adjustment: master controller transmitter channel value is 0, is connect
Receiving device channel value is 1；The transmitter channel value of robot A is 1, and receiver channel value is 9；Robot B, robot C, robot
The transmitter channel value of D is 1, and receiver channel value is 0；The receiver channel value of standby machine people is 0.Master controller at this time
Transmitter and standby machine people, robot B, robot C, robot D receiver all pass through identical channel 0 and establish communication,
And robot A and remaining robot then disconnect communication connection, as shown in Figure 4.
4), master control process
Under Webots environment, emulation experiment is carried out to the present invention, wherein important master control process such as Fig. 5 institute
Show.
0. setting receiver channel is 1, for receiving the information sent from the robot to break down；Transmitter is set
Channel is 0, for sending message to the robot worked normally.
1. program loop control waits unit to control the time.
2. detecting in failure message queue either with or without message, if there is message to go to 3a in queue, 3b is otherwise gone to.
Whether 3a. detection delay terminates, if it is not, delay certain time goes to 1；Otherwise, standby machine people is represented
It has arrived at station and adjusts initial pose work and complete, go to 4.
3b. conveyer belt motion control detects handling situations, if can't run, robot is to workpiece in waiting station
Processing, goes to 1；If can run, 4 are gone to.
4. obtaining conveyer belt upper position sensor probe value, if probe value is less than threshold value, position sensor is represented not yet
Workpiece arrival is detected, goes to 1；Otherwise 5 are gone to.
5. checking whether message sends, if be sent, 1 is gone to；Otherwise, it sends message and records, turn simultaneously
To 1.
Analogue system can successfully be coordinated to complete the life of device as the result is shown under non-failure conditions and fault condition
Processing tasks are produced, allows standby machine people to take over failed machines people under certain robot fault state in systems and completes operation, it is real
The seamless interfacing of device fabrication production is showed.
Specific embodiments of the present invention are described above.It is to be appreciated that the invention is not limited to above-mentioned
Particular implementation, those skilled in the art can make various deformations or amendments within the scope of the claims, this not shadow
Ring substantive content of the invention.
Claims (8)
1. a kind of High-reliability Control method in multi-robot system, which is characterized in that the described method includes:
Robot topology design: robot topology includes the working group being made of working robot, and by standby machine people's structure
At spare working group, the position between standby machine people and working robot is replaceable；
Failure predication design: in conjunction with the health status of robot in system, using Markov model predicted method to Work machine
People carries out failure predication；
Fault recovery design: when certain working robot is broken down, control standby machine people substitutes the working robot；
The fault recovery design, wherein working robot, standby machine are equipped with the controller of itself per capita, when working properly
Working robot and master controller on station carry out communication and complete production operation, when event occurs in the working robot on certain station
When barrier, standby machine people's heavy duty controller substitutes failed machines people and master controller communication, completes the processing tasks to workpiece；
Robot on the master controller and each station each equipped with transmitter and receiver, standby machine people equipped with
Receiver；Master controller transmitter channel initial value is the first numerical value, and receiver channel initial value is second value；On each station
Robot transmitter channel initial value be second value, receiver channel initial value be the first numerical value；Standby machine people receives
Device channel initial value is second value；
Communicate between multirobot when fault-free: when the working robot on station can work normally, communication concentrates on main control
Between working robot on device and each station, the transmitter of master controller and the receiver of all working robot all pass through phase
Same the first numerical value Path Setup communication；When the sensor of master controller, which detects on conveyer belt, workpiece arrival, main control
Device sends message by transmitter, informs that working robot prepares to start respective task；
Communication when certain working robot breaks down: when a certain working robot on station breaks down, the work at this time
Making robot, to pass through the second value channel of transmitter first logical to master controller and the receiver second value of standby machine people
Road sends message, it is notified to have occurred and that failure；Standby machine people receives manually be displaced toward failed machines after message and move, and complete
At the adjustment of initial pose；After master controller receives message, pause a period of time enables standby machine people to reach failure stations, and
And complete the adjustment of initial pose；Then, receiver channel value is set the first numerical value by standby machine people, when workpiece next time
When passing through, master controller can be received by the message standby machine people that the first numerical value channel is sent；Finally by failed machines people
Receiver channel be set as the idle channel that system does not use, disconnect the communication between master controller and failed machines people；
Communicated between standby machine man-hour multirobot: complete adjustment after each robot transmitters and receivers channel such as
Under: master controller transmitter channel value is the first numerical value, and receiver channel value is second value；The transmitter of failed machines people is logical
Road value is second value, and receiver channel value is setting value；Other working robot's transmitter channel values are second value, are received
Device channel value is the first numerical value；The standby machine people's receiver channel value for replacing failed machines people is the first numerical value；Master control at this time
It is logical that the transmitter of device processed and the receiver of standby machine people, other working robots all pass through identical first numerical value Path Setup
News, and failed machines people and remaining robot then disconnect communication connection.
