CN109669462A - Intelligent planning method and system - Google Patents
Intelligent planning method and system Download PDFInfo
- Publication number
- CN109669462A CN109669462A CN201910019184.9A CN201910019184A CN109669462A CN 109669462 A CN109669462 A CN 109669462A CN 201910019184 A CN201910019184 A CN 201910019184A CN 109669462 A CN109669462 A CN 109669462A
- Authority
- CN
- China
- Prior art keywords
- robot
- description
- parameter
- package
- storage
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 64
- 238000004891 communication Methods 0.000 claims description 4
- 241000208340 Araliaceae Species 0.000 claims description 3
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 claims description 3
- 235000003140 Panax quinquefolius Nutrition 0.000 claims description 3
- 235000008434 ginseng Nutrition 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims 1
- 238000013473 artificial intelligence Methods 0.000 abstract description 2
- 230000000694 effects Effects 0.000 description 23
- 230000008569 process Effects 0.000 description 16
- 238000010586 diagram Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 10
- 230000008859 change Effects 0.000 description 5
- 230000006399 behavior Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 235000017274 Diospyros sandwicensis Nutrition 0.000 description 1
- 241000282838 Lama Species 0.000 description 1
- 229940110339 Long-acting muscarinic antagonist Drugs 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 235000003642 hunger Nutrition 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
- G05D1/0253—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting relative motion information from a plurality of images taken successively, e.g. visual odometry, optical flow
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/028—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using a RF signal
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network
Abstract
The embodiment of the application provides an intelligent planning method and system, relates to the technical field of artificial intelligence, and can realize global scheduling of multiple robots from a macroscopic level through an intelligent planning method, and meanwhile, the distance between the robots and packages is considered and the priorities are correspondingly set, so that all the robots can effectively perform cooperative work, an optimal scheme is adopted to complete warehousing operation tasks, and logistics cost is effectively reduced. In addition, the field description related to the method and the system is a general model for describing the warehousing scene, the model can be generally used repeatedly after being created, and the problem description only needs to be modified for specific warehousing problems by a user in few cases, so that the method and the system have good portability and expandability compared with the existing planning method, and the warehousing problems can be efficiently planned.
Description
Technical field
The present invention relates to field of artificial intelligence, in particular to a kind of Intelligent planning method and system.
Background technique
With the rapid development of e-commerce, it is more that traditional warehouse logistics can not adapt to modern logistics batch, and batch is small,
Period short feature.The application of warehouse logistics robot can effectively improve logistic efficiency.
The research of warehouse logistics robot is focused primarily upon using two dimensional code, RFID and indoor GPS technology pair at present
The planning of stand-alone machines people's travel path.The technologies such as ground two-dimensional code or range sensor are relied primarily on to avoid the collision of robot
Conflict, and corresponding solution is then lacked for multirobot collaborative work, and be when planning robot travel path
Stochastic programming can not cope with complicated situation, and the quality of the low efficiency and program results that lead to planning is low.
Summary of the invention
In a first aspect, the embodiment of the invention provides a kind of Intelligent planning methods, which comprises obtain storage field
Field description, the field be described as the domain knowledge based on the storage field building for describe store in a warehouse scene mould
Type；The problem of obtaining storage problem to be planned description, the storage problem are using the robot in warehouse to the warehouse
In package the problem of being handled, described problem description includes for the different distance between the robot and the package
The different priorities being correspondingly arranged；Field description is input to planner with described problem description to plan, is generated complete
Office's planning solution；The programming dispatching sequence of the robot is extracted from the Global motion planning solution and by the programming dispatching sequence
It is sent to the robot.
During above-mentioned realization, then the field description in acquisition storage field first obtains storage problem to be planned
The problem of describe, field is described later and description is input to planner the problem of including priority, using in planner
Planning algorithm carries out Global motion planning to storage problem, obtains Global motion planning solution, finally sends out the schedule sequences in Global motion planning solution
Send to robot, so that robot executes corresponding movement according to schedule sequences, complete storehouse warehousing and storage activities task, so as to from
Macroscopic aspect is realized to the overall scheduling of multirobot, can effectively be cooperated, and completes warehousing and storage activities task, has
Effect reduces logistics cost.In addition, the description of field involved in the above method and system is the Universal Die for describing storage scene
Type, usually it can be used repeatedly after creation for the model, it is seldom necessary to which the case where modifying, user only need for specific storage
Problem modifies problem description, therefore the above method and system have a good portable and scalability, and can be with
The planning to storage problem is efficiently completed, and then the efficiency and program results quality of planning can be improved.
Further, described the problem of obtaining storage problem to be planned, describes, comprising: the landform for obtaining the warehouse is retouched
It states, the topograph includes the positional relationship between the functional area and each functional area in the warehouse；Obtain the machine
The original state of the original state of device people and/or the package；By the topograph and the original state of the robot
And/or the original state of the package is determined as the original state of described problem description；Obtain the dbjective state of the robot
And/or the dbjective state of the package；The dbjective state of the dbjective state of the robot and/or the package is determined as institute
State the dbjective state of problem description.
During above-mentioned realization, problem description includes the topograph in warehouse, can entire landform to warehouse and
Situations such as functional area, carries out detailed embodiment, the original state of the original state and/or package of topograph and robot
It is determined as the original state of problem description, can accurately grasps the original state in storage problem to be planned.
Further, described the problem of obtaining storage problem to be planned, describes, further includes: obtains described problem description
The corresponding original state parameter of original state, wherein the original state parameter includes priority parameters, threshold parameter and dynamic
Parameter.
During above-mentioned realization, need to obtain the corresponding original state parameter of original state of problem description, initial shape
State parameter can specifically be embodied original state by way of data, and can pass through the meter to original state parameter
The modes such as calculation, to realize the control of the original state to problem description.
