CN102033536A - Scheduling, organization and cooperation system and method for multi-robot system - Google Patents
Scheduling, organization and cooperation system and method for multi-robot system Download PDFInfo
- Publication number
- CN102033536A CN102033536A CN2010105997263A CN201010599726A CN102033536A CN 102033536 A CN102033536 A CN 102033536A CN 2010105997263 A CN2010105997263 A CN 2010105997263A CN 201010599726 A CN201010599726 A CN 201010599726A CN 102033536 A CN102033536 A CN 102033536A
- Authority
- CN
- China
- Prior art keywords
- task
- management
- robot
- evaluation result
- resource
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 38
- 230000008520 organization Effects 0.000 title abstract description 9
- 230000008569 process Effects 0.000 claims abstract description 20
- 238000004891 communication Methods 0.000 claims abstract description 13
- 238000011156 evaluation Methods 0.000 claims description 68
- 238000012545 processing Methods 0.000 claims description 23
- 230000007246 mechanism Effects 0.000 claims description 14
- 238000012544 monitoring process Methods 0.000 claims description 14
- 238000003860 storage Methods 0.000 claims description 8
- 108010014172 Factor V Proteins 0.000 claims description 2
- 230000002180 anti-stress Effects 0.000 claims description 2
- 238000000354 decomposition reaction Methods 0.000 claims description 2
- 238000007781 pre-processing Methods 0.000 claims description 2
- 230000003993 interaction Effects 0.000 abstract description 6
- 230000000694 effects Effects 0.000 abstract description 5
- 230000010365 information processing Effects 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 239000002699 waste material Substances 0.000 abstract description 2
- 230000009897 systematic effect Effects 0.000 abstract 3
- 230000000903 blocking effect Effects 0.000 abstract 1
- 238000007726 management method Methods 0.000 description 48
- 238000011160 research Methods 0.000 description 11
- 238000013461 design Methods 0.000 description 10
- 230000006870 function Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000013334 tissue model Methods 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- General Factory Administration (AREA)
Abstract
The invention discloses a scheduling, organization and cooperation system and a scheduling, organization and cooperation method for a multi-robot system. By adoption of distributive mode architecture, the information interaction is reduced, the systematic resources are used fully, the activity and the problem solving level of the overall system are enhanced, and the ability of intelligent coordination and flexible cooperation among a plurality of robots is enhanced. The method and the system intelligently perform scheduling and cooperation, reduce the communication traffic, reduce the systematic consumption, well adapt to a dynamic environment and complicated dynamic tasks, and enhance the problem solving capability by employing a dynamic decision maker scheme, namely every robot may be a task decision maker. According to the invention, a bulletin is used, a method of making a robot actively check the bulletin to acquire task information in an active free (capability) state is adopted and the selection of the best can be finished during checking, so that the information interaction is reduced, the information processing and comparison process is simplified, the communication traffic is greatly reduced and problems of information blocking and wastes of the systematic resources are solved.
Description
Technical field
Design robot control of the present invention field, particularly cooperative system and method are organized in a kind of scheduling of multi-robot system.
Background technology
Along with the continuous expansion in robot function and field, the flexible intelligent robot has replaced the robot of rigid, the function singleness of tradition, becomes current main direction of studying.Yet, in the multi-robot system, be in dynamically, between each robot in the uncertain environment, in the task implementation, need a large amount of information interactions and negotiation, yet along with the increase of robot quantity, communication pressure between robot and coordination difficulty also will increase greatly.And traditional multi-robot system communication exists a large amount of problems such as congestion information; Centralized or the layer-stepping pattern that is adopted on the organizational form in the dynamic change that adapts to main body ability and environment, has reduced the activity of total system, and bottleneck has been appearred in gerentocratic high request especially.In addition, also need to carry out the re-treatment and the comparison of bulk information when selecting the task executor, not only efficient is not high, but also has wasted a large amount of system resource.
The research of multi-robot system at present has been subjected to common attention, and relatively more classical experimental system has: CEBOT (Cellular Robotic system), ALLIANCE/L-ALLANCE system, SWARM system.The colony's architecture, perception that these researchs relate to multirobot and Multi-sensor Fusion, communicate by letter and many aspects such as the coordination system, Task Distribution, study, the realization of motion planning system, and are main contents of multi-robot system research for the research of the coordination and cooperation of a plurality of robots.The scholar that external current research mainly contains U.S. USC university sets up soeiallyM0bile and TheNerdHerd experimental system; The Collective Robotics(collective robot system of people such as the C.R.Kube development of Canada Alberta university) and many work of doing at aspects such as multi-Agent cooperation, autonomous Agent architecture, multi-Agent communications of doctor LynneE.Parker of U.S. Oak Ridge National Laboratory.With respect to abroad, China starts late for the research of multi-robot system, generally concentrate on aspects such as multirobot cooperation and multirobot study, and spininess is to the application foundation Journal of Sex Research of intelligent manufacturing system and robot soccer.The MACAS system that main contents have Chinese Academy of Sciences's Shenyang Institute of Automation to set up; The multiple-mobile-robot system platform ActivMedia Robotics of Shanghai Communications University's development.Yet all multi-methods that these researchs are adopted during the problem aspect Task Distribution and the cooperation in handling the multirobot dispatching system are in the dynamic change that adapts to main body ability and environment, reduce the traffic, the problem solving ability that improves total system and the aspects such as overall performance optimization of activity and still exist problems.The design and in conjunction with new application background and technology, has designed new the flexible tissue model and the smart collaboration scheme that are applicable to the multirobot scheduling on the basis of accumulation available research achievements, this scheme will have broad application prospects.
Summary of the invention
The objective of the invention is: at all bottlenecks that exist in the current multi-robot system, designed a kind of new dispatch group organization model that is suitable for the flexible robot, and a kind of smart collaboration mechanism has been proposed based on model, to reduce the traffic, minimizing system overhead, the raising problem solving ability in the scheduling process, improve the entire system performance.
The technical solution used in the present invention is: provide a kind of scheduling of multi-robot system to organize collaboration method, may further comprise the steps:
The first step, task issuing process: after the management and running unit of first Robot1 of robot finds that new task arrives, task management unit, rm-cell and management and running unit associations are made self-assessment, provide evaluation result, first Robot1 of robot becomes the decision maker, and the management and running unit together is published to announcement board Bulletin with mission bit stream together with evaluation result.
