CN107103388A - Robot scheduling System and method for based on requirement forecasting - Google Patents
Robot scheduling System and method for based on requirement forecasting Download PDFInfo
- Publication number
- CN107103388A CN107103388A CN201710283230.7A CN201710283230A CN107103388A CN 107103388 A CN107103388 A CN 107103388A CN 201710283230 A CN201710283230 A CN 201710283230A CN 107103388 A CN107103388 A CN 107103388A
- Authority
- CN
- China
- Prior art keywords
- robot
- user
- scheduling
- density
- operation plan
- 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 25
- 238000011156 evaluation Methods 0.000 claims description 6
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 201000004569 Blindness Diseases 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000002123 temporal effect Effects 0.000 description 4
- 230000005540 biological transmission 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
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
System and method for is dispatched the invention discloses a kind of robot based on requirement forecasting, the program is dispatched robot in place before user is sent using request using data and priori according to user, is shortened user and is used the reservation needed for robot and stand-by period；Meanwhile, in real time according to the prediction of user's request, the distribution of dynamic dispatching robot reduces the situation of the reservations to be serviced such as robot blindness, improves the service efficiency of robot.
Description
Technical field
The present invention relates to robot dispatching technique field, more particularly to a kind of scheduling system of robot based on requirement forecasting
System.
Background technology
As technology develops the change with population structure, robot will progress into daily life.For towards
The robot of public service is, it is necessary to which a scheduling system arranges the stroke and task of robot.Traditional scheduling system of robot
System often relies on the service request (reservation) of user's transmission or fixed operational plan is scheduled arrangement.
But, the scheduling system for asking (reservation) based on user could can only be carried out after user's request issue to robot
Scheduling, causes user to wait robot in place or needs the time course of user " searching " robot.This mode can cause service
Not in time or need substantial amounts of robot to carry out dense deployment, cause the wasting of resources.
The content of the invention
System and method for is dispatched it is an object of the invention to provide a kind of robot based on requirement forecasting, by making to user
With the prediction of robot demand, prior to user's request, robot is dispatched to the objective of user's needs, user is met to machine
Device people service instant demand, realize robot " etc. " people.
The purpose of the present invention is achieved through the following technical solutions：
A kind of robot scheduling system based on requirement forecasting, including：Lexical analysis module, scheduling performing module and scheduling
Study module；Wherein：
The lexical analysis module, for generating corresponding tune according to scheduled events, user density and/or reserve requests
Degree plan, and the scheduling result fed back according to scheduling performing module form new operation plan in real time；
The scheduling performing module, for carrying out dynamic dispatching to robot according to the operation plan received, and will be adjusted
Degree result feeds back to lexical analysis module and scheduling study module；
The scheduling study module, for being analyzed according to scheduling result and robot instream factor, excavates and improves
The dispatching method and robot distribution scheme of robot instream factor, and then Optimized Operation analysis module.
The course of work of the lexical analysis module is as follows：
Robot distribution initialization：According to the historical data of robot operation and priori build robot in space and
Temporal initialization distribution；
Corresponding operation plan is generated according to scheduled events, user density and/or reserve requests：A, according to scheduled events
Robot distribution is adjusted：When lexical analysis module receives the scheduled events that robot may be influenceed to use, according to right
The participation number of scheduled events and robot usage quantity is estimated, utilization rate will be estimated in advance less than first threshold area
Robot is formulated to scheduled events desired zone, forms corresponding first operation plan；B, according to the targeted customer's serviced
Density is adjusted to robot distribution：When that can be predicted using historical data to user using the probability of robot,
The region for being higher than the 3rd threshold value using probability will be dispatched in the robot for being less than Second Threshold region using probability, makes scheduling
Back zone intra domain user uses probability density and robot density matching；When can not be predicted to user using the probability of robot
When, it is defaulted as each user and uses the probability of robot equal, now user is equal with user's crowd density using probability density,
The region for being higher than the 3rd threshold value using probability will be dispatched in the robot for being less than Second Threshold region using probability, makes scheduling
Back zone intra domain user uses probability density and robot density matching；According to aforesaid way, corresponding second operation plan is formed；
C, according to the reserve requests of user robot distribution is adjusted：When the robot that lexical analysis module receives user is invited in advance
When asking, neighbouring robot is dispatched to the reservation destination of user, now, asked according to user, formed the corresponding 3rd and adjust
Degree plan；
Global assessment：According to above-mentioned first operation plan, the second operation plan and/or the 3rd operation plan, machine is formed
People is expected distribution；Global robot Evaluation on distribution is carried out, each zone user is calculated using the ratio between probability density and robot density,
Mobile state of going forward side by side is adjusted, and the ratio of regional is in target interval, is re-formed final operation plan and export to scheduling
Performing module.