Further, described the problem of obtaining storage problem to be planned, describes, further includes: obtains described problem description
The corresponding dbjective state parameter of dbjective state, wherein the dbjective state parameter includes multiple essential dbjective state parameters and more
A optional dbjective state parameter.
During above-mentioned realization, need to obtain the corresponding dbjective state parameter of dbjective state of problem description, target-like
The corresponding dbjective state parameter of state can be showed original state by specific data, and in planning process, mesh
The setting of mark state parameter can make planning procedure realize the solution of local solution, realize the flexibility of planning.
Further, described that field description and described problem description are input to planner and plan, it generates entirely
Office planning solution after, further includes: judge the Global motion planning solution whether be meet the multiple essential dbjective state parameter and
The multiple optional dbjective state parameter, if so, showing that the Global motion planning solution is global solution；Judge the Global motion planning solution
For the optional dbjective state in part for meeting the multiple essential dbjective state parameter and the multiple optional dbjective state parameter
Parameter, if so, showing that the Global motion planning solution is local solution.
Further, the field description and described problem description are described by PDDL language, in the neck
Institute object, predicate and movement to be used in the description of statement described problem in the description of domain.
Second aspect, the embodiment of the invention provides a kind of small watersheds, comprising: host and logical with the host
Believe that the robot of connection, the robot are arranged in warehouse；The host is used to obtain the field description in storage field, and
The problem of obtaining storage problem to be planned description, and field description is input to planner with described problem description and is carried out
Planning generates Global motion planning solution, the programming dispatching sequence of the robot is extracted from the Global motion planning solution and will be described
Programming dispatching sequence is sent to the robot, wherein the field is described as the domain knowledge structure based on the storage field
That builds is used to describe the model of storage scene, and the storage problem is using the robot in warehouse to the package in the warehouse
The problem of being handled, described problem description include being correspondingly arranged for the different distance between the robot and the package
Different priorities；The robot is used to execute corresponding movement based on the schedule sequences, completes the storage problem pair
The warehousing and storage activities task answered.
Further, the host is used to obtain the topograph in the warehouse, and obtains the initial of the robot
The original state of state and/or the package, and by the original state and/or institute of the topograph and the robot
The original state for stating package is determined as the original state of described problem description, wherein the topograph includes the warehouse
Positional relationship between functional area and each functional area, the host are also used to obtain the dbjective state of the robot
And/or the dbjective state of the package, and the dbjective state of the dbjective state of the robot and/or the package is determined as
The dbjective state of described problem description.
Further, the host is also used to obtain the corresponding original state parameter of original state of described problem description,
Wherein, the original state parameter includes priority parameters, threshold parameter and dynamic parameter.
Further, the host is also used to obtain the corresponding dbjective state parameter of dbjective state of described problem description,
Wherein, the dbjective state parameter includes multiple essential dbjective state parameters and multiple optional dbjective state parameters.
Other features and advantages of the present invention will be illustrated in subsequent specification, also, partly be become from specification
It is clear that by implementing understanding of the embodiment of the present invention.The objectives and other advantages of the invention can be by written theory
Specifically noted structure is achieved and obtained in bright book, claims and attached drawing.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is a kind of flow diagram of Intelligent planning method provided by the embodiments of the present application；
Fig. 2 is a kind of structural block diagram of small watersheds provided by the embodiments of the present application；
Fig. 3 is a kind of flow diagram of Intelligent planning method step S120 provided by the embodiments of the present application；
Fig. 4 is a kind of topographic map in warehouse provided by the embodiments of the present application；
Fig. 5 is a kind of working principle diagram of Intelligent planning method provided by the embodiments of the present application.
Specific embodiment
Below in conjunction with attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Ground description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Usually exist
The component of the embodiment of the present invention described and illustrated in attached drawing can be arranged and be designed with a variety of different configurations herein.Cause
This, is not intended to limit claimed invention to the detailed description of the embodiment of the present invention provided in the accompanying drawings below
Range, but it is merely representative of selected embodiment of the invention.Based on the embodiment of the present invention, those skilled in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall within the protection scope of the present invention.
It should also be noted that similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, does not then need that it is further defined and explained in subsequent attached drawing.Meanwhile of the invention
In description, term " first ", " second " etc. are only used for distinguishing description, are not understood to indicate or imply relative importance.
Fig. 1 is please referred to, Fig. 1 is a kind of flow diagram of Intelligent planning method provided by the embodiments of the present application, the method
Include the following steps:
Step S110: the field description in storage field is obtained.
Field is described as the model for being used to describe storage scene of the domain knowledge building based on storage field.
Step S120: the problem of obtaining storage problem to be planned description.
Storage problem is described problem description the problem of processing using the robot in warehouse the package in warehouse
Including the different priorities being correspondingly arranged for the different distance between the robot and the package.Wherein it is possible to pass through
Setting priority parameters are indicated priority, for example, it is contemplated that robot is with the shelf in warehouse at a distance from, then basis away from
From priority parameters are arranged, priority parameters are higher, illustrate that robot is smaller at a distance from shelf, and priority is high, select excellent
The high robot of first grade goes to complete warehousing and storage activities, can reduce the warehousing and storage activities time accordingly, to improve storage efficiency.
In storage field, Intelligent planning method the problem of being planned referred to as storage problem, storage problem can be referred to
The problem of being handled using the robot in warehouse the package in warehouse, the usually corresponding warehousing and storage activities of storage problem are appointed
Business.In general, each warehouse all corresponds to the storage problem of oneself, when being planned, usually each warehouse is independently advised
It draws, therefore is illustrated to simplify, it is believed that the scope limitation of planning is being one of warehouse that small watersheds are managed.
Step S130: being input to planner with described problem description for field description and plan, generates global rule
Draw solution.
Field description may be constructed the STRIPS classical planning model in intelligent planning field with problem description, and planner is used for
To the model programming evaluation.Here planner can use the existing planner in intelligent planning field, for example, it may be but not
It is limited to one of FF planner and LAMA planner.