Second step, executor's selection course: selecting the task executor before the time arrives, there is the robot of idling-resource to check the mission bit stream of announcement board Bulletin, carry out self-assessment, the evaluation result comparison module of management and running unit compares evaluation result and current decision maker's evaluation result, if this time evaluation result is better than current decision maker's evaluation result, the evaluation result of then revising in the current task information is new evaluation result, and replacing current decision maker becomes new decision maker, and notifies former decision maker to abandon right to make decision to this task; Otherwise, abandon this task.
The 3rd step, executor's deterministic process: if task executor's selection course finishes, and this moment, the decision maker still was discoverer first Robot1 of robot of task, the task ability judge module of management and running unit judges that first Robot1 of robot possesses the ability of finishing this task, then current decision maker becomes the task executor, begin task executions, and upgrade self-ability information with regard to the performance of task.
Wherein, described the 3rd step further comprises: if task executor's selection course finishes, and this moment, the decision maker still was discoverer first Robot1 of robot of task, and first Robot1 of robot does not possess the ability of finishing this task, then this task is decomposed by the task decomposing module of the management and running unit of first Robot1 of robot, bear part task wherein, and the task that will remain is issued bulletin, three steps of the repetition first step to the once more.
Wherein, the step of described self-assessment comprises:
At first, after new task is found in the management and running unit, management and running unit and task management unit and resource management module are held consultation: if this task directly obtains from real world, then estimate according to the current task load information of task management unit calculating and the resource load information of rm-cell calculating, then evaluation result is issued together with mission bit stream by its management and running unit; So that the other machines people is known new information, this robot also becomes current decision maker, and this condition of information is monitored in beginning in real time.If receive the notice that the other machines people sends, then abandon right to make decision to this task.
Secondly, task management unit and resource management module carry out the calculating of pre-service and processing power to current task.
Wherein, preprocessing process is: the mission bit stream collection module collection monitoring in the task management unit and all mission bit streams of tracking comprise: priority Ui, beginning time limit Si, processing time Ti, carry out required resource Ri etc. with traffic summation Ci, the current place node Ni of other task, task; Resource information monitoring module dynamic collection in the resource management module is the monitoring resource information relevant with processing power in real time, comprising: the flow Ii of controller utilization factor Pi, instruction ready queue length L i, storage space Mi, each interface and utilization factor Ei etc.
Wherein, processing power computation process is: mission bit stream computing module in the task management unit is according to all mission bit streams of collecting, and with they integrate calculate current task loading condition T_load=μ 1Ui+μ 2Si+μ 3Ti+μ 4Ci+μ 5Ni+μ 6Ri+
Resource information computing module in the rm-cell is according to the information of dynamic real-time monitor and collection, and with they integrate calculate current resource load situation R_load=β 1Pi+β 2Li+β 3Mi+β 4Ii+β 5Ei+
Wherein, μ i, β i are respectively the wherein weights of each information,
,
, can specifically set according to different demands.
At last, the management and running unit is according to negotiation result, and in conjunction with other factors, comprising: antistress and communication capacity, the discovery of task and the ability of acceptance, and the issue capability of task; By finishing the overall evaluation work of ability, and provide final self evaluation result F=f(T_ load with the communication negotiation of other unit, R_load ...), evaluation result F is the function of each factor.
Other provides a kind of scheduling of multi-robot system to organize cooperative system, and described scheduling organizes cooperative system to comprise:
The task management unit, be used for monitoring and follow the tracks of all mission bit streams, described mission bit stream comprises priority, beginning time limit, processing time, the traffic summation with other task, current place node, the required resource of task execution, and mission bit stream integrated calculate current task loading condition, according to mission requirements, the application resource is carried out its task.
Rm-cell is used to manage all resources relevant with processing power, the monitoring of dynamic real-time and collect resource information, and resource information is integrated the current resource load situation of calculating; Described resource comprises: the flow of controller utilization factor, instruction ready queue length, storage space, each interface and utilization factor etc.
The management and running unit: be used to the discovery and the acceptance of the task that realizes, and the issue of task; Hold consultation with its task management unit, rm-cell, finish the overall evaluation work of ability, and provide evaluation result; Realize with the other machines people between communicate by letter; After receiving an assignment, can carry out task scheduling, finish the decomposition of extensive task according to task issue situation.
Described task management unit, rm-cell and management and running unit interconnect by communication interface.
Wherein, described management and running unit comprises:
The evaluation result comparison module, be used for self evaluation result and current decision maker's evaluation result is compared: if evaluation result is better than former decision maker, revise then that evaluation result is new evaluation result in the announcement board, replace former decision maker and become new decision maker, give notice to former decision maker, so that former decision maker abandons the right to make decision to this task, otherwise do not participate in the competition.
The task ability judge module, be used to judge whether first Robot1 of robot possesses the ability of finishing this task: arrived uncontested person when the effective time of message, the task ability judge module is made a strategic decision according to its ability, and ability is enough, then carry out its task, otherwise task is decomposed.
The release module of task is issued evaluation result together with mission bit stream, so that the other machines people is known new information.
Wherein, described management and running unit further comprises:
The task decomposing module, be used for extensive task is decomposed: arrived uncontested person when the effective time of message, first Robot1 of robot does not possess the ability of finishing this task again, then task is decomposed, carry out the part task after decomposing, and the task that will remain is handled by this scheduling coordination mechanism once more.
Wherein, described task management unit comprises:
The mission bit stream collection module, all mission bit streams that are used to monitor and follow the tracks of comprise: priority, beginning time limit, processing time, the traffic summation with other task, current place node, task are carried out required resource etc.
The mission bit stream computing module is used for according to all mission bit streams of collecting, with they integrate calculate current task loading condition T_load=μ 1Ui+μ 2Si+μ 3Ti+μ 4Ci+μ 5Ni+μ 6Ri+
Wherein, μ i is weights,
, specifically set according to different needs.
Wherein, described rm-cell comprises:
The resource information monitoring module is used to manage all resources relevant with processing power, comprising: the flow of controller utilization factor, instruction ready queue length, storage space, each interface and utilization factor etc.