The machine artificially has the Mechatronic Systems of autonomous ability, including：Robot, unmanned vehicle, unmanned plane and nothing
People's ship.
A kind of robot dispatching method based on requirement forecasting, this method based on aforementioned system realize, including：
Lexical analysis is generated with operation plan：Generated according to scheduled events, user density and/or reserve requests corresponding
Operation plan, and new operation plan is formed according to the scheduling result of feedback in real time；
Scheduling is performed：Dynamic dispatching, and outwards output scheduling result are carried out to robot according to the operation plan received；
Scheduling study：Analyzed according to scheduling result and robot instream factor, excavate and improve that robot is actual makes
With the dispatching method and robot distribution scheme of rate, and then Optimized Operation analysis and operation plan generating process.
The lexical analysis and the course of work that operation plan is generated are as follows：
Robot distribution initialization：According to the historical data of robot operation and priori build robot in space and
Temporal initialization distribution；
Corresponding operation plan is generated according to scheduled events, user density and/or reserve requests：A, according to scheduled events
Robot distribution is adjusted：When lexical analysis module receives the scheduled events that robot may be influenceed to use, according to right
The participation number of scheduled events and robot usage quantity is estimated, utilization rate will be estimated in advance less than first threshold area
Robot is formulated to scheduled events desired zone, forms corresponding first operation plan；B, according to the targeted customer's serviced
Density is adjusted to robot distribution：When that can be predicted using historical data to user using the probability of robot,
The region for being higher than the 3rd threshold value using probability will be dispatched in the robot for being less than Second Threshold region using probability, makes scheduling
Back zone intra domain user uses probability density and robot density matching；When can not be predicted to user using the probability of robot
When, it is defaulted as each user and uses the probability of robot equal, now user is equal with user's crowd density using probability density,
The region for being higher than the 3rd threshold value using probability will be dispatched in the robot for being less than Second Threshold region using probability, makes scheduling
Back zone intra domain user uses probability density and robot density matching；According to aforesaid way, corresponding second operation plan is formed；
C, according to the reserve requests of user robot distribution is adjusted：When the robot that lexical analysis module receives user is invited in advance
When asking, neighbouring robot is dispatched to the reservation destination of user, now, asked according to user, formed the corresponding 3rd and adjust
Degree plan；
Global assessment：According to above-mentioned first operation plan, the second operation plan and/or the 3rd operation plan, machine is formed
People is expected distribution；Global robot Evaluation on distribution is carried out, each zone user is calculated using the ratio between probability density and robot density,
Mobile state of going forward side by side is adjusted, and the ratio of regional is in target interval, is re-formed final operation plan and export to scheduling
Performing module.
The machine artificially has the Mechatronic Systems of autonomous ability, including：Robot, unmanned vehicle, unmanned plane and nothing
People's ship.
As seen from the above technical solution provided by the invention, the program is existed according to user using data and priori
User is sent using dispatching robot in place before request, is shortened user and is used the reservation needed for robot and stand-by period；
Meanwhile, in real time according to the prediction of user's request, the distribution of dynamic dispatching robot reduces the feelings of the reservations to be serviced such as robot blindness
Condition, improves the service efficiency of robot.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, being used required in being described below to embodiment
Accompanying drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for this
For the those of ordinary skill in field, on the premise of not paying creative work, other can also be obtained according to these accompanying drawings
Accompanying drawing.
Fig. 1 dispatches the schematic diagram of system for the robot provided in an embodiment of the present invention based on requirement forecasting；
Fig. 2 dispatches the workflow diagram of system for the robot provided in an embodiment of the present invention based on requirement forecasting；
Fig. 3 is the workflow diagram of lexical analysis module provided in an embodiment of the present invention；
Fig. 4 is the flow chart of the robot dispatching method provided in an embodiment of the present invention based on requirement forecasting.