Step S140: the programming dispatching sequence of the robot is extracted from the Global motion planning solution and by the planning
Schedule sequences are sent to the robot.
The Global motion planning solution obtained from planner needs to extract and be converted into the information that robot can identify, advises from the overall situation
The programming dispatching sequence extracted in solution is drawn, after each robot obtains schedule sequences, executes and is acted accordingly in schedule sequences, i.e.,
The corresponding warehousing and storage activities task of achievable storage problem, makes storage problem be changed into dbjective state by original state in other words.
During above-mentioned realization, then the field description in acquisition storage field first obtains storage problem to be planned
The problem of describe, field is described later and description is input to planner the problem of including priority, using in planner
Planning algorithm carries out Global motion planning to storage problem, obtains Global motion planning solution, finally sends out the schedule sequences in Global motion planning solution
Send to robot, so that robot executes corresponding movement according to schedule sequences, complete storehouse warehousing and storage activities task, so as to from
Macroscopic aspect is realized to the overall scheduling of multirobot, can effectively be cooperated, and completes warehousing and storage activities task, has
Effect reduces logistics cost.
In addition, the description of field involved in the above method and system is the universal model for describing storage scene, the mould
Usually it can be used repeatedly after creation for type, it is seldom necessary to which the case where modifying, user only need to repair for specific storage problem
Change problem description, therefore the above method and system have good portable and scalability, and can be efficiently
The planning to storage problem is completed, and then the efficiency and program results quality of planning can be improved.
Referring to figure 2., Fig. 2 is a kind of structural block diagram of small watersheds provided by the embodiments of the present application, a set of intelligence
Planning system can be deployed in one or more warehouses (three are shown in Fig. 2), small watersheds include host and with master
The robot of machine communication connection.
Robot at least disposes a robot for executing warehousing and storage activities, each warehouses such as loading cargo, unloading cargo,
Fig. 2 shows robot do not limit the quantity of robot, the case where quantity of robot can be according to warehouse, robot are available
The case where quantity and warehousing and storage activities arranges, for example, most multipotency arranges 10 robots in warehouse A, available machine at this time
People's quantity only has 8, but we need 5 robots to complete warehousing and storage activities in the works, then the machine finally arranged in warehouse A
Device people can be 5, if we plan that 9 robots is needed to complete warehousing and storage activities, since available robot quantity is inadequate,
The robot then finally arranged in warehouse A can be 8.
Host is used to be scheduled robot using Intelligent planning method provided in an embodiment of the present invention, host setting
Position is not construed as limiting, and be can be set in warehouse, also be can be set long-range.It should be understood that host here should make broad sense
Understand, is not limited to the computer or server of separate unit, is also possible to the cluster of multiple stage computers or server, or even also not necessarily
It is strictly corresponding with physical equipment, such as can also be virtual machine, Cloud Server etc..
For example, host can be set in warehouse, then staff need warehouse can by control host come pair
Robot is scheduled, and for another example, host can be set in outside warehouse, such as the main frame of office, and the office and storehouse
There is a certain distance in library, and host can realize by network communication and be scheduled to robot that this outdoor main unit can also be set to
Other intelligent terminals, such as smart phone, Intelligent flat.
As an implementation, small watersheds can also include the station acquisition device connecting with main-machine communication,
Station acquisition device is used to acquire the location information of robot and package in warehouse, and sends it to host, so that main
Machine determines the current location of robot and package, so that host be assisted to carry out intelligent planning.Station acquisition device may include
At least one of camera and infrared sensor device, naturally it is also possible to using other sensors with positioning function.
It should be understood that can also be positioned by other means to robot and package, example in some other embodiment
Such as robot and superscribe setting two dimensional code, RFID label tag, in robot install GPS module mode.
Fig. 3 is please referred to, Fig. 3 is a kind of flow diagram of Intelligent planning method step S120 provided by the embodiments of the present application,
Step S120 includes the following steps:
Step S121: the topograph in the warehouse is obtained.
The topograph includes the positional relationship between the functional area and each functional area in the warehouse.For example,
Functional area in warehouse can be divided into storage area and unloading area, and storage area include it is several, can also be to depositing
It stores region and carries out label,
Step S122: the original state of the robot and/or the original state of the package are obtained.
Step S123: by the initial shape of the original state and/or the package of the topograph and the robot
State is determined as the original state of described problem description.
Step S124: the dbjective state of the robot and/or the dbjective state of the package are obtained.
Step S125: the dbjective state of the dbjective state of the robot and/or the package is determined as described problem
The dbjective state of description.
During above-mentioned realization, problem description includes the topograph in warehouse, can entire landform to warehouse and
Situations such as functional area, carries out detailed embodiment, the original state of the original state and/or package of topograph and robot
It is determined as the original state of problem description, can accurately grasps the original state in storage problem to be planned.
Specifically, step S120 further includes following steps:
Obtain the corresponding original state parameter of original state of described problem description, wherein the original state parameter packet
Include priority parameters, threshold parameter and dynamic parameter.
Such as, it may be considered that then priority parameters are arranged at a distance from shelf in warehouse in robot according to distance, excellent
First grade parameter is higher, illustrates that robot is smaller at a distance from shelf, then can preferentially select and shelf are apart from small robot
Implementary plan movement.Such as, then original state parameter is arranged to robot in the artificial robot of machine, is robot1 (x1), robot2
(x1), wherein parameter x1 indicates that the distance between robot and shelf priority, the value of parameter x1 are smaller, then it represents that priority is got over
The default value of height, parameter x1 can be set to 0, when parameter x1 be default value 0 when, can indicate between robot and shelf away from
From being temporarily not detected, after station acquisition appliance arrangement gets the distance between robot and shelf, parameter x1 is carried out
It updates.