The resource information computing module is used for the information according to dynamic real-time monitor and collection, and with they integrate calculate current resource load situation R_load=β 1Pi+β 2Li+β 3Mi+β 4Ii+β 5Ei+
Wherein, β i is weights,
, specifically set according to different needs.
Beneficial technical effects of the present invention:
(1) dispatch group organization model that the design proposed and coordination mechanism are a kind of brand-new design proposals, distributed pattern architecture is adopted in design, can reduce information interaction, make full use of system resource, improve the activity and the problem solving level of total system, strengthened the ability of the intelligent coordinated and flexible cooperation between a plurality of robots.
(2) along with the variation of task and environment, the role of each robot also can change, develop to flexible intelligent gradually from the robot of function singleness, cause the dynamic change of robot system institutional framework, to this design person's scheme that adopts the dynamic decision, be the decision maker that each robot all may become task, intelligent dispatching and cooperating, reach the reduction traffic, reduce the purpose of system consumption, and can better adapt to dynamic environment and complicated dynamic task, improve the ability of finding the solution of problem.
(3) adopt the method for network service in the traditional scheme between each robot, can take a large amount of Internet resources, therefore, cause the obstruction of network when limited or network resource loads is heavier at Internet resources easily.We have quoted announcement board in this article at this defective, employing allows robot check initiatively that when the resource free time (ability) is arranged announcement board obtains the method for mission bit stream, simultaneously, the process of checking can be finished the selection for the superior, thereby minimizing information interaction, simplified the information processing comparison procedure in the former traditional scheme, greatly reduced the traffic, effectively solved the information that occurs in the traditional scheme and block and the resource waste problem.
Description of drawings
The dispatch group organization model figure of Fig. 1 multi-robot system of the present invention.
The cooperative system frame diagram is organized in the scheduling of Fig. 2 multi-robot system of the present invention.
The task management unit framework figure of cooperative system is organized in the scheduling of Fig. 3 multi-robot system of the present invention.
The rm-cell frame diagram of cooperative system is organized in the scheduling of Fig. 4 multi-robot system of the present invention.
The management and running unit framework figure of cooperative system is organized in the scheduling of Fig. 5 multi-robot system of the present invention.
Collaboration method task issuing process process flow diagram is organized in the scheduling of Fig. 6 multi-robot system of the present invention.
Collaboration method executor selection course process flow diagram is organized in the scheduling of Fig. 7 multi-robot system of the present invention.
Collaboration method executor deterministic process process flow diagram is organized in the scheduling of Fig. 8 multi-robot system of the present invention.
Embodiment
The present invention is described in detail below in conjunction with drawings and Examples.
One, thinking of the present invention:
Development along with computing technique, the continuous expansion of the deep and application of multirobot technical research, the quantity size of robot application is also in continuous expansion, the function that robot has is also enriched constantly, communication pressure between the robot and coordination difficulty will strengthen, make to become more and more important about the formation of robot tissue and the research of organizing based on robot of finding the solution problems such as mechanism, how intelligent.This mechanism proposes thoughts such as distributed group organization model, announcement board, dynamic decision person and will reduce the traffic in the multi-robot system for how to solve, improves problem solving ability, improves resource utilization, better adapt to difficult problems such as dynamic environment and complicated dynamic task and represented wide prospect.
The traffic is big, resource utilization is not high, shortcomings such as the problem ability is lower are found the solution by system because the scheduling of current multirobot exists, and therefore, the design organize models adopts distributed operating strategy, resource that can the better utilization system.In new intelligence flexible dispatch group organization model and coordination mechanism, we have introduced the means of announcement board as decision maker's release task message, take to allow the robot of resource free time (ability) check that initiatively announcement board is to obtain the mode of mission bit stream, to make full use of system resource, to reduce the traffic.And adopt dynamic decision person strategy, reduce information interaction, simplify information process, better adapt to dynamic environment and complicated dynamic task.
Two, organize models:
The design's organize models wherein all comprises three parts, task management, resource management and behavior management in the dispatch group organization model of each robot and the coordination mechanism as shown in Figures 1 and 2.Each several part all can adopt prior art to be realized, it is that example describes that the design adopts the Agent technology, and the each several part function is described below respectively:
Task management Agent(TA), be task management unit 100: monitor and follow the tracks of all mission bit streams, these information comprise that priority, beginning time limit, processing time, the traffic summation with other task, current place node, task carry out required resource etc., and they can be integrated and calculate current task loading condition.Can reasonably apply for resource according to mission requirements, carry out its task.As shown in Figure 3, task management Agent(TA) comprising: mission bit stream collection module 110, all mission bit streams that are used to monitor and follow the tracks of comprise: priority, beginning time limit, processing time, the traffic summation with other task, current place node, task are carried out required resource etc.; And mission bit stream computing module 120, be used for according to all mission bit streams of collecting, with they integrate calculate current task loading condition T_load=μ 1Ui+μ 2Si+μ 3Ti+μ 4Ci+μ 5Ni+μ 6Ri+
Wherein, μ i is weights,
, specifically set according to different needs.
Resource management Agent(RA), be rm-cell 200: manage all resources relevant with processing power, generally include: the flow of controller utilization factor, instruction ready queue length, storage space, each interface and utilization factor etc., the monitoring of dynamic real-time and collect these information, and they are integrated the current resource load situation of calculating.As shown in Figure 4, resource management Agent(RA) comprising: resource information monitoring module 210, be used to manage all resources relevant, comprise: the flow of controller utilization factor, instruction ready queue length, storage space, each interface and utilization factor etc. with processing power; Resource information computing module 220 is used for the information according to dynamic real-time monitor and collection, and with they integrate calculate current resource load situation R_load=β 1Pi+β 2Li+β 3Mi+β 4Ii+β 5Ei+
Wherein, β i is weights,
, specifically set according to different needs.