Embodiment
With reference to the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.Based on this
The embodiment of invention, the every other implementation that those of ordinary skill in the art are obtained under the premise of creative work is not made
Example, belongs to protection scope of the present invention.
Fig. 1 dispatches the schematic diagram of system for the robot provided in an embodiment of the present invention based on requirement forecasting.Such as Fig. 1 institutes
Show, it mainly includes：Lexical analysis module, scheduling performing module and scheduling study module.
As shown in Fig. 2 the function and the course of work of system modules are as follows：
1st, lexical analysis module.Corresponding scheduling meter is generated according to scheduled events, user density and/or reserve requests
Draw, and the scheduling result fed back according to scheduling performing module forms new operation plan in real time.
2nd, performing module is dispatched.Dynamic dispatching is carried out to robot according to the operation plan received, and by scheduling result
Feed back to lexical analysis module and scheduling study module.
In the embodiment of the present invention, described robot includes but is not limited to any electromechanical system with autonomous ability
System, such as robot, unmanned vehicle, unmanned plane, unmanned boat etc..
3rd, study module is dispatched.Analyzed according to scheduling result and robot instream factor, excavate and improve robot
The dispatching method and robot distribution scheme of instream factor, and then Optimized Operation analysis module.Optimized Operation analysis herein
Module can be scheduled for analysis module comprising the initialization distribution for improving robot and use.
In the embodiment of the present invention, lexical analysis module can carry out analysis in real time with scheduling performing module and perform operation,
That is, the distribution situation to robot is adjusted in real time, to reduce the situation of the reservations to be serviced such as robot blindness, is carried
The service efficiency of Gao Liao robots.
In the embodiment of the present invention, the course of work of lexical analysis module is as shown in figure 3, main include following several parts：
1st, robot distribution initialization：Robot is built in space according to the historical data of robot operation and priori
With temporal initialization distribution.
2nd, corresponding operation plan is generated according to scheduled events, user density and/or reserve requests：
A, event anticipation adjustment.
Robot distribution is adjusted according to scheduled events：Robot may be influenceed to use when lexical analysis module is received
Scheduled events when, estimated according to the participation number to scheduled events and to robot usage quantity, will estimate use in advance
Rate is formulated to scheduled events desired zone less than the robot in first threshold area, forms corresponding first operation plan.
B, user density adjustment.
Robot distribution is adjusted according to the density of the targeted customer serviced：When can using historical data to
(such as it is predicted), will be located by the use habit historical data of registered user when family is predicted using the probability of robot
Use probability higher than the region of the 3rd threshold value in being dispatched to using probability less than the robot in Second Threshold region, make scheduling back zone
Intra domain user uses probability density and robot density matching；When that can not be predicted to user using the probability of robot,
It is defaulted as each user equal using the probability of robot, now user is equal with user's crowd density using probability density, will
Use probability higher than the region of the 3rd threshold value in being dispatched to using probability less than the robot in Second Threshold region, make after scheduling
Area's intra domain user uses probability density and robot density matching；According to aforesaid way, corresponding second operation plan is formed.
C, reserve requests adjustment.
Robot distribution is adjusted according to the reserve requests of user：When lexical analysis module receives the robot of user
During reserve requests, neighbouring robot is dispatched to the reservation destination of user, now, asked according to user, form corresponding
3rd operation plan.
It will be understood by those skilled in the art that above-mentioned first threshold, Second Threshold, the 3rd threshold value can be set according to demand
It is fixed, meanwhile, it is only used for identifying different operation plans on first, second, third before operation plan, is not construed as limiting.
In addition, above-mentioned list three kinds of operation plans, one kind can be only occurred in which in a practical situation, naturally it is also possible to occurred simultaneously
Above-mentioned three kinds.
3rd, global assessment：According to above-mentioned first operation plan, the second operation plan and/or the 3rd operation plan, machine is formed
Device people is expected distribution；Carry out global robot Evaluation on distribution, calculate each zone user using probability density and robot density it
Than Mobile state of going forward side by side adjustment makes the ratio of regional be in target interval, re-forms final operation plan and export to tune
Spend performing module.