It should be understood that when the parameter x1 in robot1 (x1) is default value 0, then it represents that No.1 robot is not detected
The distance between shelf can not be planned and be dispatched by priority to No.1 robot, the ginseng in robot1 (x1)
Number x1 be parameter x1 in 1, robot2 (x1) when being 3, then may indicate that the distance priority grade of No.1 robot higher than No. two machines
Device people can also indicate that the distance between No.1 robot and shelf are relatively close for No. two robots.
As an implementation, robot can be obtained at a distance from shelf by station acquisition device, including be taken the photograph
As at least one of head and infrared sensor device, other sensors with positioning function can also be used.
For another example, it may be considered that the significance level of package is arranged priority according to the significance level of package, and is arranged corresponding
Importance priority parameter, importance priority parameter is bigger, illustrates that package is more important, more needs to be handled as early as possible, such as adds
Anxious package etc..In addition to this, in order to prevent portion envelops because priority it is too low, for a long time can not shipment, there is hunger phenomenon, can
Time priority is arranged to package, and Time priority parameter is set accordingly, Time priority parameter can indicate to wrap up
The time stored in warehouse is more long, more needs to be handled as early as possible.
For example, package is package, then the priority parameters that can carry out original state to package are configured, e.g.,
Package (x1, x2), wherein parameter x1 is the importance priority parameter of package, indicates that the importance of package, parameter x1 value are got over
Greatly, then it can indicate that the significance level of the package is bigger, the default value of parameter x1 can be set to 0, indicate that the package is common
Package；Parameter x2 is the Time priority parameter of package, and parameter x2 value is bigger, then can indicate to be wrapped in waited in warehouse when
Between it is longer, priority is higher accordingly, and the default value of parameter x2 can be set to 0, indicate the package wait time be 0, ginseng
The time that the value of number x2 can wait in planning process according to the package carries out dynamic modification.
As an implementation, in order to comprehensively consider importance priority and Time priority, it is excellent that third can be set
First grade parameter assesses final priority, and third priority parameters can be understood as coefficient of balance, pass through package
Three priority parameters may determine that last priority, then selected currently handle according to last priority
Package.
Importance priority parameter can be arranged by hand in modeling process, and Time priority parameter is default value, furthermore
Time priority parameter can carry out dynamic change by host in planning process, and third priority parameter can be set to default
Value, can also dynamically change in planning process.
In view of actual conditions, uncertainty event may be occurred in the process by transporting kinds of goods, as interim event occurs in robot
The reasons such as barrier, terrain issues will cause transport procedure failure, in robot scheduling process, merely because current robot is primary
Failure and abandon the next scheduling process of this robot, or directly ignore robot failure the case where, it is above to appearance not
Determine situation processing be all it is unreasonable, may result in planning and low-quality planning occur and solve.
Dynamic parameter and threshold parameter can be set, if robot because of certain failures, such as not enough power supply or component
Failure etc. causes scheduling to fail, then and after robot recovery state, can such as have been charged by reducing the value of dynamic parameter
After the completion of electricity or maintenance, then this variate-value is improved, wherein if dynamic parameter is repeatedly lowered, until lower than the threshold set
Value parameter then can be determined that the robot fails, and delete the robot in planning.
It is intelligible, it can be to upper goods area loadingarea, memory block storearea, shipping space deliverarea etc.
Similar dynamic parameter and threshold parameter is equally arranged in goods area, when failing when robot because of terrain issues, can reduce this
Dynamic parameter, when dynamic parameter repeatedly reduces, after setting threshold parameter, then in next planning process, by this goods area from
It is deleted in planning.
For example, robot1 (x1, x2, x3, x4), robot2 (x1, x2, x3, x4), wherein parameter x1 indicate robot with
The distance between shelf priority, details are not described herein again, and parameter x2 and parameter x3 are dynamic parameter, and parameter x4 indicates threshold value, such as
Robot1 (1,1,0.2,0), which is arranged, indicates the original state of robot, wherein x1=1, x2=1, x3=0.2, x4=0 work as machine
The scheduling of device people fails, then parameter x2 value will be lowered, and the value that parameter x2 is reduced is the value of parameter x3, then parameter x2 after reducing
Value be 0.8, when the value of parameter x2 is reduced to the value lower than parameter x4, robot1 can be considered failure, and delete in planning
The related content of robot1, the correlation of robot1 will not be considered into open space planning in the planning of next time.
Particularly, the goods areas such as upper goods area loadingarea, memory block storearea, shipping space deliverarea can also
Dynamic parameter and threshold parameter to be arranged accordingly, for example, loadingarea (x1, x2, x3), storearea (x1, x2,
X3), deliverarea (x1, x2, x3), parameter x1, parameter x2 and parameter x3 therein indicate identical for different acquisitions
Meaning, be illustrated herein just for storearea (x1, x2, x3), storearea1 (1,0.2,0) be memory block just
Beginning state, wherein x1=1, x2=0.2, x3=0, when robot scheduling due to the landform of memory block either memory block
Other reasons and failure when, then the value of parameter x1 will be lowered, parameter x1 reduce value be parameter x2 value, then reduce after
The value of parameter x1 is 0.8, and when the value of parameter x1 is reduced to the value lower than parameter x3, storearea1 can be considered failure, and
The related content of storearea1 is deleted in planning, the correlation of storearea1 will not be considered into rule in the planning of next time
Draw content.
During above-mentioned realization, need to obtain the corresponding original state parameter of original state of problem description, initial shape
State parameter can specifically be embodied original state by way of data, and can pass through the meter to original state parameter
The modes such as calculation, to realize the control of the original state to problem description.
Optionally, described the problem of obtaining storage problem to be planned, describes, further includes: obtains the mesh of described problem description
The corresponding dbjective state parameter of mark state, wherein the dbjective state parameter includes multiple essential dbjective state parameters and multiple
Optional dbjective state parameter.