Management and running Agent(SA), promptly the management and running unit 300: should have rapid reaction and communication capacity, realize the discovery and the acceptance of task, and the issue of task; Can hold consultation with other Agent, finish the overall evaluation work of ability, and provide evaluation result; Realize with the other machines people between work such as communicate by letter.Particularly after receiving an assignment, can carry out task scheduling, also can finish the disintegration of extensive task according to task issue situation.As shown in Figure 5, management and running Agent(SA) comprising: evaluation result comparison module 310, be used for self evaluation result and current decision maker's evaluation result is compared: if evaluation result is better than former decision maker, revise then that evaluation result is new evaluation result in the announcement board, replace former decision maker and become new decision maker, give notice to former decision maker,, otherwise do not participate in the competition so that former decision maker abandons the right to make decision to this task; Task ability judge module 320, be used to judge whether first Robot1 of robot possesses the ability of finishing this task: arrived uncontested person when the effective time of message, task ability judge module 320 is made a strategic decision according to its ability, and ability is enough, then carry out its task, otherwise task is decomposed; Task decomposing module 330, be used for extensive task is decomposed: arrived uncontested person when the effective time of message, first Robot1 of robot does not possess the ability of finishing this task again, then task is decomposed, carry out the part task after decomposing, and the task that will remain is handled by this scheduling coordination mechanism once more; And task release module 340, evaluation result is issued together with mission bit stream, so that the other machines people is known new information.
Three, coordination mechanism:
The new task discovery mechanism: a kind of is the new task that obtains issue, and another kind is the arrival of new task in the real world, and this mechanism is mainly born by management and running Agent.After finding new task, management and running Agent holds consultation immediately and between other Agent, finish for the pre-service of this mission bit stream and the calculating of processing power etc. by resource management Agent and task management Agent, management and running Agent then comes its ability of comprehensive evaluation according to negotiation result and in conjunction with other factors, and provides evaluation result.This process is also referred to as self and estimates, and enters the new task processing procedure afterwards.
New task processing procedure: if obtaining of task is the new task of issue, then management and running Agent need compare evaluation result and task publisher's evaluation result, if evaluation result is better than former decision maker, revise then that evaluation result is new evaluation result in the announcement board, replace former decision maker and become new decision maker, give notice to former decision maker,, otherwise do not participate in the competition so that former decision maker abandons the right to make decision to this task.
If this task directly obtains from real world, then evaluation result is issued together with mission bit stream by its management and running Agent, so that the other machines people is known new information, this robot also becomes current decision maker, and this condition of information is monitored in beginning in real time.If receive the notice that the other machines people sends, then abandon right to make decision to this task.
Decision-making mechanism: arrived uncontested person the effective time as message, and management and running Agent makes a strategic decision according to its ability, and ability is enough carried out its task; Otherwise task is decomposed, carry out the part task after decomposing, and the task that will remain is handled by this scheduling coordination mechanism once more.
Four, this model workflow simply is described below:
(1) after Robot1 finds that new task arrives, at first make self-assessment, provide evaluation result, mission bit stream is together released together with evaluation result, as shown in Figure 6, (a) task issuing process.
(2) selecting the task executor before the time arrives (being in the effective time of message), there is the robot of idling-resource (ability) to check mission bit stream, carry out self-assessment, and evaluation result and current decision maker's evaluation result compared, if this evaluation result is better than current decision maker, the evaluation result of then revising in the current task information is new evaluation result, and replace current decision maker and become new decision maker, and notify former decision maker to abandon right to make decision to this task, as shown in Figure 7, (b) executor's selection course.
(3) if task executor's selection course finishes, and this moment, the decision maker still was the discoverer Robot1 of task, and Robot1 do not possess the ability of finishing this task, then by Robot1 this task decomposed, bear part task wherein, and the task that will remain issues bulletin once more, otherwise then current decision maker becomes the task executor, the beginning task executions, and upgrade self-ability information with regard to the performance of task, and as shown in Figure 8, (C) executor's deterministic process.
Above content be in conjunction with optimal technical scheme to further describing that the present invention did, can not assert that the concrete enforcement of invention only limits to these explanations.Concerning the general technical staff of the technical field of the invention, under the prerequisite that does not break away from design of the present invention, can also make simple deduction and replacement, all should be considered as protection scope of the present invention.
Claims (8)
1. collaboration method is organized in the scheduling of a multi-robot system, may further comprise the steps:
Steps A, task issuing process: after the management and running unit (300) of first Robot1 of robot finds that new task arrives, task management unit (100), rm-cell (200) and management and running unit (300) are united and are made self-assessment, provide evaluation result, first Robot1 of robot becomes the decision maker, and management and running unit (300) together are published to announcement board Bulletin with mission bit stream together with evaluation result;
Step B, executor's selection course: selecting the task executor before the time arrives, there is the robot of idling-resource to check the mission bit stream of announcement board Bulletin, carry out self-assessment, the evaluation result comparison module (310) of management and running unit (300) compares evaluation result and current decision maker's evaluation result, if this time evaluation result is better than current decision maker's evaluation result, the evaluation result of then revising in the current task information is new evaluation result, and replacing current decision maker becomes new decision maker, and notifies former decision maker to abandon right to make decision to this task; Otherwise, abandon this task;
Step C, executor's deterministic process: if task executor's selection course finishes, and this moment, the decision maker still was discoverer first Robot1 of robot of task, the task ability judge module (320) of management and running unit (300) judges that first Robot1 of robot possesses the ability of finishing this task, then current decision maker becomes the task executor, begin task executions, and upgrade self-ability information with regard to the performance of task.
2. collaboration method is organized in the scheduling of multi-robot system according to claim 1, described step C further comprises: if task executor's selection course finishes, and this moment, the decision maker still was discoverer first Robot1 of robot of task, and first Robot1 of robot does not possess the ability of finishing this task, then this task is decomposed by the task decomposing module (330) of the management and running unit (300) of first Robot1 of robot, bear part task wherein, and the task that will remain issues bulletin once more, and repeating step A is to step C.