2. the High-reliability Control method in multi-robot system according to claim 1, which is characterized in that the machine
People's topology design, wherein working group is multiple robots that one group of hardware configuration is identical, physical location is close, multiple robots
Control program be it is identical or different, each robot in working group is that physics is interchangeable, and software program can change according to demand；
Operating position simultaneously between standby machine people and working robot is replaceable, and standby machine people can realize replacement failure work automatically
The working robot of position, does not need other interventions.
3. the High-reliability Control method in multi-robot system according to claim 1, which is characterized in that the failure
Predictive designs, wherein the health status of robot using fault diagnosis realize, i.e., to the health status of the robot in system into
Row assessment and classification, output information are the health grading of robot, and define the health status of robot.
4. the High-reliability Control method in multi-robot system according to claim 3, which is characterized in that the health
Grading is five discrete grades, and the health status of robot is defined as following five states: normal state, slight degenerate state, in
Spend degenerate state, high degradation state, fault case.
5. the High-reliability Control method in multi-robot system according to claim 4, which is characterized in that the failure
Predictive designs, wherein failure predication is carried out to working robot using Markov model predicted method, it is specific as follows:
S1, prediction Obj State divide: corresponding to the health status of robot, by " normal state ", " slight degenerate state ", " moderate
Degenerate state ", " high degradation state ", " fault case " this Obj State of five states as Markov model；
S2 calculates probability pi:
For the new engine people of passage capacity detection, it is believed that it is in " normal state ", and the probability of " normal state " is equal to 1, just
Beginning probability vector is exactly { 1,0,0,0,0 }；
S3 calculates the lower transition probability p of each stateij
Its probability is approximatively described with the frequency mutually shifted between state, obtains state transition probability matrix；
S4 is predicted according to transition probability matrix and probability.
6. the High-reliability Control method in multi-robot system according to claim 5, which is characterized in that in S3, make
The calculating of transition probability matrix is carried out with the expectation-maximization algorithm in Markov model.
7. the High-reliability Control method in multi-robot system according to claim 5, which is characterized in that in S4,
When realizing status predication, robot history " health status " data and five possible states are connected, as a result obtain five
Status switch is brought in Markov model into the size for calculating separately out likelihood probability and more several probability by status switch,
Then the corresponding end state, that is, predicted state of the maximum sequence of select probability, this end state is prediction result.
8. the High-reliability Control in a kind of multi-robot system for realizing any one of the claims 1-7 the method
System characterized by comprising
Robot topological system: including the working group being made of working robot, and the spare work being made of standby machine people
Make group, the position between standby machine people and working robot is replaceable；
Failure prediction system: in conjunction with the health status of robot in system, using Markov model predicted method to Work machine
People carries out failure predication；
Fault recovery system: machine is controlled when certain working robot is broken down according to the prediction result of failure prediction system
The standby machine people of people's topological system substitutes the working robot.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510729291.2A CN105426986B (en) | 2015-10-30 | 2015-10-30 | High-reliability Control method and system in multi-robot system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510729291.2A CN105426986B (en) | 2015-10-30 | 2015-10-30 | High-reliability Control method and system in multi-robot system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105426986A CN105426986A (en) | 2016-03-23 |
| CN105426986B true CN105426986B (en) | 2019-06-21 |
Family
ID=55505180
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510729291.2A Active CN105426986B (en) | 2015-10-30 | 2015-10-30 | High-reliability Control method and system in multi-robot system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105426986B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106041935A (en) * | 2016-07-27 | 2016-10-26 | 重庆峰创科技有限公司 | High-reliability fault-tolerant control device for an industrial robot |
| JP2019530079A (en) * | 2016-09-09 | 2019-10-17 | ファナック アメリカ コーポレイション | Program analysis and variable change analysis |
| CN114115337A (en) * | 2016-09-22 | 2022-03-01 | 深圳市大疆创新科技有限公司 | Flight control method and device and intelligent terminal |
| JP6500867B2 (en) * | 2016-09-23 | 2019-04-17 | カシオ計算機株式会社 | Robot, fault diagnosis system, fault diagnosis method and program |