Under the complex situations of reality, the planning procedure in planner not necessarily can be to the model of satisfaction input, and asks
It must plan solution, so the corresponding setting dbjective state parameter of dbjective state for needing to describe problem, including multiple essential
Dbjective state parameter and multiple optional dbjective state parameters, to realize that planning obtains local solution, essential dbjective state parameter list
Show the target be it is essential, optional dbjective state parameter indicate the target be it is optional, when optional target cannot achieve, but must
When the target of choosing is fully completed, the planning solution which obtains is considered local solution,.
During above-mentioned realization, need to obtain the corresponding dbjective state parameter of dbjective state of problem description, target-like
The corresponding dbjective state parameter of state can be showed original state by specific data, and in planning process, mesh
The setting of mark state parameter can make planning procedure realize the solution of local solution, realize the flexibility of planning.
Optionally, further include following steps after step S130:
Judge whether the Global motion planning solution is to meet the multiple essential dbjective state parameter and the multiple optional
Dbjective state parameter, if so, showing that the Global motion planning solution is global solution.
The Global motion planning solution is judged to meet the multiple essential dbjective state parameter and the multiple optional target
The optional dbjective state parameter in the part of state parameter, if so, showing that the Global motion planning solution is local solution.
It is corresponding with the dbjective state of problem description to have target, for example, target is stored package (x1), join herein
Number x1 can indicate that the dbjective state of the target is that optional target or essential target indicate the target if parameter x1 is 1
Dbjective state is essential target, if parameter x1 is 0, indicates that the dbjective state of the target is optional target.It should be understood that must
Target is selected to be fully completed, no matter optional target completes how many, all can be considered that the planner successfully finds out planning solution.
Optionally, the field description and described problem description are described by PDDL language, in the field
Institute's object, predicate and movement to be used in described problem description is stated in description.
As an implementation, field description can be used, but be not limited to be described using PDDL language, and field is retouched
It states as the domain knowledge building based on storage field for describing the model of storage scene, following field coded description gives
An example being described using PDDL language, configuration file can be written in these description contents by user, then by host
It reads and obtains field description.
Field coded description:
Above-mentioned code is largely divided into three parts: object, predicate and movement illustrated separately below, object, predicate
And the concept of movement has corresponding definition in PDDL language.
Object refers to entity involved in storage scene of the present invention.In above-mentioned code, object includes machine
People robot, the region area in warehouse and package package, wherein region can be further divided into three kinds of functional areas again,
It is respectively: upper goods area loadingarea, memory block storearea and deliveryarea.It may be noted that being described in field
In only state in storage scene that there are above-mentioned objects, but it is not instantiated, such as do not describe to have in warehouse
Which robot body has.
Predicate refers to attribute possessed by object, and value is true or false.In above-mentioned code, under predicate includes
6, face:
Available? r-robot
Whether robot r can be used
Carrying? r-robot? p-package
Whether robot r is carrying package p
At? x- (either robot package)? a-area
Whether robot x's or package x is located at region a
Clear? s-storearea
Whether memory block s is empty
Connected? a1? a2-area
Whether region a1 is connected to a2
Stored? p-package
Whether package p has stored
Movement refers to the behavior of the object in storage scene, is primarily referred to as the behavior of robot in embodiments of the present invention,
But the behavior of robot is also related to other objects.In above-mentioned code, movement includes following 5:
Load-store: robot loads cargo in upper goods area, and load indicates that this movement is to load cargo, store table
The purpose of this bright movement is to store cargo.
Load-deliver: robot loads cargo in memory block, and load indicates that this movement is to load cargo,
The purpose that deliver indicates this movement is to deliver.
Unload-store: robot unloads cargo in memory block, and unload indicates that this movement is unloading cargo,
The purpose that store shows this movement is to store cargo.
Unload-deliver: robot shipping space unloads cargo, and unload indicates that this movement is unloading cargo,
The purpose that deliver indicates this movement is to deliver.
Move: robot is moved to another region from a region.
It is introduced by taking load-store as an example below and how to describe a movement:
The movement includes three parameter parameters, is robot r respectively, wraps up p and upper goods area
loadingarea。
The precondition precondition of the movement is that robot r can be used, and robot r is located at upper goods area
Loadingarea, package p are located at upper goods area loadingarea, and only when meeting the precondition, which can just be executed.
Effect effect after the movement executes is that robot r is unavailable, and robot r is carrying package p, wraps up the not position p
In upper goods area loadingarea, effect reflects the state of each object after movement executes.
For the description of other movements, it is referred to load-store and is understood, no longer illustrated one by one here.
It should be understood that the content of above-mentioned field description is merely illustrative, in the specific implementation, the content of field description can be with
With difference above.
Particularly, field description usually describes a kind of general storage scene, as long as therefore storage scene do not occur
Variation, field, which describes established model, need to only establish once, can use always later, without modifying.
In addition, the original state of problem description includes the topograph in warehouse, topograph is carried out to the landform in warehouse
Modeling as a result, particular content may include which functional area warehouse has, the contents such as positional relationship between these functional areas.
The original state of problem description further includes the original state of robot and/or the original state of package.Wherein, machine
The original state of people may include having which robot in warehouse, the contents such as initial position of these robots, it is however generally that, machine
The initial position of device people just refers to the current position of robot.The original state of package may include having which package in warehouse,
The contents such as the initial position of these packages, it is however generally that, the initial position of package, which just refers to, wraps up current position.According to before
Elaboration, in the certain embodiments of the embodiment of the present invention, position information acquisition device acquisition position information is simultaneously sent to master
Machine, host, which carries out analysis to location information, can be obtained the initial position of robot and the initial position of package.
It may be noted that the specific storage problem of view, the original state of problem description may include the original state of robot
And or package one of original state, when both can also include simultaneously, such as only include the original state of package, table
Show the original state for not limiting robot.