3. collaboration method is organized in the scheduling of multi-robot system according to claim 1, and the step of described self-assessment comprises:
At first, after management and running unit (300) find new task, hold consultation with task management unit (100) and resource management module (200) in management and running unit (300): if this task directly obtains from real world, then estimate according to the current task load information of task management unit (100) calculating and the resource load information of rm-cell (200) calculating, then evaluation result is issued together with mission bit stream by its management and running unit (300); So that the other machines people is known new information, this robot also becomes current decision maker, and this condition of information is monitored in beginning in real time;
If receive the notice that the other machines people sends, then abandon right to make decision to this task;
Secondly, task management unit (100) and resource management module (200) carry out the calculating of pre-service and processing power to current task;
Wherein, preprocessing process is: mission bit stream collection module (110) collection monitoring in task management unit (100) and all mission bit streams of tracking comprise: priority Ui, beginning time limit Si, processing time Ti, traffic summation Ci, current place node Ni with other task, the required resource Ri of task execution; Resource information monitoring module (210) dynamic collection in the resource management module (200) is the monitoring resource information relevant with processing power in real time, comprising: the flow Ii and the utilization factor Ei of controller utilization factor Pi, instruction ready queue length L i, storage space Mi, each interface;
Wherein, processing power computation process is: mission bit stream computing module (120) in task management unit (100) is according to all mission bit streams of collecting, and with they integrate calculate current task loading condition T_load=μ 1Ui+μ 2Si+μ 3Ti+μ 4Ci+μ 5Ni+μ 6Ri+
Resource information computing module (220) in the rm-cell (200) is according to the information of dynamic real-time monitor and collection, and with they integrate calculate current resource load situation R_load=β 1Pi+β 2Li+β 3Mi+β 4Ii+β 5Ei+
Wherein, μ i, β i are respectively the wherein weights of each information,
,
, occurrence can specifically be set according to different demands;
At last, management and running unit (300) according to negotiation result, and in conjunction with other factors, comprising: antistress and communication capacity, the discovery of task and the ability of acceptance, and the issue capability of task; By finishing the overall evaluation work of ability, and provide final self evaluation result F=f(T_ load with the communication negotiation of other unit, R_load ...), evaluation result F is T_ load, the function of factors such as R_load.
4. cooperative system is organized in the scheduling of a multi-robot system, it is characterized in that, described scheduling organizes cooperative system to comprise:
Task management unit (100), be used for monitoring and follow the tracks of all mission bit streams, described mission bit stream comprises priority, beginning time limit, processing time, the traffic summation with other task, current place node, the required resource of task execution, and mission bit stream integrated calculate current task loading condition, according to mission requirements, the application resource is carried out its task;
Rm-cell (200) is used to manage all resources relevant with processing power, the monitoring of dynamic real-time and collect resource information, and resource information is integrated the current resource load situation of calculating; Described resource comprises: the flow and the utilization factor of controller utilization factor, instruction ready queue length, storage space, each interface;
Management and running unit (300): be used to the discovery and the acceptance of the task that realizes, and the issue of task; Hold consultation with its task management unit (100), rm-cell (200), finish the overall evaluation work of ability, and provide evaluation result; Realize with the other machines people between communicate by letter; After receiving an assignment, can carry out task scheduling, finish the decomposition of extensive task according to task issue situation;
Described task management unit (100), rm-cell (200) and management and running unit (300) interconnect by communication interface.
5. cooperative system is organized in the scheduling of multi-robot system according to claim 4, it is characterized in that, described management and running unit (300) comprising:
Evaluation result comparison module (310), be used for self evaluation result and current decision maker's evaluation result is compared: if evaluation result is better than former decision maker, revise then that evaluation result is new evaluation result in the announcement board, replace former decision maker and become new decision maker, give notice to former decision maker, so that former decision maker abandons the right to make decision to this task, otherwise do not participate in the competition;
Task ability judge module (320), be used to judge whether first Robot1 of robot possesses the ability of finishing this task: arrived uncontested person when the effective time of message, task ability judge module (320) is made a strategic decision according to its ability, ability is enough, then carry out its task, otherwise task is decomposed;
The release module of task (340) is issued evaluation result together with mission bit stream, so that the other machines people is known new information.
6. cooperative system is organized in the scheduling of multi-robot system according to claim 5, it is characterized in that, described management and running unit (300) further comprises:
Task decomposing module (330), be used for extensive task is decomposed: arrived uncontested person when the effective time of message, first Robot1 of robot does not possess the ability of finishing this task again, then task is decomposed, carry out the part task after decomposing, and the task that will remain is handled by this scheduling coordination mechanism once more.
7. cooperative system is organized in the scheduling of multi-robot system according to claim 4, it is characterized in that, described task management unit (100) comprising:
Mission bit stream collection module (110), all mission bit streams that are used to monitor and follow the tracks of comprise: priority, beginning time limit, processing time, the traffic summation with other task, current place node, task are carried out required resource;
Mission bit stream computing module (120) is used for according to all mission bit streams of collecting, with they integrate calculate current task loading condition T_load=μ 1Ui+μ 2Si+μ 3Ti+μ 4Ci+μ 5Ni+μ 6Ri+
Wherein, μ i is weights,
, specifically set according to different needs.