Said system provided in an embodiment of the present invention, sends to use and asks using data and priori according to user in user
Before asking by robot scheduling in place, shorten user and use the reservation needed for robot and stand-by period；Meanwhile, in real time according to
The prediction of family demand, dynamic dispatching robot distribution reduces the situation of the reservations to be serviced such as robot blindness, improves robot
Service efficiency.
It is apparent to those skilled in the art that, for convenience and simplicity of description, only with above-mentioned each function
The division progress of module is for example, in practical application, as needed can distribute above-mentioned functions by different function moulds
Block is completed, i.e., the internal structure of system is divided into different functional modules, to complete all or part of work(described above
Energy.
Another embodiment of the present invention also provides a kind of robot dispatching method based on requirement forecasting, and this method is based on foregoing
The system that embodiment is provided is realized, as shown in figure 4, it mainly comprises the following steps：
Lexical analysis is generated with operation plan：Generated according to scheduled events, user density and/or reserve requests corresponding
Operation plan, and new operation plan is formed according to the scheduling result of feedback in real time；
Scheduling is performed：Dynamic dispatching, and outwards output scheduling result are carried out to robot according to the operation plan received；
Scheduling study：Analyzed according to scheduling result and robot instream factor, excavate and improve that robot is actual makes
With the dispatching method and robot distribution scheme of rate, and then Optimized Operation analysis and operation plan generating process.
In the embodiment of the present invention, the lexical analysis and the course of work that operation plan is generated are as follows：
Robot distribution initialization：According to the historical data of robot operation and priori build robot in space and
Temporal initialization distribution；
Corresponding operation plan is generated according to scheduled events, user density and/or reserve requests：A, according to scheduled events
Robot distribution is adjusted：When lexical analysis module receives the scheduled events that robot may be influenceed to use, according to right
The participation number of scheduled events and robot usage quantity is estimated, utilization rate will be estimated in advance less than first threshold area
Robot is formulated to scheduled events desired zone, forms corresponding first operation plan；B, according to the targeted customer's serviced
Density is adjusted to robot distribution：When that can be predicted using historical data to user using the probability of robot,
The region for being higher than the 3rd threshold value using probability will be dispatched in the robot for being less than Second Threshold region using probability, makes scheduling
Back zone intra domain user uses probability density and robot density matching；When can not be predicted to user using the probability of robot
When, it is defaulted as each user and uses the probability of robot equal, now user is equal with user's crowd density using probability density,
The region for being higher than the 3rd threshold value using probability will be dispatched in the robot for being less than Second Threshold region using probability, makes scheduling
Back zone intra domain user uses probability density and robot density matching；According to aforesaid way, corresponding second operation plan is formed；
C, according to the reserve requests of user robot distribution is adjusted：When the robot that lexical analysis module receives user is invited in advance
When asking, neighbouring robot is dispatched to the reservation destination of user, now, asked according to user, formed the corresponding 3rd and adjust
Degree plan；
Global assessment：According to above-mentioned first operation plan, the second operation plan and/or the 3rd operation plan, machine is formed
People is expected distribution；Global robot Evaluation on distribution is carried out, each zone user is calculated using the ratio between probability density and robot density,
Mobile state of going forward side by side is adjusted, and the ratio of regional is in target interval, is re-formed final operation plan and export to scheduling
Performing module.
Retouched in detail it should be noted that the specific implementation in the above method has had in system embodiment above
State, therefore repeat no more herein.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment can
To be realized by software, the mode of necessary general hardware platform can also be added to realize by software.Understood based on such,
The technical scheme of above-described embodiment can be embodied in the form of software product, the software product can be stored in one it is non-easily
The property lost storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in, including some instructions are to cause a computer to set
Standby (can be personal computer, server, or network equipment etc.) performs the method described in each embodiment of the invention.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art is in the technical scope of present disclosure, the change or replacement that can be readily occurred in,
It should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claims
Enclose and be defined.