The dbjective state of problem description includes the dbjective state of robot and/or the dbjective state of package, usually corresponds to storehouse
Store up job task.Wherein, the dbjective state of robot may include the contents such as the target position of robot, the target position of robot
Set just refer to executed warehousing and storage activities task after it is expected the location of robot.The dbjective state of package may include package
The contents such as target position, the target position of package just refers to executed warehousing and storage activities task after expectation wrap up the location of.
In one embodiment, problem description can be used, but be not limited to be described using PDDL language.Following
Problem coded description gives an example being described using PDDL language, these description contents can be written by user matches
File is set, then read by host and obtains problem description.It should be understood that certain contents in problem description, such as machine
The initial position of people can automatically write configuration file by host, and prompt can also be provided by host, and user is written according to prompt
Configuration file.
Problem coded description:
In the part objects of above-mentioned code, object involved in problem is described, but different with field description, asked
Object is instantiated in topic description, such as pointing out it to robot includes two machines of robot1 and robot2
People, pointing out it to package includes package1 to package7 seven packages, please refers to Fig. 4, and Fig. 4 is the application implementation
A kind of topographic map in warehouse that example provides, in the warehouse topographic map, to region point out including a upper goods area
Loadingarea1, nine memory block storearea1-1 to storearea3-3 and three shipping space deliverarea1 are extremely
deliverarea3。
In the part init of above-mentioned code, the current shape of robot and package is described by predicate (value true)
Condition, including robot are available, and the position of robot, the position of package and storage region are empty several contents.In the part init
AREA DESCRIPTION then describe the positional relationship between each functional area in warehouse, for example, its description content can
As space is limited, to be omitted here the content of AREADESCRIPTION referring to Fig. 4.
Original state in the part objects and the description of init partial correspondence problem of above-mentioned code.Wherein shut down
The content of people, that is, robot above-mentioned original state, in relation to the content, that is, package above-mentioned initial shape wrapped up
State, content, that is, warehouse above-mentioned topograph of the functional area in relation to warehouse.
Dbjective state in the goal partial correspondence problem description of above-mentioned code.In the part goal of above-mentioned code, pass through
Predicate (value true) describes the dbjective state of package, including package has stored a content.In this example,
The not dbjective state of designated robot, puts package well as long as meaning, does not make to the dbjective state of robot
Limitation.
It should be understood that the content of above problem description is merely illustrative, in the specific implementation, the content of problem description can be with
With difference above.
In addition, problem description is to be directed to specific warehouse and specific warehousing and storage activities task,
User is required when therefore being planned for different storage problems redefines corresponding problem description.
Particularly, the data that problem describes can also be divided into static data and dynamic data.The objects of above-mentioned code
The content of part and AREADESCRIPTION belong to part constant in problem, therefore the static number of also referred to as problem description
According to rest part belongs to the part that can be changed in problem, therefore the dynamic data of also referred to as problem description.
Referring to figure 5., Fig. 5 a kind of working principle diagram of Intelligent planning method provided by the embodiments of the present application.Robot
The Planning i.e. corresponding schedule sequences of the robot below robot1, it is seen then that the content of schedule sequences may include multiple
Pass through the movement of PDDL language definition in the description of field, remaining robot is similar with robot1, all may be used after step S140 execution
To obtain respective schedule sequences.Rest part in Fig. 4 has illustrated that it will not be described here in each step before.Respectively
It after a robot obtains schedule sequences, executes and is acted accordingly in schedule sequences, the corresponding storage of storage problem can be completed and make
Industry task makes storage problem be changed into dbjective state by original state in other words.
Please refer to Fig. 2, a kind of small watersheds provided by the embodiments of the present application include host and logical with the host
Believe that the robot of connection, the robot are arranged in warehouse；Host be used for obtain storage field field description, and obtain to
The problem of storage problem of planning, describes, and field description is input to planner with described problem description and is planned,
Global motion planning solution is generated, the programming dispatching sequence of the robot is extracted from the Global motion planning solution and adjusts the planning
Degree series are sent to the robot, wherein the field is described as the use of the building of the domain knowledge based on the storage field
In description storage scene model, the storage problem be using the robot in warehouse to the package in the warehouse at
The problem of reason, described problem description include the difference being correspondingly arranged for the different distance between the robot and the package
Priority；The robot is used to execute corresponding movement based on the schedule sequences, completes the corresponding storehouse of the storage problem
Store up job task.
Optionally, the host is used to obtain the topograph in the warehouse, and obtains the initial shape of the robot
The original state of state and/or the package, and by the original state of the topograph and the robot and/or described
The original state of package is determined as the original state of described problem description, wherein the topograph includes the function in the warehouse
Can positional relationship between region and each functional area, the host be also used to obtain the robot dbjective state and/
Or the dbjective state of the package, and the dbjective state of the dbjective state of the robot and/or the package is determined as institute
State the dbjective state of problem description.
Optionally, the host is also used to obtain the corresponding original state parameter of original state of described problem description,
In, the original state parameter includes priority parameters, threshold parameter and dynamic parameter.
Optionally, the host is also used to obtain the corresponding dbjective state parameter of dbjective state of described problem description,
In, the dbjective state parameter includes multiple essential dbjective state parameters and multiple optional dbjective state parameters.
The embodiment of the present application provides a kind of read/write memory medium, when the computer program is executed by processor, executes
Method process performed by electronic equipment in embodiment of the method as shown in Figure 1.
It is apparent to those skilled in the art that for convenience and simplicity of description, the device of foregoing description
Specific work process, no longer can excessively be repeated herein with reference to the corresponding process in preceding method.