8. cooperative system is organized in the scheduling of multi-robot system according to claim 4, it is characterized in that, described rm-cell (200) comprising:
Resource information monitoring module (210) is used to manage all resources relevant with processing power, comprising: the flow and the utilization factor of controller utilization factor, instruction ready queue length, storage space, each interface;
Resource information computing module (220) is used for the information according to dynamic real-time monitor and collection, and with they integrate calculate current resource load situation R_load=β 1Pi+β 2Li+β 3Mi+β 4Ii+β 5Ei+
Wherein, β i is weights,
, specifically set according to different needs.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010105997263A CN102033536B (en) | 2010-12-22 | 2010-12-22 | Scheduling, organization and cooperation system and method for multi-robot system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010105997263A CN102033536B (en) | 2010-12-22 | 2010-12-22 | Scheduling, organization and cooperation system and method for multi-robot system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102033536A true CN102033536A (en) | 2011-04-27 |
| CN102033536B CN102033536B (en) | 2012-12-26 |
Family
ID=43886548
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2010105997263A Expired - Fee Related CN102033536B (en) | 2010-12-22 | 2010-12-22 | Scheduling, organization and cooperation system and method for multi-robot system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102033536B (en) |
Cited By (36)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102499728A (en) * | 2011-12-02 | 2012-06-20 | 苏州生物医学工程技术研究所 | Medical miniature multi-robot system with self-organizing ability |
| CN102662350A (en) * | 2012-05-31 | 2012-09-12 | 东南大学 | Track teaching and planning method of master-slave mode multi-robot cooperative system |
| CN103064743A (en) * | 2012-12-27 | 2013-04-24 | 深圳先进技术研究院 | Resource scheduling method for multiple robots and resource scheduling system thereof |
| CN103176454A (en) * | 2013-02-21 | 2013-06-26 | 深圳先进技术研究院 | Clustering method and clustering system of multi-robot system |
| CN103235595A (en) * | 2013-04-27 | 2013-08-07 | 湖南科技大学 | Control system and control method of outdoor micro ground swarm robot |
| CN103324173A (en) * | 2013-06-08 | 2013-09-25 | 上海交通大学 | Multiple-heterogeneous robot cooperation method based on middleware |
| CN103399543A (en) * | 2013-07-23 | 2013-11-20 | 清华大学 | Method and system for scheduling multiple robot equipment cooperated for transferring wafers |
| WO2014101558A1 (en) * | 2012-12-27 | 2014-07-03 | 深圳先进技术研究院 | Processing method and system for controlling service amounts of multiple robots |
| CN104820621A (en) * | 2015-04-27 | 2015-08-05 | 南京大学 | Intelligent vehicle cooperation method based on distributed shared memory |
| CN105069530A (en) * | 2015-08-13 | 2015-11-18 | 肇庆学院 | Multi-robot task allocation method based on multi-objective optimization |
| CN105093934A (en) * | 2015-08-17 | 2015-11-25 | 哈尔滨工业大学 | Distributed finite time tracking control method for multi-robot system in view of interference and model uncertainty |
| CN105182828A (en) * | 2015-09-18 | 2015-12-23 | 深圳前海达闼科技有限公司 | Method and equipment for requesting assistance by equipment and responding to request for assistance by equipment |
| CN105488892A (en) * | 2016-01-04 | 2016-04-13 | 杭州亚美利嘉科技有限公司 | Method and server for robot queuing management |
| CN105553017A (en) * | 2015-12-31 | 2016-05-04 | 小米科技有限责任公司 | Robot charging system |
| CN105729491A (en) * | 2016-04-01 | 2016-07-06 | 纳恩博（北京）科技有限公司 | Executing method, device and system for robot task |
| CN106557362A (en) * | 2016-11-15 | 2017-04-05 | 北京光年无限科技有限公司 | It is applied to the task immigration method and system of intelligent robot |
| CN106777135A (en) * | 2016-05-27 | 2017-05-31 | 中科鼎富（北京）科技发展有限公司 | Service scheduling method, device and robot service system |
| CN107077651A (en) * | 2016-12-29 | 2017-08-18 | 深圳前海达闼云端智能科技有限公司 | Robot cooperation method, device, robot and computer program product |
| CN107223261A (en) * | 2016-12-07 | 2017-09-29 | 深圳前海达闼云端智能科技有限公司 | Man-machine hybrid decision method and device |
| CN107247460A (en) * | 2017-06-01 | 2017-10-13 | 三峡大学 | A kind of cluster control method and system of machine honeybee |
| CN107450491A (en) * | 2017-08-04 | 2017-12-08 | 杭州南江机器人股份有限公司 | A kind of robot scheduling system, method, electronic equipment and storage medium |
| CN108171394A (en) * | 2017-11-21 | 2018-06-15 | 中国科学院自动化研究所 | Multi-robot Task Allocation based on hierachical structure and resource consolidation |
| CN108227654A (en) * | 2017-12-28 | 2018-06-29 | 顺丰科技有限公司 | A kind of dispatch service end, dispatching device, robot system and dispatching method |
| CN108428059A (en) * | 2018-03-27 | 2018-08-21 | 昆明理工大学 | A kind of detecting robot of pipe queue forms and develops method |
| CN109240251A (en) * | 2018-11-19 | 2019-01-18 | 炬星科技（深圳）有限公司 | The scheduling decision method of distributed robot |
| CN110780651A (en) * | 2019-11-01 | 2020-02-11 | 四川长虹电器股份有限公司 | AGV dispatching system and method |
| CN111103887A (en) * | 2020-01-14 | 2020-05-05 | 大连理工大学 | Multi-sensor-based multi-mobile-robot scheduling system design method |
| CN111633655A (en) * | 2020-06-06 | 2020-09-08 | 杭州电子科技大学 | Traffic scheduling method for distributed autonomous mobile robot |
| US10953541B2 (en) | 2018-07-31 | 2021-03-23 | At&T Intellectual Property I, L.P. | Providing logistical support for robots |
| CN112990727A (en) * | 2021-03-26 | 2021-06-18 | 中国人民财产保险股份有限公司深圳市分公司 | Robot task execution control method, device, system and medium |
| WO2022012267A1 (en) * | 2020-07-17 | 2022-01-20 | 北京理工大学 | Collaboration method for multiple machining robots in hardware flexible production workshop |
| CN114089755A (en) * | 2021-11-16 | 2022-02-25 | 大连理工大学 | Multi-robot task allocation method based on consistency package algorithm |
| CN114536339A (en) * | 2022-03-03 | 2022-05-27 | 深圳市大族机器人有限公司 | Method and device for controlling cooperative robot, cooperative robot and storage medium |
| CN115113626A (en) * | 2022-07-20 | 2022-09-27 | 威康(深圳)智能有限公司 | Robot distributed control system and method thereof |