| CN108701285A (en) * | 2017-08-23 | 2018-10-23 | 深圳蓝胖子机器人有限公司 | Robot dispatching method, server, electronic equipment and readable storage medium storing program for executing |
| CN113146651B (en) * | 2021-04-15 | 2023-03-10 | 华中科技大学 | Tea making robot and control method thereof |
| CN113524200B (en) * | 2021-09-07 | 2021-12-14 | 季华实验室 | Mechanical arm scheduling system, mechanical arm scheduling method, mechanical arm replacing device, mechanical arm equipment and mechanical arm medium |
| CN114779615B (en) * | 2022-06-17 | 2022-09-13 | 深圳市捷牛智能装备有限公司 | Robot management and control method and system based on artificial intelligence |
| CN115220451A (en) * | 2022-07-18 | 2022-10-21 | 杭州海康机器人股份有限公司 | Scheduling control method and device and electronic equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1039908A (en) * | 1996-07-18 | 1998-02-13 | Nachi Fujikoshi Corp | Fault predicting method for industrial robot |
| CN1737423A (en) * | 2005-08-10 | 2006-02-22 | 东北大学 | Method and apparatus for realizing integration of fault-diagnosis and fault-tolerance for boiler sensor based on Internet |
| CN101286954A (en) * | 2007-02-13 | 2008-10-15 | Abb研究有限公司 | Remote diagnostic system for robots |
-
2015
- 2015-10-30 CN CN201510729291.2A patent/CN105426986B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1039908A (en) * | 1996-07-18 | 1998-02-13 | Nachi Fujikoshi Corp | Fault predicting method for industrial robot |
| CN1737423A (en) * | 2005-08-10 | 2006-02-22 | 东北大学 | Method and apparatus for realizing integration of fault-diagnosis and fault-tolerance for boiler sensor based on Internet |
| CN101286954A (en) * | 2007-02-13 | 2008-10-15 | Abb研究有限公司 | Remote diagnostic system for robots |
Non-Patent Citations (3)
| Title |
|---|
| Fault Detection and Analysis of Control Software for a Mobile Robot;Jiliang Lin 等;《Sixth International Conference on Intelligent Systems Design and Applications》;20061018;第1卷;全文 |
| 小波包变换和隐马尔可夫模型在轴承性能退化评估中的应用;肖文斌;《振动与冲击》;20110831;第30卷(第8期);第32页第1栏第2段-第35页第1栏第2段 |
| 机器人系统的故障预测技术研究;王瑞芳;《制造业自动化》;20081130;第30卷(第11期);第15页第2栏第2段-第18页第2栏第2段 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105426986A (en) | 2016-03-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105426986B (en) | High-reliability Control method and system in multi-robot system | |
| CN107861478B (en) | A kind of parallel control method in intelligence workshop and system | |
| US11036191B2 (en) | Machine learning device, industrial machine cell, manufacturing system, and machine learning method for learning task sharing among plurality of industrial machines | |
| CN106527384B (en) | A kind of production regulation method based on cloud platform complementary handover strategies | |
| Bandyopadhyay et al. | Probabilistic swarm guidance using optimal transport | |
| CN106953802B (en) | Network optimal path selection method based on deep learning | |
| CN108345723A (en) | A kind of Diagnostic system of motor fault and method based on decision tree and Bayesian network | |
| Yang et al. | Cloud-edge-device collaboration mechanisms of deep learning models for smart robots in mass personalization | |
| CN104378232B (en) | Fissure discovery, restoration methods and device under active and standby cluster networking pattern | |
| EP3014446A1 (en) | Asynchronous message passing for large graph clustering | |
| CN111526070A (en) | Service function chain fault detection method based on prediction | |
| CN110073304B (en) | Method and apparatus for determining current and future states of industrial machines | |
| JP7320885B2 (en) | Systems, methods and media for manufacturing processes | |
| CN114297935A (en) | Airport terminal building departure optimization operation simulation system and method based on digital twin | |
| CN110891283A (en) | Small base station monitoring device and method based on edge calculation model | |
| Lin et al. | Integrated cyber physical simulation modelling environment for manufacturing 4.0 | |
| JP2019087101A (en) | Anticipation model maintenance system, method for maintaining anticipation model, and anticipation model maintenance program | |
| CN105446203B (en) | A kind of robot power supply control method and system | |
| CN108445857B (en) | Design method for 1+ N redundancy mechanism of SCADA system | |
| US11385602B2 (en) | System control method and apparatus, controller, and control system | |
| Singh et al. | To enhance the reliability and energy efficiency of WSN using new clustering approach | |
| Foumani et al. | Resolution of deadlocks in a robotic cell scheduling problem with post-process inspection system: Avoidance and recovery scenarios | |
| Manogaran et al. | Boosted tree classifier algorithm based collaborative computing framework for smart system | |
| Ashfahani et al. | Autonomous deep quality monitoring in streaming environments | |
| CN109976294A (en) | A kind of intelligent parking method and system |
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 | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20240315 Address after: 618 Liangjiang Avenue, Longxing Town, Yubei District, Chongqing Patentee after: Chongqing near space innovation R & D center of Shanghai Jiaotong University Country or region after: China Address before: 200240 No. 800, Dongchuan Road, Shanghai, Minhang District Patentee before: SHANGHAI JIAO TONG University Country or region before: China |
|
| TR01 | Transfer of patent right |