In conclusion method and system provided by the embodiments of the present application can be by the method for intelligent planning, from Macro
Face realizes to the overall scheduling of multirobot, at the same consider robot with the distance between wrap up and it is corresponding priority is set, from
And make effectively cooperate between each robot, and then optimal scheme is taken to complete warehousing and storage activities task, have
Effect reduces logistics cost.In addition, the description of field involved in the above method and system is the Universal Die for describing storage scene
Type, usually it can be used repeatedly after creation for the model, it is seldom necessary to which the case where modifying, user only need for specific storage
Problem modifies problem description, therefore the above method and system have good portability compared to existing planing method
And scalability, and can efficiently complete the planning to storage problem.
In several embodiments provided herein, it should be understood that disclosed device and method can also pass through
Other modes are realized.The apparatus embodiments described above are merely exemplary, for example, flow chart and block diagram in attached drawing
Show the device of multiple embodiments according to the present invention, the architectural framework in the cards of method and computer program product,
Function and operation.In this regard, each box in flowchart or block diagram can represent the one of a module, section or code
Part, a part of the module, section or code, which includes that one or more is for implementing the specified logical function, to be held
Row instruction.It should also be noted that function marked in the box can also be to be different from some implementations as replacement
The sequence marked in attached drawing occurs.For example, two continuous boxes can actually be basically executed in parallel, they are sometimes
It can execute in the opposite order, this depends on the function involved.It is also noted that every in block diagram and or flow chart
The combination of box in a box and block diagram and or flow chart can use the dedicated base for executing defined function or movement
It realizes, or can realize using a combination of dedicated hardware and computer instructions in the system of hardware.
In addition, each functional module in each embodiment of the present invention can integrate one independent portion of formation together
Point, it is also possible to modules individualism, an independent part can also be integrated to form with two or more modules.
It, can be with if the function is realized and when sold or used as an independent product in the form of software function module
It is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be a
People's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
And storage medium above-mentioned includes: that USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic or disk.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.It should also be noted that similar label and letter exist
Similar terms are indicated in following attached drawing, therefore, once being defined in a certain Xiang Yi attached drawing, are then not required in subsequent attached drawing
It is further defined and explained.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to
Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that
There is also other identical elements in process, method, article or equipment including the element.
Claims (10)
1. a kind of Intelligent planning method, which is characterized in that the described method includes:
The field description in storage field is obtained, the field is described as being used for for the building of the domain knowledge based on the storage field
The model of description storage scene；
The problem of obtaining storage problem to be planned description, the storage problem are using the robot in warehouse to the warehouse
In package the problem of being handled, described problem description includes for the different distance between the robot and the package
The different priorities being correspondingly arranged；
Field description is input to planner with described problem description to plan, generates Global motion planning solution；
The programming dispatching sequence of the robot is extracted from the Global motion planning solution and sends the programming dispatching sequence
To the robot.
2. Intelligent planning method according to claim 1, which is characterized in that described to obtain asking for storage problem to be planned
Topic description, comprising:
The topograph in the warehouse is obtained, the topograph includes the functional area and each functional area in the warehouse
Between positional relationship；
Obtain the original state of the robot and/or the original state of the package；
The original state of the original state and/or the package of the topograph and the robot is determined as described
The original state of problem description；
Obtain the dbjective state of the robot and/or the dbjective state of the package；
The dbjective state of the dbjective state of the robot and/or the package is determined as to the target-like of described problem description
State.
3. Intelligent planning method according to claim 2, which is characterized in that described to obtain asking for storage problem to be planned
Topic description, further includes:
Obtain the corresponding original state parameter of original state of described problem description, wherein the original state parameter includes excellent
First grade parameter, threshold parameter and dynamic parameter.
4. Intelligent planning method according to claim 2, which is characterized in that described to obtain asking for storage problem to be planned
Topic description, further includes:
Obtain the corresponding dbjective state parameter of dbjective state of described problem description, wherein the dbjective state parameter includes more
A essential dbjective state parameter and multiple optional dbjective state parameters.
5. Intelligent planning method according to claim 4, which is characterized in that described to describe the field and described problem
Description is input to planner and is planned, after generation Global motion planning solution, further includes:
Judge whether the Global motion planning solution is to meet the multiple essential dbjective state parameter and the multiple optional target
State parameter, if so, showing that the Global motion planning solution is global solution；
The Global motion planning solution is judged to meet the multiple essential dbjective state parameter and the multiple optional dbjective state
The optional dbjective state parameter in the part of parameter, if so, showing that the Global motion planning solution is local solution.
6. Intelligent planning method according to any one of claims 1-5, which is characterized in that the field description and institute
It states problem description to be described by PDDL language, institute is to be used in the description of statement described problem in the description of the field
Object, predicate and movement.
7. a kind of small watersheds characterized by comprising host and the robot being connect with the main-machine communication, institute
Robot is stated to be arranged in warehouse；
The problem of host is for obtaining the field description in storage field, and obtaining storage problem to be planned describes, and
Field description is input to planner with described problem description to plan, generates Global motion planning solution, from the global rule
It draws and extracts the programming dispatching sequence of the robot in solution and the programming dispatching sequence is sent to the robot,
In, the field is described as the model for being used to describe storage scene of the building of the domain knowledge based on the storage field, described
Storage problem is the problem of processing using the robot in warehouse the package in the warehouse, and described problem description includes
The different priorities being correspondingly arranged for the different distance between the robot and the package；
The robot is used to execute corresponding movement based on the schedule sequences, completes the corresponding storage of the storage problem and makees
Industry task.
8. small watersheds according to claim 7, which is characterized in that the host is used to obtain the ground in the warehouse
Shape description, and obtain the original state of the robot and/or the original state of the package, and by the topograph,
And the original state of the robot and/or the original state of the package are determined as the original state of described problem description,
Wherein, the topograph includes the positional relationship between the functional area and each functional area in the warehouse, the host
It is also used to obtain the dbjective state of the robot and/or the dbjective state of the package, and by the target-like of the robot
State and/or the dbjective state of the package are determined as the dbjective state of described problem description.