Claims (6)
1. a kind of robot scheduling system based on requirement forecasting, it is characterised in that including：Lexical analysis module, scheduling are performed
Module and scheduling study module；Wherein：
The lexical analysis module, based on corresponding scheduling is generated according to scheduled events, user density and/or reserve requests
Draw, and the scheduling result fed back according to scheduling performing module forms new operation plan in real time；
The scheduling performing module, for carrying out dynamic dispatching to robot according to the operation plan received, and scheduling is tied
Fruit feeds back to lexical analysis module and scheduling study module；
The scheduling study module, for being analyzed according to scheduling result and robot instream factor, excavates and improves machine
The dispatching method and robot distribution scheme of people's instream factor, and then Optimized Operation analysis module.
2. a kind of robot scheduling system based on requirement forecasting according to claim 1, it is characterised in that the scheduling
The course of work of analysis module is as follows：
Robot distribution initialization：Robot is built in room and time according to the historical data of robot operation and priori
On initialization distribution；
Corresponding operation plan is generated according to scheduled events, user density and/or reserve requests：A, according to scheduled events to machine
Device people distribution is adjusted：When lexical analysis module receives the scheduled events that robot may be influenceed to use, according to plan
The participation number of event and robot usage quantity is estimated, machine of the utilization rate less than first threshold area will be estimated in advance
People is formulated to scheduled events desired zone, forms corresponding first operation plan；B, the density according to the targeted customer serviced
Robot distribution is adjusted：When that can be predicted using historical data to user using the probability of robot, it will locate
Use probability higher than the region of the 3rd threshold value in being dispatched to using probability less than the robot in Second Threshold region, make scheduling back zone
Intra domain user uses probability density and robot density matching；When that can not be predicted to user using the probability of robot,
It is defaulted as each user equal using the probability of robot, now user is equal with user's crowd density using probability density, will
Use probability higher than the region of the 3rd threshold value in being dispatched to using probability less than the robot in Second Threshold region, make after scheduling
Area's intra domain user uses probability density and robot density matching；According to aforesaid way, corresponding second operation plan is formed；c、
Robot distribution is adjusted according to the reserve requests of user：When lexical analysis module receives the robot reserve requests of user
When, neighbouring robot is dispatched to the reservation destination of user, now, asked according to user, corresponding 3rd scheduling is formed
Plan；
Global assessment：According to above-mentioned first operation plan, the second operation plan and/or the 3rd operation plan, robot is formed pre-
Phase is distributed；Global robot Evaluation on distribution is carried out, each zone user is calculated using the ratio between probability density and robot density, goes forward side by side
Mobile state adjust, make regional ratio be in target interval in, re-form final operation plan export to scheduling perform
Module.
3. a kind of robot scheduling system based on requirement forecasting according to claim 1, it is characterised in that the machine
The artificial Mechatronic Systems with autonomous ability, including：Robot, unmanned vehicle, unmanned plane and unmanned boat.
4. a kind of robot dispatching method based on requirement forecasting, it is characterised in that this method is based on described in claim 1 or 2
System realize, including：
Lexical analysis is generated with operation plan：Corresponding scheduling is generated according to scheduled events, user density and/or reserve requests
Plan, and new operation plan is formed according to the scheduling result of feedback in real time；
Scheduling is performed：Dynamic dispatching, and outwards output scheduling result are carried out to robot according to the operation plan received；
Scheduling study：Analyzed according to scheduling result and robot instream factor, excavate and improve robot instream factor
Dispatching method and robot distribution scheme, and then Optimized Operation analysis with operation plan generating process.