| CN116700094A (en) * | 2023-06-21 | 2023-09-05 | 哈尔滨博尼智能技术有限公司 | Data driving control system |
| US11897139B2 (en) | 2021-01-29 | 2024-02-13 | Farobot Inc. | Dynamic configuration method based on role assignation and multi-agent plan execution device |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3588405A1 (en) * | 2018-06-29 | 2020-01-01 | Tata Consultancy Services Limited | Systems and methods for scheduling a set of non-preemptive tasks in a multi-robot environment |
| TWI812923B (en) * | 2021-02-09 | 2023-08-21 | 法博智能移動股份有限公司 | Dynamic configuration method based on role assignation, electronic device, and medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004104716A1 (en) * | 2003-05-16 | 2004-12-02 | Fsi International, Inc. | Scheduling multi-robot processing systems |
| CN101551661A (en) * | 2009-05-12 | 2009-10-07 | 广东工业大学 | Control method for multi-robot system |
-
2010
- 2010-12-22 CN CN2010105997263A patent/CN102033536B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004104716A1 (en) * | 2003-05-16 | 2004-12-02 | Fsi International, Inc. | Scheduling multi-robot processing systems |
| CN101551661A (en) * | 2009-05-12 | 2009-10-07 | 广东工业大学 | Control method for multi-robot system |
Non-Patent Citations (1)
| Title |
|---|
| 《微计算机信息》 20051231 王占杰 等 "多agent动态调度控制模型" 第21卷, 第1期 * |
Cited By (59)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102499728A (en) * | 2011-12-02 | 2012-06-20 | 苏州生物医学工程技术研究所 | Medical miniature multi-robot system with self-organizing ability |
| CN102662350B (en) * | 2012-05-31 | 2013-11-27 | 东南大学 | Track teaching and planning method of master-slave mode multi-robot cooperative system |
| CN102662350A (en) * | 2012-05-31 | 2012-09-12 | 东南大学 | Track teaching and planning method of master-slave mode multi-robot cooperative system |
| CN103064743B (en) * | 2012-12-27 | 2017-09-26 | 深圳先进技术研究院 | A kind of resource regulating method and its resource scheduling system for multirobot |
| CN103064743A (en) * | 2012-12-27 | 2013-04-24 | 深圳先进技术研究院 | Resource scheduling method for multiple robots and resource scheduling system thereof |
| WO2014101558A1 (en) * | 2012-12-27 | 2014-07-03 | 深圳先进技术研究院 | Processing method and system for controlling service amounts of multiple robots |
| CN103176454A (en) * | 2013-02-21 | 2013-06-26 | 深圳先进技术研究院 | Clustering method and clustering system of multi-robot system |
| CN103176454B (en) * | 2013-02-21 | 2015-07-29 | 深圳先进技术研究院 | The cluster method of multi-robot system and system |
| CN103235595B (en) * | 2013-04-27 | 2016-03-16 | 湖南科技大学 | A kind of outdoor micro ground swarm robot control system and control method |
| CN103235595A (en) * | 2013-04-27 | 2013-08-07 | 湖南科技大学 | Control system and control method of outdoor micro ground swarm robot |
| CN103324173A (en) * | 2013-06-08 | 2013-09-25 | 上海交通大学 | Multiple-heterogeneous robot cooperation method based on middleware |
| CN103324173B (en) * | 2013-06-08 | 2015-10-28 | 上海交通大学 | Based on many heterogeneous robots collaboration method of middleware |
| CN103399543B (en) * | 2013-07-23 | 2016-03-23 | 清华大学 | The dispatching method of multiple robot devices of film trasport cooperation and system |
| CN103399543A (en) * | 2013-07-23 | 2013-11-20 | 清华大学 | Method and system for scheduling multiple robot equipment cooperated for transferring wafers |
| CN104820621A (en) * | 2015-04-27 | 2015-08-05 | 南京大学 | Intelligent vehicle cooperation method based on distributed shared memory |
| CN104820621B (en) * | 2015-04-27 | 2018-07-24 | 南京大学 | Intelligent carriage Synergistic method based on Distributed shared memory |
| CN105069530A (en) * | 2015-08-13 | 2015-11-18 | 肇庆学院 | Multi-robot task allocation method based on multi-objective optimization |
| CN105069530B (en) * | 2015-08-13 | 2019-02-26 | 肇庆学院 | A kind of multi-robot Task Allocation based on multiple-objection optimization |
| CN105093934B (en) * | 2015-08-17 | 2017-08-25 | 哈尔滨工业大学 | Consider interference and the distributed finite time tracking controller design method of multi-robot system of model uncertainty |
| CN105093934A (en) * | 2015-08-17 | 2015-11-25 | 哈尔滨工业大学 | Distributed finite time tracking control method for multi-robot system in view of interference and model uncertainty |
| CN105182828A (en) * | 2015-09-18 | 2015-12-23 | 深圳前海达闼科技有限公司 | Method and equipment for requesting assistance by equipment and responding to request for assistance by equipment |
| CN105182828B (en) * | 2015-09-18 | 2018-09-07 | 深圳前海达闼科技有限公司 | Method and equipment for requesting assistance by equipment and responding to request for assistance by equipment |
| CN105553017A (en) * | 2015-12-31 | 2016-05-04 | 小米科技有限责任公司 | Robot charging system |
| CN105488892A (en) * | 2016-01-04 | 2016-04-13 | 杭州亚美利嘉科技有限公司 | Method and server for robot queuing management |
| CN105729491A (en) * | 2016-04-01 | 2016-07-06 | 纳恩博（北京）科技有限公司 | Executing method, device and system for robot task |
| CN105729491B (en) * | 2016-04-01 | 2018-09-04 | 纳恩博（北京）科技有限公司 | The execution method, apparatus and system of robot task |
| CN106777135A (en) * | 2016-05-27 | 2017-05-31 | 中科鼎富（北京）科技发展有限公司 | Service scheduling method, device and robot service system |
| CN106557362A (en) * | 2016-11-15 | 2017-04-05 | 北京光年无限科技有限公司 | It is applied to the task immigration method and system of intelligent robot |
| CN107223261A (en) * | 2016-12-07 | 2017-09-29 | 深圳前海达闼云端智能科技有限公司 | Man-machine hybrid decision method and device |
| CN107077651A (en) * | 2016-12-29 | 2017-08-18 | 深圳前海达闼云端智能科技有限公司 | Robot cooperation method, device, robot and computer program product |
| CN107247460A (en) * | 2017-06-01 | 2017-10-13 | 三峡大学 | A kind of cluster control method and system of machine honeybee |
| CN107247460B (en) * | 2017-06-01 | 2020-08-18 | 三峡大学 | Cluster control method and system for machine bees |
| CN107450491A (en) * | 2017-08-04 | 2017-12-08 | 杭州南江机器人股份有限公司 | A kind of robot scheduling system, method, electronic equipment and storage medium |
| CN108171394A (en) * | 2017-11-21 | 2018-06-15 | 中国科学院自动化研究所 | Multi-robot Task Allocation based on hierachical structure and resource consolidation |