9. small watersheds according to claim 8, which is characterized in that the host is also used to obtain described problem and retouches
The corresponding original state parameter of the original state stated, wherein the original state parameter include priority parameters, threshold parameter and
Dynamic parameter.
10. small watersheds according to claim 9, which is characterized in that the host is also used to obtain described problem
The corresponding dbjective state parameter of the dbjective state of description, wherein the dbjective state parameter includes multiple essential dbjective state ginsengs
Several and multiple optional dbjective state parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910019184.9A CN109669462A (en) | 2019-01-08 | 2019-01-08 | Intelligent planning method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910019184.9A CN109669462A (en) | 2019-01-08 | 2019-01-08 | Intelligent planning method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109669462A true CN109669462A (en) | 2019-04-23 |
Family
ID=66149390
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910019184.9A Pending CN109669462A (en) | 2019-01-08 | 2019-01-08 | Intelligent planning method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109669462A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111461640A (en) * | 2020-03-05 | 2020-07-28 | 四川九洲电器集团有限责任公司 | Generalized task action planning method |
| CN116302449A (en) * | 2023-05-17 | 2023-06-23 | 鹏城实验室 | Cross-agent algorithm resource scheduling method, device, equipment and medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070299802A1 (en) * | 2007-03-31 | 2007-12-27 | Mitchell Kwok | Human Level Artificial Intelligence Software Application for Machine & Computer Based Program Function |
| JP2010033256A (en) * | 2008-07-28 | 2010-02-12 | Sinfonia Technology Co Ltd | Carrying system and program for carrying system |
| CN103747453A (en) * | 2014-01-15 | 2014-04-23 | 武汉大学 | Online open planning supporting method and system for dissimilar intelligent wireless sensors |
| CN105467997A (en) * | 2015-12-21 | 2016-04-06 | 浙江工业大学 | Storage robot path program method based on linear temporal logic theory |
| CN107618803A (en) * | 2017-09-25 | 2018-01-23 | 芜湖智久机器人有限公司 | A kind of quick storehouse management AGV trolley control systems for quickly taking cargo transport thing |
-
2019
- 2019-01-08 CN CN201910019184.9A patent/CN109669462A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070299802A1 (en) * | 2007-03-31 | 2007-12-27 | Mitchell Kwok | Human Level Artificial Intelligence Software Application for Machine & Computer Based Program Function |
| JP2010033256A (en) * | 2008-07-28 | 2010-02-12 | Sinfonia Technology Co Ltd | Carrying system and program for carrying system |
| CN103747453A (en) * | 2014-01-15 | 2014-04-23 | 武汉大学 | Online open planning supporting method and system for dissimilar intelligent wireless sensors |
| CN105467997A (en) * | 2015-12-21 | 2016-04-06 | 浙江工业大学 | Storage robot path program method based on linear temporal logic theory |
| CN107618803A (en) * | 2017-09-25 | 2018-01-23 | 芜湖智久机器人有限公司 | A kind of quick storehouse management AGV trolley control systems for quickly taking cargo transport thing |
Non-Patent Citations (1)
| Title |
|---|
| 黄卓: "基于landmark可纳排序的规划系统研究及应用", 《中国优秀硕士论文全文数据库 信息科技辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111461640A (en) * | 2020-03-05 | 2020-07-28 | 四川九洲电器集团有限责任公司 | Generalized task action planning method |
| CN116302449A (en) * | 2023-05-17 | 2023-06-23 | 鹏城实验室 | Cross-agent algorithm resource scheduling method, device, equipment and medium |
| CN116302449B (en) * | 2023-05-17 | 2023-08-22 | 鹏城实验室 | Cross-agent algorithm resource scheduling method, device, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6759512B2 (en) | Warehouse layout optimization based on customizable goals | |
| CN110097315B (en) | Container determination method, container determination device, medium, and computing apparatus | |
| Amato et al. | An approach to control automated warehouse systems | |
| Huang et al. | Robotics in ecommerce logistics | |
| US20170046654A1 (en) | Free location item and storage retrieval | |
| CN105404540B (en) | A kind of method, system and the remote server of robot remote upgrading | |
| US8423391B2 (en) | Systems and methods for automated parallelization of transport load builder | |
| US20200005226A1 (en) | Automated guided vehicle control and organizing inventory items using stock keeping unit clusters | |
| Manners-Bell et al. | The logistics and supply chain innovation handbook: disruptive technologies and new business models | |
| CN109657888A (en) | A kind of AGV task creating method, device, electronic equipment and storage medium | |
| Qin et al. | JD. com: Operations research algorithms drive intelligent warehouse robots to work | |
| US20200279204A1 (en) | Method for processing item sorting scheduling request, and related device | |
| CN111754182A (en) | Library management method, library management device, server, robot, system and storage medium | |
| CN109669462A (en) | Intelligent planning method and system | |
| Simić et al. | Modelling material flow using the Milk run and Kanban systems in the automotive industry | |
| US11797721B2 (en) | Computer-aided warehouse space planning | |
| Figueiras et al. | Big data provision for digital twins in industry 4.0 logistics processes | |
| US10926952B1 (en) | Optimizing storage space utilizing artificial intelligence | |
| Zoubek et al. | Methodology proposal for storage rationalization by implementing principles of industry 4.0. in a technology-driven warehouse | |
| Li et al. | A solution for cross-docking operations planning, scheduling and coordination | |
| US20080028057A1 (en) | System and method to facilitate design and operation of event-driven, embedded solutions | |
| US20220351133A1 (en) | Modeling dynamic material flow in generative design using topological maps | |
| US11164147B2 (en) | Computer storage system for generating warehouse management orders | |
| CN114435816A (en) | Storage position distribution method for checking of three-dimensional storehouse | |
| CN117021073A (en) | Robot control method and device, electronic equipment and readable storage medium |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190423 |
|
| RJ01 | Rejection of invention patent application after publication |