5. a kind of robot dispatching method based on requirement forecasting according to claim 4, it is characterised in that the scheduling
Analyze the course of work generated with operation plan as follows：
Robot distribution initialization：Robot is built in room and time according to the historical data of robot operation and priori
On initialization distribution；
Corresponding operation plan is generated according to scheduled events, user density and/or reserve requests：A, according to scheduled events to machine
Device people distribution is adjusted：When lexical analysis module receives the scheduled events that robot may be influenceed to use, according to plan
The participation number of event and robot usage quantity is estimated, machine of the utilization rate less than first threshold area will be estimated in advance
People is formulated to scheduled events desired zone, forms corresponding first operation plan；B, the density according to the targeted customer serviced
Robot distribution is adjusted：When that can be predicted using historical data to user using the probability of robot, it will locate
Use probability higher than the region of the 3rd threshold value in being dispatched to using probability less than the robot in Second Threshold region, make scheduling back zone
Intra domain user uses probability density and robot density matching；When that can not be predicted to user using the probability of robot,
It is defaulted as each user equal using the probability of robot, now user is equal with user's crowd density using probability density, will
Use probability higher than the region of the 3rd threshold value in being dispatched to using probability less than the robot in Second Threshold region, make after scheduling
Area's intra domain user uses probability density and robot density matching；According to aforesaid way, corresponding second operation plan is formed；c、
Robot distribution is adjusted according to the reserve requests of user：When lexical analysis module receives the robot reserve requests of user
When, neighbouring robot is dispatched to the reservation destination of user, now, asked according to user, corresponding 3rd scheduling is formed
Plan；
Global assessment：According to above-mentioned first operation plan, the second operation plan and/or the 3rd operation plan, robot is formed pre-
Phase is distributed；Global robot Evaluation on distribution is carried out, each zone user is calculated using the ratio between probability density and robot density, goes forward side by side
Mobile state adjust, make regional ratio be in target interval in, re-form final operation plan export to scheduling perform
Module.
6. a kind of robot dispatching method based on requirement forecasting according to claim 4, it is characterised in that the machine
The artificial Mechatronic Systems with autonomous ability, including：Robot, unmanned vehicle, unmanned plane and unmanned boat.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710283230.7A CN107103388B (en) | 2017-04-26 | 2017-04-26 | Robot scheduling system and method based on demand prediction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710283230.7A CN107103388B (en) | 2017-04-26 | 2017-04-26 | Robot scheduling system and method based on demand prediction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107103388A true CN107103388A (en) | 2017-08-29 |
| CN107103388B CN107103388B (en) | 2021-02-05 |
Family
ID=59658196
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710283230.7A Expired - Fee Related CN107103388B (en) | 2017-04-26 | 2017-04-26 | Robot scheduling system and method based on demand prediction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107103388B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108717549A (en) * | 2018-04-26 | 2018-10-30 | 东华大学 | Crowd density analysis method based on unmanned plane vision and support vector cassification |
| CN109035747A (en) * | 2018-06-12 | 2018-12-18 | 北京拜思克科技有限公司 | A kind of intelligent family moving platform system and its traffic control method |
| CN109686087A (en) * | 2018-12-28 | 2019-04-26 | 西安艾润物联网技术服务有限责任公司 | The management method and device of patrol robot |
| CN111552260A (en) * | 2020-07-10 | 2020-08-18 | 炬星科技（深圳）有限公司 | Worker position estimation method, worker position estimation device, and storage medium |
| CN116468213A (en) * | 2023-03-07 | 2023-07-21 | 杭州城市大脑有限公司 | Personnel information matching and calling method based on urban brain |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103177334A (en) * | 2013-03-01 | 2013-06-26 | 深圳先进技术研究院 | Method and system for scheduling robot resources |
| CN104077915A (en) * | 2014-03-27 | 2014-10-01 | 中华电信股份有限公司 | Riding trend prediction device and method |
| JP2014527246A (en) * | 2011-09-17 | 2014-10-09 | ナラヤン、アミット | Load forecast from individual customer to system level |
| CN105719019A (en) * | 2016-01-21 | 2016-06-29 | 华南理工大学 | Public bicycle peak time demand prediction method considering user reservation data |