| CN108171394B (en) * | 2017-11-21 | 2021-02-02 | 中国科学院自动化研究所 | Multi-robot task allocation method based on layered structure and resource integration |
| CN108227654A (en) * | 2017-12-28 | 2018-06-29 | 顺丰科技有限公司 | A kind of dispatch service end, dispatching device, robot system and dispatching method |
| CN108428059A (en) * | 2018-03-27 | 2018-08-21 | 昆明理工大学 | A kind of detecting robot of pipe queue forms and develops method |
| CN108428059B (en) * | 2018-03-27 | 2021-07-16 | 昆明理工大学 | Pipeline detection robot queue forming and evolution method |
| US10953541B2 (en) | 2018-07-31 | 2021-03-23 | At&T Intellectual Property I, L.P. | Providing logistical support for robots |
| US11890757B2 (en) | 2018-07-31 | 2024-02-06 | Hyundai Motor Company | Providing logistical support for robots |
| WO2020103298A1 (en) * | 2018-11-19 | 2020-05-28 | 炬星科技（深圳）有限公司 | Distributed robot dispatch decision-making method, device and system, electronic device and storage medium |
| CN109240251A (en) * | 2018-11-19 | 2019-01-18 | 炬星科技（深圳）有限公司 | The scheduling decision method of distributed robot |
| CN109240251B (en) * | 2018-11-19 | 2024-05-14 | 炬星科技（深圳）有限公司 | Scheduling decision method of distributed robot |
| CN110780651A (en) * | 2019-11-01 | 2020-02-11 | 四川长虹电器股份有限公司 | AGV dispatching system and method |
| CN111103887B (en) * | 2020-01-14 | 2021-11-12 | 大连理工大学 | Multi-sensor-based multi-mobile-robot scheduling system design method |
| CN111103887A (en) * | 2020-01-14 | 2020-05-05 | 大连理工大学 | Multi-sensor-based multi-mobile-robot scheduling system design method |
| CN111633655A (en) * | 2020-06-06 | 2020-09-08 | 杭州电子科技大学 | Traffic scheduling method for distributed autonomous mobile robot |
| CN111633655B (en) * | 2020-06-06 | 2021-04-30 | 杭州电子科技大学 | Traffic scheduling method for distributed autonomous mobile robot |
| WO2022012267A1 (en) * | 2020-07-17 | 2022-01-20 | 北京理工大学 | Collaboration method for multiple machining robots in hardware flexible production workshop |
| US11897139B2 (en) | 2021-01-29 | 2024-02-13 | Farobot Inc. | Dynamic configuration method based on role assignation and multi-agent plan execution device |
| CN112990727A (en) * | 2021-03-26 | 2021-06-18 | 中国人民财产保险股份有限公司深圳市分公司 | Robot task execution control method, device, system and medium |
| CN114089755A (en) * | 2021-11-16 | 2022-02-25 | 大连理工大学 | Multi-robot task allocation method based on consistency package algorithm |
| CN114089755B (en) * | 2021-11-16 | 2024-02-02 | 大连理工大学 | Multi-robot task allocation method based on consistency packet algorithm |
| CN114536339A (en) * | 2022-03-03 | 2022-05-27 | 深圳市大族机器人有限公司 | Method and device for controlling cooperative robot, cooperative robot and storage medium |
| CN114536339B (en) * | 2022-03-03 | 2024-05-31 | 深圳市大族机器人有限公司 | Control method and device for cooperative robot, cooperative robot and storage medium |
| CN115113626A (en) * | 2022-07-20 | 2022-09-27 | 威康(深圳)智能有限公司 | Robot distributed control system and method thereof |
| CN115113626B (en) * | 2022-07-20 | 2023-04-11 | 威康(深圳)智能有限公司 | Robot distributed control system and method thereof |
| CN116700094A (en) * | 2023-06-21 | 2023-09-05 | 哈尔滨博尼智能技术有限公司 | Data driving control system |
| CN116700094B (en) * | 2023-06-21 | 2024-03-01 | 哈尔滨博尼智能技术有限公司 | Data driving control system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102033536B (en) | 2012-12-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102033536B (en) | Scheduling, organization and cooperation system and method for multi-robot system | |
| CN101441580B (en) | Distributed paralleling calculation platform system and calculation task allocating method thereof | |
| CN102932422B (en) | Cloud environment task scheduling method based on improved ant colony algorithm | |
| CN103838621B (en) | Method and system for scheduling routine work and scheduling nodes | |
| CN109491761A (en) | Cloud computing multiple target method for scheduling task based on EDA-GA hybrid algorithm | |
| Liu et al. | A survey on virtual machine scheduling in cloud computing | |
| CN101320329A (en) | Preemptive manpower resource collocation method and system based on task priority | |
| CN106445070B (en) | Energy consumption optimization scheduling method for hard real-time system resource-limited sporadic tasks | |
| CN105446816A (en) | Heterogeneous platform oriented energy consumption optimization scheduling method | |
| CN102075944A (en) | Multi-Agent cooperation-based available resource management system and method in cognitive network | |
| CN109783225A (en) | A kind of tenant's priority management method and system of multi-tenant big data platform | |
| CN103365711A (en) | Task scheduling mechanism and method applied to business platform of internet of Things | |
| Qing | Vehicle scheduling model of emergency logistics distribution based on internet of things | |
| Liu et al. | A framework for scheduling in cloud manufacturing with deep reinforcement learning | |
| CN108574729A (en) | A kind of intelligent transformer substation cloud system | |
| CN103268261A (en) | Hierarchical computing resource management method suitable for large-scale high-performance computer | |
| Dahal et al. | Scheduling in multiprocessor system using genetic algorithms | |
| CN109274549A (en) | Networking management method between a kind of blank pipe monitoring information processing system | |
| CN104377830B (en) | GOOSE-based intelligent micro-grid rapid control system and control strategy distribution method | |
| Zhang et al. | Design and optimization of AGV scheduling algorithm in logistics system based on convolutional neural network | |
| CN111954268A (en) | Cooperative resource reallocation method and system based on small unmanned aerial vehicle | |
| CN103034528B (en) | A kind of examination & approval of the multi-Agent based on body task data disposal route | |
| Yin et al. | Optimization of emergency logistics service capacity in the context of COVID-19 | |
| Song et al. | Efficient semi-online algorithms for multiple objects in computational offloading | |
| Li et al. | Cloud platform task scheduling strategy for power dispatching automation system based on artificial intelligence algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20121226 Termination date: 20161222 |