| CN106355345A (en) * | 2016-09-08 | 2017-01-25 | 京东方科技集团股份有限公司 | Intelligent dispatching system and method of automatic vending robots |
| CN106503869A (en) * | 2016-11-14 | 2017-03-15 | 东南大学 | A kind of public bicycles dynamic dispatching method that is predicted based on website short-term needs |
-
2017
- 2017-04-26 CN CN201710283230.7A patent/CN107103388B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014527246A (en) * | 2011-09-17 | 2014-10-09 | ナラヤン、アミット | Load forecast from individual customer to system level |
| CN103177334A (en) * | 2013-03-01 | 2013-06-26 | 深圳先进技术研究院 | Method and system for scheduling robot resources |
| CN104077915A (en) * | 2014-03-27 | 2014-10-01 | 中华电信股份有限公司 | Riding trend prediction device and method |
| CN105719019A (en) * | 2016-01-21 | 2016-06-29 | 华南理工大学 | Public bicycle peak time demand prediction method considering user reservation data |
| CN106355345A (en) * | 2016-09-08 | 2017-01-25 | 京东方科技集团股份有限公司 | Intelligent dispatching system and method of automatic vending robots |
| CN106503869A (en) * | 2016-11-14 | 2017-03-15 | 东南大学 | A kind of public bicycles dynamic dispatching method that is predicted based on website short-term needs |
Non-Patent Citations (1)
| Title |
|---|
| 沈博闻，于宁波，刘景泰: "仓储物流机器人集群的智能调度和路径规划", 《智能系统学报》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108717549A (en) * | 2018-04-26 | 2018-10-30 | 东华大学 | Crowd density analysis method based on unmanned plane vision and support vector cassification |
| CN109035747A (en) * | 2018-06-12 | 2018-12-18 | 北京拜思克科技有限公司 | A kind of intelligent family moving platform system and its traffic control method |
| CN109035747B (en) * | 2018-06-12 | 2020-12-22 | 北京拜思克科技有限公司 | Intelligent mobile platform system and operation scheduling method thereof |
| CN109686087A (en) * | 2018-12-28 | 2019-04-26 | 西安艾润物联网技术服务有限责任公司 | The management method and device of patrol robot |
| CN111552260A (en) * | 2020-07-10 | 2020-08-18 | 炬星科技（深圳）有限公司 | Worker position estimation method, worker position estimation device, and storage medium |
| CN116468213A (en) * | 2023-03-07 | 2023-07-21 | 杭州城市大脑有限公司 | Personnel information matching and calling method based on urban brain |
| CN116468213B (en) * | 2023-03-07 | 2023-10-27 | 杭州城市大脑有限公司 | Personnel information matching and calling method based on urban brain |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107103388B (en) | 2021-02-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107103388A (en) | Robot scheduling System and method for based on requirement forecasting | |
| CN111932027B (en) | Cloud service comprehensive scheduling optimization system and method fusing edge facilities | |
| CN110825520B (en) | Cluster extremely-fast elastic telescoping method for realizing efficient resource utilization | |
| Amberg et al. | Robust efficiency in urban public transportation: Minimizing delay propagation in cost-efficient bus and driver schedules | |
| CN109343939B (en) | Distributed cluster and parallel computing task scheduling method | |
| CN1773539A (en) | System and method for managing one or more computing resources utilizing computing center | |
| CN109766175A (en) | Resource elastic telescopic system and its dispatching method towards high-performance calculation on cloud | |
| CN104731657B (en) | A kind of resource regulating method and system | |
| US20050246208A1 (en) | Using software agents to schedule airline flights | |
| CN106209967B (en) | A kind of video monitoring cloud resource prediction technique and system | |
| JP2017515244A (en) | System and method for providing on-site service | |
| CN109343945A (en) | A kind of multitask dynamic allocation method based on contract net algorithm | |
| CN110196773B (en) | Multi-time-scale security check system and method for unified scheduling computing resources | |
| CN109377063A (en) | A kind of method for scheduling task, device, equipment and storage medium | |
| CN108833294B (en) | Low-bandwidth-overhead flow scheduling method for data center wide area network | |
| Liu et al. | RFID: Towards low latency and reliable DAG task scheduling over dynamic vehicular clouds | |
| Kalyaev et al. | Method of multiagent scheduling of resources in cloud computing environments | |
| CN108762899A (en) | A kind of cloud task rescheduling method and apparatus | |
| Liu et al. | Globally-optimized realtime supply-demand matching in on-demand ridesharing | |
| CN117591285A (en) | Computing power resource scheduling and distributing system and method | |
| CN106227597A (en) | Task priority treating method and apparatus | |
| CN110535670B (en) | NFV capacity planning method and electronic equipment | |
| CN106936905B (en) | Openstack-based scheduling method and scheduling system of Nova component virtual machine | |
| CN114172814A (en) | Method for constructing intention-driven satellite network resource management three-way model and application | |
| CN109039694A (en) | A kind of the global network resource allocation methods and device of service-oriented |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210205 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |